# -*- coding: utf-8 -*-
# Copyright 2023 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import os

# try/except added for compatibility with python < 3.8
try:
    from unittest import mock
    from unittest.mock import AsyncMock  # pragma: NO COVER
except ImportError:  # pragma: NO COVER
    import mock

from collections.abc import Iterable
import json
import math

from google.api_core import (
    future,
    gapic_v1,
    grpc_helpers,
    grpc_helpers_async,
    operation,
    operations_v1,
    path_template,
)
from google.api_core import api_core_version, client_options
from google.api_core import exceptions as core_exceptions
from google.api_core import operation_async  # type: ignore
import google.auth
from google.auth import credentials as ga_credentials
from google.auth.exceptions import MutualTLSChannelError
from google.longrunning import operations_pb2  # type: ignore
from google.oauth2 import service_account
from google.protobuf import empty_pb2  # type: ignore
from google.protobuf import field_mask_pb2  # type: ignore
from google.protobuf import json_format
from google.protobuf import timestamp_pb2  # type: ignore
import grpc
from grpc.experimental import aio
from proto.marshal.rules import wrappers
from proto.marshal.rules.dates import DurationRule, TimestampRule
import pytest
from requests import PreparedRequest, Request, Response
from requests.sessions import Session

from google.cloud.automl_v1beta1.services.auto_ml import (
    AutoMlAsyncClient,
    AutoMlClient,
    pagers,
    transports,
)
from google.cloud.automl_v1beta1.types import (
    model_evaluation,
    operations,
    regression,
    service,
)
from google.cloud.automl_v1beta1.types import (
    tables,
    text,
    text_extraction,
    text_sentiment,
    translation,
    video,
)
from google.cloud.automl_v1beta1.types import annotation_spec, classification
from google.cloud.automl_v1beta1.types import column_spec
from google.cloud.automl_v1beta1.types import column_spec as gca_column_spec
from google.cloud.automl_v1beta1.types import data_stats, data_types
from google.cloud.automl_v1beta1.types import dataset
from google.cloud.automl_v1beta1.types import dataset as gca_dataset
from google.cloud.automl_v1beta1.types import detection, image, io
from google.cloud.automl_v1beta1.types import model
from google.cloud.automl_v1beta1.types import model as gca_model
from google.cloud.automl_v1beta1.types import table_spec
from google.cloud.automl_v1beta1.types import table_spec as gca_table_spec


def client_cert_source_callback():
    return b"cert bytes", b"key bytes"


# If default endpoint is localhost, then default mtls endpoint will be the same.
# This method modifies the default endpoint so the client can produce a different
# mtls endpoint for endpoint testing purposes.
def modify_default_endpoint(client):
    return (
        "foo.googleapis.com"
        if ("localhost" in client.DEFAULT_ENDPOINT)
        else client.DEFAULT_ENDPOINT
    )


# If default endpoint template is localhost, then default mtls endpoint will be the same.
# This method modifies the default endpoint template so the client can produce a different
# mtls endpoint for endpoint testing purposes.
def modify_default_endpoint_template(client):
    return (
        "test.{UNIVERSE_DOMAIN}"
        if ("localhost" in client._DEFAULT_ENDPOINT_TEMPLATE)
        else client._DEFAULT_ENDPOINT_TEMPLATE
    )


def test__get_default_mtls_endpoint():
    api_endpoint = "example.googleapis.com"
    api_mtls_endpoint = "example.mtls.googleapis.com"
    sandbox_endpoint = "example.sandbox.googleapis.com"
    sandbox_mtls_endpoint = "example.mtls.sandbox.googleapis.com"
    non_googleapi = "api.example.com"

    assert AutoMlClient._get_default_mtls_endpoint(None) is None
    assert AutoMlClient._get_default_mtls_endpoint(api_endpoint) == api_mtls_endpoint
    assert (
        AutoMlClient._get_default_mtls_endpoint(api_mtls_endpoint) == api_mtls_endpoint
    )
    assert (
        AutoMlClient._get_default_mtls_endpoint(sandbox_endpoint)
        == sandbox_mtls_endpoint
    )
    assert (
        AutoMlClient._get_default_mtls_endpoint(sandbox_mtls_endpoint)
        == sandbox_mtls_endpoint
    )
    assert AutoMlClient._get_default_mtls_endpoint(non_googleapi) == non_googleapi


def test__read_environment_variables():
    assert AutoMlClient._read_environment_variables() == (False, "auto", None)

    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "true"}):
        assert AutoMlClient._read_environment_variables() == (True, "auto", None)

    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "false"}):
        assert AutoMlClient._read_environment_variables() == (False, "auto", None)

    with mock.patch.dict(
        os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "Unsupported"}
    ):
        with pytest.raises(ValueError) as excinfo:
            AutoMlClient._read_environment_variables()
    assert (
        str(excinfo.value)
        == "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`"
    )

    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "never"}):
        assert AutoMlClient._read_environment_variables() == (False, "never", None)

    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "always"}):
        assert AutoMlClient._read_environment_variables() == (False, "always", None)

    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "auto"}):
        assert AutoMlClient._read_environment_variables() == (False, "auto", None)

    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "Unsupported"}):
        with pytest.raises(MutualTLSChannelError) as excinfo:
            AutoMlClient._read_environment_variables()
    assert (
        str(excinfo.value)
        == "Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`"
    )

    with mock.patch.dict(os.environ, {"GOOGLE_CLOUD_UNIVERSE_DOMAIN": "foo.com"}):
        assert AutoMlClient._read_environment_variables() == (False, "auto", "foo.com")


def test__get_client_cert_source():
    mock_provided_cert_source = mock.Mock()
    mock_default_cert_source = mock.Mock()

    assert AutoMlClient._get_client_cert_source(None, False) is None
    assert (
        AutoMlClient._get_client_cert_source(mock_provided_cert_source, False) is None
    )
    assert (
        AutoMlClient._get_client_cert_source(mock_provided_cert_source, True)
        == mock_provided_cert_source
    )

    with mock.patch(
        "google.auth.transport.mtls.has_default_client_cert_source", return_value=True
    ):
        with mock.patch(
            "google.auth.transport.mtls.default_client_cert_source",
            return_value=mock_default_cert_source,
        ):
            assert (
                AutoMlClient._get_client_cert_source(None, True)
                is mock_default_cert_source
            )
            assert (
                AutoMlClient._get_client_cert_source(mock_provided_cert_source, "true")
                is mock_provided_cert_source
            )


@mock.patch.object(
    AutoMlClient,
    "_DEFAULT_ENDPOINT_TEMPLATE",
    modify_default_endpoint_template(AutoMlClient),
)
@mock.patch.object(
    AutoMlAsyncClient,
    "_DEFAULT_ENDPOINT_TEMPLATE",
    modify_default_endpoint_template(AutoMlAsyncClient),
)
def test__get_api_endpoint():
    api_override = "foo.com"
    mock_client_cert_source = mock.Mock()
    default_universe = AutoMlClient._DEFAULT_UNIVERSE
    default_endpoint = AutoMlClient._DEFAULT_ENDPOINT_TEMPLATE.format(
        UNIVERSE_DOMAIN=default_universe
    )
    mock_universe = "bar.com"
    mock_endpoint = AutoMlClient._DEFAULT_ENDPOINT_TEMPLATE.format(
        UNIVERSE_DOMAIN=mock_universe
    )

    assert (
        AutoMlClient._get_api_endpoint(
            api_override, mock_client_cert_source, default_universe, "always"
        )
        == api_override
    )
    assert (
        AutoMlClient._get_api_endpoint(
            None, mock_client_cert_source, default_universe, "auto"
        )
        == AutoMlClient.DEFAULT_MTLS_ENDPOINT
    )
    assert (
        AutoMlClient._get_api_endpoint(None, None, default_universe, "auto")
        == default_endpoint
    )
    assert (
        AutoMlClient._get_api_endpoint(None, None, default_universe, "always")
        == AutoMlClient.DEFAULT_MTLS_ENDPOINT
    )
    assert (
        AutoMlClient._get_api_endpoint(
            None, mock_client_cert_source, default_universe, "always"
        )
        == AutoMlClient.DEFAULT_MTLS_ENDPOINT
    )
    assert (
        AutoMlClient._get_api_endpoint(None, None, mock_universe, "never")
        == mock_endpoint
    )
    assert (
        AutoMlClient._get_api_endpoint(None, None, default_universe, "never")
        == default_endpoint
    )

    with pytest.raises(MutualTLSChannelError) as excinfo:
        AutoMlClient._get_api_endpoint(
            None, mock_client_cert_source, mock_universe, "auto"
        )
    assert (
        str(excinfo.value)
        == "mTLS is not supported in any universe other than googleapis.com."
    )


def test__get_universe_domain():
    client_universe_domain = "foo.com"
    universe_domain_env = "bar.com"

    assert (
        AutoMlClient._get_universe_domain(client_universe_domain, universe_domain_env)
        == client_universe_domain
    )
    assert (
        AutoMlClient._get_universe_domain(None, universe_domain_env)
        == universe_domain_env
    )
    assert (
        AutoMlClient._get_universe_domain(None, None) == AutoMlClient._DEFAULT_UNIVERSE
    )

    with pytest.raises(ValueError) as excinfo:
        AutoMlClient._get_universe_domain("", None)
    assert str(excinfo.value) == "Universe Domain cannot be an empty string."


@pytest.mark.parametrize(
    "client_class,transport_class,transport_name",
    [
        (AutoMlClient, transports.AutoMlGrpcTransport, "grpc"),
        (AutoMlClient, transports.AutoMlRestTransport, "rest"),
    ],
)
def test__validate_universe_domain(client_class, transport_class, transport_name):
    client = client_class(
        transport=transport_class(credentials=ga_credentials.AnonymousCredentials())
    )
    assert client._validate_universe_domain() == True

    # Test the case when universe is already validated.
    assert client._validate_universe_domain() == True

    if transport_name == "grpc":
        # Test the case where credentials are provided by the
        # `local_channel_credentials`. The default universes in both match.
        channel = grpc.secure_channel(
            "http://localhost/", grpc.local_channel_credentials()
        )
        client = client_class(transport=transport_class(channel=channel))
        assert client._validate_universe_domain() == True

        # Test the case where credentials do not exist: e.g. a transport is provided
        # with no credentials. Validation should still succeed because there is no
        # mismatch with non-existent credentials.
        channel = grpc.secure_channel(
            "http://localhost/", grpc.local_channel_credentials()
        )
        transport = transport_class(channel=channel)
        transport._credentials = None
        client = client_class(transport=transport)
        assert client._validate_universe_domain() == True

    # TODO: This is needed to cater for older versions of google-auth
    # Make this test unconditional once the minimum supported version of
    # google-auth becomes 2.23.0 or higher.
    google_auth_major, google_auth_minor = [
        int(part) for part in google.auth.__version__.split(".")[0:2]
    ]
    if google_auth_major > 2 or (google_auth_major == 2 and google_auth_minor >= 23):
        credentials = ga_credentials.AnonymousCredentials()
        credentials._universe_domain = "foo.com"
        # Test the case when there is a universe mismatch from the credentials.
        client = client_class(transport=transport_class(credentials=credentials))
        with pytest.raises(ValueError) as excinfo:
            client._validate_universe_domain()
        assert (
            str(excinfo.value)
            == "The configured universe domain (googleapis.com) does not match the universe domain found in the credentials (foo.com). If you haven't configured the universe domain explicitly, `googleapis.com` is the default."
        )

        # Test the case when there is a universe mismatch from the client.
        #
        # TODO: Make this test unconditional once the minimum supported version of
        # google-api-core becomes 2.15.0 or higher.
        api_core_major, api_core_minor = [
            int(part) for part in api_core_version.__version__.split(".")[0:2]
        ]
        if api_core_major > 2 or (api_core_major == 2 and api_core_minor >= 15):
            client = client_class(
                client_options={"universe_domain": "bar.com"},
                transport=transport_class(
                    credentials=ga_credentials.AnonymousCredentials(),
                ),
            )
            with pytest.raises(ValueError) as excinfo:
                client._validate_universe_domain()
            assert (
                str(excinfo.value)
                == "The configured universe domain (bar.com) does not match the universe domain found in the credentials (googleapis.com). If you haven't configured the universe domain explicitly, `googleapis.com` is the default."
            )

    # Test that ValueError is raised if universe_domain is provided via client options and credentials is None
    with pytest.raises(ValueError):
        client._compare_universes("foo.bar", None)


@pytest.mark.parametrize(
    "client_class,transport_name",
    [
        (AutoMlClient, "grpc"),
        (AutoMlAsyncClient, "grpc_asyncio"),
        (AutoMlClient, "rest"),
    ],
)
def test_auto_ml_client_from_service_account_info(client_class, transport_name):
    creds = ga_credentials.AnonymousCredentials()
    with mock.patch.object(
        service_account.Credentials, "from_service_account_info"
    ) as factory:
        factory.return_value = creds
        info = {"valid": True}
        client = client_class.from_service_account_info(info, transport=transport_name)
        assert client.transport._credentials == creds
        assert isinstance(client, client_class)

        assert client.transport._host == (
            "automl.googleapis.com:443"
            if transport_name in ["grpc", "grpc_asyncio"]
            else "https://automl.googleapis.com"
        )


@pytest.mark.parametrize(
    "transport_class,transport_name",
    [
        (transports.AutoMlGrpcTransport, "grpc"),
        (transports.AutoMlGrpcAsyncIOTransport, "grpc_asyncio"),
        (transports.AutoMlRestTransport, "rest"),
    ],
)
def test_auto_ml_client_service_account_always_use_jwt(transport_class, transport_name):
    with mock.patch.object(
        service_account.Credentials, "with_always_use_jwt_access", create=True
    ) as use_jwt:
        creds = service_account.Credentials(None, None, None)
        transport = transport_class(credentials=creds, always_use_jwt_access=True)
        use_jwt.assert_called_once_with(True)

    with mock.patch.object(
        service_account.Credentials, "with_always_use_jwt_access", create=True
    ) as use_jwt:
        creds = service_account.Credentials(None, None, None)
        transport = transport_class(credentials=creds, always_use_jwt_access=False)
        use_jwt.assert_not_called()


@pytest.mark.parametrize(
    "client_class,transport_name",
    [
        (AutoMlClient, "grpc"),
        (AutoMlAsyncClient, "grpc_asyncio"),
        (AutoMlClient, "rest"),
    ],
)
def test_auto_ml_client_from_service_account_file(client_class, transport_name):
    creds = ga_credentials.AnonymousCredentials()
    with mock.patch.object(
        service_account.Credentials, "from_service_account_file"
    ) as factory:
        factory.return_value = creds
        client = client_class.from_service_account_file(
            "dummy/file/path.json", transport=transport_name
        )
        assert client.transport._credentials == creds
        assert isinstance(client, client_class)

        client = client_class.from_service_account_json(
            "dummy/file/path.json", transport=transport_name
        )
        assert client.transport._credentials == creds
        assert isinstance(client, client_class)

        assert client.transport._host == (
            "automl.googleapis.com:443"
            if transport_name in ["grpc", "grpc_asyncio"]
            else "https://automl.googleapis.com"
        )


def test_auto_ml_client_get_transport_class():
    transport = AutoMlClient.get_transport_class()
    available_transports = [
        transports.AutoMlGrpcTransport,
        transports.AutoMlRestTransport,
    ]
    assert transport in available_transports

    transport = AutoMlClient.get_transport_class("grpc")
    assert transport == transports.AutoMlGrpcTransport


@pytest.mark.parametrize(
    "client_class,transport_class,transport_name",
    [
        (AutoMlClient, transports.AutoMlGrpcTransport, "grpc"),
        (AutoMlAsyncClient, transports.AutoMlGrpcAsyncIOTransport, "grpc_asyncio"),
        (AutoMlClient, transports.AutoMlRestTransport, "rest"),
    ],
)
@mock.patch.object(
    AutoMlClient,
    "_DEFAULT_ENDPOINT_TEMPLATE",
    modify_default_endpoint_template(AutoMlClient),
)
@mock.patch.object(
    AutoMlAsyncClient,
    "_DEFAULT_ENDPOINT_TEMPLATE",
    modify_default_endpoint_template(AutoMlAsyncClient),
)
def test_auto_ml_client_client_options(client_class, transport_class, transport_name):
    # Check that if channel is provided we won't create a new one.
    with mock.patch.object(AutoMlClient, "get_transport_class") as gtc:
        transport = transport_class(credentials=ga_credentials.AnonymousCredentials())
        client = client_class(transport=transport)
        gtc.assert_not_called()

    # Check that if channel is provided via str we will create a new one.
    with mock.patch.object(AutoMlClient, "get_transport_class") as gtc:
        client = client_class(transport=transport_name)
        gtc.assert_called()

    # Check the case api_endpoint is provided.
    options = client_options.ClientOptions(api_endpoint="squid.clam.whelk")
    with mock.patch.object(transport_class, "__init__") as patched:
        patched.return_value = None
        client = client_class(transport=transport_name, client_options=options)
        patched.assert_called_once_with(
            credentials=None,
            credentials_file=None,
            host="squid.clam.whelk",
            scopes=None,
            client_cert_source_for_mtls=None,
            quota_project_id=None,
            client_info=transports.base.DEFAULT_CLIENT_INFO,
            always_use_jwt_access=True,
            api_audience=None,
        )

    # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT is
    # "never".
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "never"}):
        with mock.patch.object(transport_class, "__init__") as patched:
            patched.return_value = None
            client = client_class(transport=transport_name)
            patched.assert_called_once_with(
                credentials=None,
                credentials_file=None,
                host=client._DEFAULT_ENDPOINT_TEMPLATE.format(
                    UNIVERSE_DOMAIN=client._DEFAULT_UNIVERSE
                ),
                scopes=None,
                client_cert_source_for_mtls=None,
                quota_project_id=None,
                client_info=transports.base.DEFAULT_CLIENT_INFO,
                always_use_jwt_access=True,
                api_audience=None,
            )

    # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT is
    # "always".
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "always"}):
        with mock.patch.object(transport_class, "__init__") as patched:
            patched.return_value = None
            client = client_class(transport=transport_name)
            patched.assert_called_once_with(
                credentials=None,
                credentials_file=None,
                host=client.DEFAULT_MTLS_ENDPOINT,
                scopes=None,
                client_cert_source_for_mtls=None,
                quota_project_id=None,
                client_info=transports.base.DEFAULT_CLIENT_INFO,
                always_use_jwt_access=True,
                api_audience=None,
            )

    # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT has
    # unsupported value.
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "Unsupported"}):
        with pytest.raises(MutualTLSChannelError) as excinfo:
            client = client_class(transport=transport_name)
    assert (
        str(excinfo.value)
        == "Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`"
    )

    # Check the case GOOGLE_API_USE_CLIENT_CERTIFICATE has unsupported value.
    with mock.patch.dict(
        os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "Unsupported"}
    ):
        with pytest.raises(ValueError) as excinfo:
            client = client_class(transport=transport_name)
    assert (
        str(excinfo.value)
        == "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`"
    )

    # Check the case quota_project_id is provided
    options = client_options.ClientOptions(quota_project_id="octopus")
    with mock.patch.object(transport_class, "__init__") as patched:
        patched.return_value = None
        client = client_class(client_options=options, transport=transport_name)
        patched.assert_called_once_with(
            credentials=None,
            credentials_file=None,
            host=client._DEFAULT_ENDPOINT_TEMPLATE.format(
                UNIVERSE_DOMAIN=client._DEFAULT_UNIVERSE
            ),
            scopes=None,
            client_cert_source_for_mtls=None,
            quota_project_id="octopus",
            client_info=transports.base.DEFAULT_CLIENT_INFO,
            always_use_jwt_access=True,
            api_audience=None,
        )
    # Check the case api_endpoint is provided
    options = client_options.ClientOptions(
        api_audience="https://language.googleapis.com"
    )
    with mock.patch.object(transport_class, "__init__") as patched:
        patched.return_value = None
        client = client_class(client_options=options, transport=transport_name)
        patched.assert_called_once_with(
            credentials=None,
            credentials_file=None,
            host=client._DEFAULT_ENDPOINT_TEMPLATE.format(
                UNIVERSE_DOMAIN=client._DEFAULT_UNIVERSE
            ),
            scopes=None,
            client_cert_source_for_mtls=None,
            quota_project_id=None,
            client_info=transports.base.DEFAULT_CLIENT_INFO,
            always_use_jwt_access=True,
            api_audience="https://language.googleapis.com",
        )


@pytest.mark.parametrize(
    "client_class,transport_class,transport_name,use_client_cert_env",
    [
        (AutoMlClient, transports.AutoMlGrpcTransport, "grpc", "true"),
        (
            AutoMlAsyncClient,
            transports.AutoMlGrpcAsyncIOTransport,
            "grpc_asyncio",
            "true",
        ),
        (AutoMlClient, transports.AutoMlGrpcTransport, "grpc", "false"),
        (
            AutoMlAsyncClient,
            transports.AutoMlGrpcAsyncIOTransport,
            "grpc_asyncio",
            "false",
        ),
        (AutoMlClient, transports.AutoMlRestTransport, "rest", "true"),
        (AutoMlClient, transports.AutoMlRestTransport, "rest", "false"),
    ],
)
@mock.patch.object(
    AutoMlClient,
    "_DEFAULT_ENDPOINT_TEMPLATE",
    modify_default_endpoint_template(AutoMlClient),
)
@mock.patch.object(
    AutoMlAsyncClient,
    "_DEFAULT_ENDPOINT_TEMPLATE",
    modify_default_endpoint_template(AutoMlAsyncClient),
)
@mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "auto"})
def test_auto_ml_client_mtls_env_auto(
    client_class, transport_class, transport_name, use_client_cert_env
):
    # This tests the endpoint autoswitch behavior. Endpoint is autoswitched to the default
    # mtls endpoint, if GOOGLE_API_USE_CLIENT_CERTIFICATE is "true" and client cert exists.

    # Check the case client_cert_source is provided. Whether client cert is used depends on
    # GOOGLE_API_USE_CLIENT_CERTIFICATE value.
    with mock.patch.dict(
        os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env}
    ):
        options = client_options.ClientOptions(
            client_cert_source=client_cert_source_callback
        )
        with mock.patch.object(transport_class, "__init__") as patched:
            patched.return_value = None
            client = client_class(client_options=options, transport=transport_name)

            if use_client_cert_env == "false":
                expected_client_cert_source = None
                expected_host = client._DEFAULT_ENDPOINT_TEMPLATE.format(
                    UNIVERSE_DOMAIN=client._DEFAULT_UNIVERSE
                )
            else:
                expected_client_cert_source = client_cert_source_callback
                expected_host = client.DEFAULT_MTLS_ENDPOINT

            patched.assert_called_once_with(
                credentials=None,
                credentials_file=None,
                host=expected_host,
                scopes=None,
                client_cert_source_for_mtls=expected_client_cert_source,
                quota_project_id=None,
                client_info=transports.base.DEFAULT_CLIENT_INFO,
                always_use_jwt_access=True,
                api_audience=None,
            )

    # Check the case ADC client cert is provided. Whether client cert is used depends on
    # GOOGLE_API_USE_CLIENT_CERTIFICATE value.
    with mock.patch.dict(
        os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env}
    ):
        with mock.patch.object(transport_class, "__init__") as patched:
            with mock.patch(
                "google.auth.transport.mtls.has_default_client_cert_source",
                return_value=True,
            ):
                with mock.patch(
                    "google.auth.transport.mtls.default_client_cert_source",
                    return_value=client_cert_source_callback,
                ):
                    if use_client_cert_env == "false":
                        expected_host = client._DEFAULT_ENDPOINT_TEMPLATE.format(
                            UNIVERSE_DOMAIN=client._DEFAULT_UNIVERSE
                        )
                        expected_client_cert_source = None
                    else:
                        expected_host = client.DEFAULT_MTLS_ENDPOINT
                        expected_client_cert_source = client_cert_source_callback

                    patched.return_value = None
                    client = client_class(transport=transport_name)
                    patched.assert_called_once_with(
                        credentials=None,
                        credentials_file=None,
                        host=expected_host,
                        scopes=None,
                        client_cert_source_for_mtls=expected_client_cert_source,
                        quota_project_id=None,
                        client_info=transports.base.DEFAULT_CLIENT_INFO,
                        always_use_jwt_access=True,
                        api_audience=None,
                    )

    # Check the case client_cert_source and ADC client cert are not provided.
    with mock.patch.dict(
        os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env}
    ):
        with mock.patch.object(transport_class, "__init__") as patched:
            with mock.patch(
                "google.auth.transport.mtls.has_default_client_cert_source",
                return_value=False,
            ):
                patched.return_value = None
                client = client_class(transport=transport_name)
                patched.assert_called_once_with(
                    credentials=None,
                    credentials_file=None,
                    host=client._DEFAULT_ENDPOINT_TEMPLATE.format(
                        UNIVERSE_DOMAIN=client._DEFAULT_UNIVERSE
                    ),
                    scopes=None,
                    client_cert_source_for_mtls=None,
                    quota_project_id=None,
                    client_info=transports.base.DEFAULT_CLIENT_INFO,
                    always_use_jwt_access=True,
                    api_audience=None,
                )


@pytest.mark.parametrize("client_class", [AutoMlClient, AutoMlAsyncClient])
@mock.patch.object(
    AutoMlClient, "DEFAULT_ENDPOINT", modify_default_endpoint(AutoMlClient)
)
@mock.patch.object(
    AutoMlAsyncClient, "DEFAULT_ENDPOINT", modify_default_endpoint(AutoMlAsyncClient)
)
def test_auto_ml_client_get_mtls_endpoint_and_cert_source(client_class):
    mock_client_cert_source = mock.Mock()

    # Test the case GOOGLE_API_USE_CLIENT_CERTIFICATE is "true".
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "true"}):
        mock_api_endpoint = "foo"
        options = client_options.ClientOptions(
            client_cert_source=mock_client_cert_source, api_endpoint=mock_api_endpoint
        )
        api_endpoint, cert_source = client_class.get_mtls_endpoint_and_cert_source(
            options
        )
        assert api_endpoint == mock_api_endpoint
        assert cert_source == mock_client_cert_source

    # Test the case GOOGLE_API_USE_CLIENT_CERTIFICATE is "false".
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "false"}):
        mock_client_cert_source = mock.Mock()
        mock_api_endpoint = "foo"
        options = client_options.ClientOptions(
            client_cert_source=mock_client_cert_source, api_endpoint=mock_api_endpoint
        )
        api_endpoint, cert_source = client_class.get_mtls_endpoint_and_cert_source(
            options
        )
        assert api_endpoint == mock_api_endpoint
        assert cert_source is None

    # Test the case GOOGLE_API_USE_MTLS_ENDPOINT is "never".
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "never"}):
        api_endpoint, cert_source = client_class.get_mtls_endpoint_and_cert_source()
        assert api_endpoint == client_class.DEFAULT_ENDPOINT
        assert cert_source is None

    # Test the case GOOGLE_API_USE_MTLS_ENDPOINT is "always".
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "always"}):
        api_endpoint, cert_source = client_class.get_mtls_endpoint_and_cert_source()
        assert api_endpoint == client_class.DEFAULT_MTLS_ENDPOINT
        assert cert_source is None

    # Test the case GOOGLE_API_USE_MTLS_ENDPOINT is "auto" and default cert doesn't exist.
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "true"}):
        with mock.patch(
            "google.auth.transport.mtls.has_default_client_cert_source",
            return_value=False,
        ):
            api_endpoint, cert_source = client_class.get_mtls_endpoint_and_cert_source()
            assert api_endpoint == client_class.DEFAULT_ENDPOINT
            assert cert_source is None

    # Test the case GOOGLE_API_USE_MTLS_ENDPOINT is "auto" and default cert exists.
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "true"}):
        with mock.patch(
            "google.auth.transport.mtls.has_default_client_cert_source",
            return_value=True,
        ):
            with mock.patch(
                "google.auth.transport.mtls.default_client_cert_source",
                return_value=mock_client_cert_source,
            ):
                (
                    api_endpoint,
                    cert_source,
                ) = client_class.get_mtls_endpoint_and_cert_source()
                assert api_endpoint == client_class.DEFAULT_MTLS_ENDPOINT
                assert cert_source == mock_client_cert_source

    # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT has
    # unsupported value.
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "Unsupported"}):
        with pytest.raises(MutualTLSChannelError) as excinfo:
            client_class.get_mtls_endpoint_and_cert_source()

        assert (
            str(excinfo.value)
            == "Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`"
        )

    # Check the case GOOGLE_API_USE_CLIENT_CERTIFICATE has unsupported value.
    with mock.patch.dict(
        os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "Unsupported"}
    ):
        with pytest.raises(ValueError) as excinfo:
            client_class.get_mtls_endpoint_and_cert_source()

        assert (
            str(excinfo.value)
            == "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`"
        )


@pytest.mark.parametrize("client_class", [AutoMlClient, AutoMlAsyncClient])
@mock.patch.object(
    AutoMlClient,
    "_DEFAULT_ENDPOINT_TEMPLATE",
    modify_default_endpoint_template(AutoMlClient),
)
@mock.patch.object(
    AutoMlAsyncClient,
    "_DEFAULT_ENDPOINT_TEMPLATE",
    modify_default_endpoint_template(AutoMlAsyncClient),
)
def test_auto_ml_client_client_api_endpoint(client_class):
    mock_client_cert_source = client_cert_source_callback
    api_override = "foo.com"
    default_universe = AutoMlClient._DEFAULT_UNIVERSE
    default_endpoint = AutoMlClient._DEFAULT_ENDPOINT_TEMPLATE.format(
        UNIVERSE_DOMAIN=default_universe
    )
    mock_universe = "bar.com"
    mock_endpoint = AutoMlClient._DEFAULT_ENDPOINT_TEMPLATE.format(
        UNIVERSE_DOMAIN=mock_universe
    )

    # If ClientOptions.api_endpoint is set and GOOGLE_API_USE_CLIENT_CERTIFICATE="true",
    # use ClientOptions.api_endpoint as the api endpoint regardless.
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "true"}):
        with mock.patch(
            "google.auth.transport.requests.AuthorizedSession.configure_mtls_channel"
        ):
            options = client_options.ClientOptions(
                client_cert_source=mock_client_cert_source, api_endpoint=api_override
            )
            client = client_class(
                client_options=options,
                credentials=ga_credentials.AnonymousCredentials(),
            )
            assert client.api_endpoint == api_override

    # If ClientOptions.api_endpoint is not set and GOOGLE_API_USE_MTLS_ENDPOINT="never",
    # use the _DEFAULT_ENDPOINT_TEMPLATE populated with GDU as the api endpoint.
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "never"}):
        client = client_class(credentials=ga_credentials.AnonymousCredentials())
        assert client.api_endpoint == default_endpoint

    # If ClientOptions.api_endpoint is not set and GOOGLE_API_USE_MTLS_ENDPOINT="always",
    # use the DEFAULT_MTLS_ENDPOINT as the api endpoint.
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "always"}):
        client = client_class(credentials=ga_credentials.AnonymousCredentials())
        assert client.api_endpoint == client_class.DEFAULT_MTLS_ENDPOINT

    # If ClientOptions.api_endpoint is not set, GOOGLE_API_USE_MTLS_ENDPOINT="auto" (default),
    # GOOGLE_API_USE_CLIENT_CERTIFICATE="false" (default), default cert source doesn't exist,
    # and ClientOptions.universe_domain="bar.com",
    # use the _DEFAULT_ENDPOINT_TEMPLATE populated with universe domain as the api endpoint.
    options = client_options.ClientOptions()
    universe_exists = hasattr(options, "universe_domain")
    if universe_exists:
        options = client_options.ClientOptions(universe_domain=mock_universe)
        client = client_class(
            client_options=options, credentials=ga_credentials.AnonymousCredentials()
        )
    else:
        client = client_class(
            client_options=options, credentials=ga_credentials.AnonymousCredentials()
        )
    assert client.api_endpoint == (
        mock_endpoint if universe_exists else default_endpoint
    )
    assert client.universe_domain == (
        mock_universe if universe_exists else default_universe
    )

    # If ClientOptions does not have a universe domain attribute and GOOGLE_API_USE_MTLS_ENDPOINT="never",
    # use the _DEFAULT_ENDPOINT_TEMPLATE populated with GDU as the api endpoint.
    options = client_options.ClientOptions()
    if hasattr(options, "universe_domain"):
        delattr(options, "universe_domain")
    with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "never"}):
        client = client_class(
            client_options=options, credentials=ga_credentials.AnonymousCredentials()
        )
        assert client.api_endpoint == default_endpoint


@pytest.mark.parametrize(
    "client_class,transport_class,transport_name",
    [
        (AutoMlClient, transports.AutoMlGrpcTransport, "grpc"),
        (AutoMlAsyncClient, transports.AutoMlGrpcAsyncIOTransport, "grpc_asyncio"),
        (AutoMlClient, transports.AutoMlRestTransport, "rest"),
    ],
)
def test_auto_ml_client_client_options_scopes(
    client_class, transport_class, transport_name
):
    # Check the case scopes are provided.
    options = client_options.ClientOptions(
        scopes=["1", "2"],
    )
    with mock.patch.object(transport_class, "__init__") as patched:
        patched.return_value = None
        client = client_class(client_options=options, transport=transport_name)
        patched.assert_called_once_with(
            credentials=None,
            credentials_file=None,
            host=client._DEFAULT_ENDPOINT_TEMPLATE.format(
                UNIVERSE_DOMAIN=client._DEFAULT_UNIVERSE
            ),
            scopes=["1", "2"],
            client_cert_source_for_mtls=None,
            quota_project_id=None,
            client_info=transports.base.DEFAULT_CLIENT_INFO,
            always_use_jwt_access=True,
            api_audience=None,
        )


@pytest.mark.parametrize(
    "client_class,transport_class,transport_name,grpc_helpers",
    [
        (AutoMlClient, transports.AutoMlGrpcTransport, "grpc", grpc_helpers),
        (
            AutoMlAsyncClient,
            transports.AutoMlGrpcAsyncIOTransport,
            "grpc_asyncio",
            grpc_helpers_async,
        ),
        (AutoMlClient, transports.AutoMlRestTransport, "rest", None),
    ],
)
def test_auto_ml_client_client_options_credentials_file(
    client_class, transport_class, transport_name, grpc_helpers
):
    # Check the case credentials file is provided.
    options = client_options.ClientOptions(credentials_file="credentials.json")

    with mock.patch.object(transport_class, "__init__") as patched:
        patched.return_value = None
        client = client_class(client_options=options, transport=transport_name)
        patched.assert_called_once_with(
            credentials=None,
            credentials_file="credentials.json",
            host=client._DEFAULT_ENDPOINT_TEMPLATE.format(
                UNIVERSE_DOMAIN=client._DEFAULT_UNIVERSE
            ),
            scopes=None,
            client_cert_source_for_mtls=None,
            quota_project_id=None,
            client_info=transports.base.DEFAULT_CLIENT_INFO,
            always_use_jwt_access=True,
            api_audience=None,
        )


def test_auto_ml_client_client_options_from_dict():
    with mock.patch(
        "google.cloud.automl_v1beta1.services.auto_ml.transports.AutoMlGrpcTransport.__init__"
    ) as grpc_transport:
        grpc_transport.return_value = None
        client = AutoMlClient(client_options={"api_endpoint": "squid.clam.whelk"})
        grpc_transport.assert_called_once_with(
            credentials=None,
            credentials_file=None,
            host="squid.clam.whelk",
            scopes=None,
            client_cert_source_for_mtls=None,
            quota_project_id=None,
            client_info=transports.base.DEFAULT_CLIENT_INFO,
            always_use_jwt_access=True,
            api_audience=None,
        )


@pytest.mark.parametrize(
    "client_class,transport_class,transport_name,grpc_helpers",
    [
        (AutoMlClient, transports.AutoMlGrpcTransport, "grpc", grpc_helpers),
        (
            AutoMlAsyncClient,
            transports.AutoMlGrpcAsyncIOTransport,
            "grpc_asyncio",
            grpc_helpers_async,
        ),
    ],
)
def test_auto_ml_client_create_channel_credentials_file(
    client_class, transport_class, transport_name, grpc_helpers
):
    # Check the case credentials file is provided.
    options = client_options.ClientOptions(credentials_file="credentials.json")

    with mock.patch.object(transport_class, "__init__") as patched:
        patched.return_value = None
        client = client_class(client_options=options, transport=transport_name)
        patched.assert_called_once_with(
            credentials=None,
            credentials_file="credentials.json",
            host=client._DEFAULT_ENDPOINT_TEMPLATE.format(
                UNIVERSE_DOMAIN=client._DEFAULT_UNIVERSE
            ),
            scopes=None,
            client_cert_source_for_mtls=None,
            quota_project_id=None,
            client_info=transports.base.DEFAULT_CLIENT_INFO,
            always_use_jwt_access=True,
            api_audience=None,
        )

    # test that the credentials from file are saved and used as the credentials.
    with mock.patch.object(
        google.auth, "load_credentials_from_file", autospec=True
    ) as load_creds, mock.patch.object(
        google.auth, "default", autospec=True
    ) as adc, mock.patch.object(
        grpc_helpers, "create_channel"
    ) as create_channel:
        creds = ga_credentials.AnonymousCredentials()
        file_creds = ga_credentials.AnonymousCredentials()
        load_creds.return_value = (file_creds, None)
        adc.return_value = (creds, None)
        client = client_class(client_options=options, transport=transport_name)
        create_channel.assert_called_with(
            "automl.googleapis.com:443",
            credentials=file_creds,
            credentials_file=None,
            quota_project_id=None,
            default_scopes=("https://www.googleapis.com/auth/cloud-platform",),
            scopes=None,
            default_host="automl.googleapis.com",
            ssl_credentials=None,
            options=[
                ("grpc.max_send_message_length", -1),
                ("grpc.max_receive_message_length", -1),
            ],
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.CreateDatasetRequest,
        dict,
    ],
)
def test_create_dataset(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = gca_dataset.Dataset(
            name="name_value",
            display_name="display_name_value",
            description="description_value",
            example_count=1396,
            etag="etag_value",
        )
        response = client.create_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.CreateDatasetRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, gca_dataset.Dataset)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.description == "description_value"
    assert response.example_count == 1396
    assert response.etag == "etag_value"


def test_create_dataset_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_dataset), "__call__") as call:
        client.create_dataset()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.CreateDatasetRequest()


@pytest.mark.asyncio
async def test_create_dataset_async(
    transport: str = "grpc_asyncio", request_type=service.CreateDatasetRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            gca_dataset.Dataset(
                name="name_value",
                display_name="display_name_value",
                description="description_value",
                example_count=1396,
                etag="etag_value",
            )
        )
        response = await client.create_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.CreateDatasetRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, gca_dataset.Dataset)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.description == "description_value"
    assert response.example_count == 1396
    assert response.etag == "etag_value"


@pytest.mark.asyncio
async def test_create_dataset_async_from_dict():
    await test_create_dataset_async(request_type=dict)


def test_create_dataset_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.CreateDatasetRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_dataset), "__call__") as call:
        call.return_value = gca_dataset.Dataset()
        client.create_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_create_dataset_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.CreateDatasetRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_dataset), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(gca_dataset.Dataset())
        await client.create_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


def test_create_dataset_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = gca_dataset.Dataset()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.create_dataset(
            parent="parent_value",
            dataset=gca_dataset.Dataset(
                translation_dataset_metadata=translation.TranslationDatasetMetadata(
                    source_language_code="source_language_code_value"
                )
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val
        arg = args[0].dataset
        mock_val = gca_dataset.Dataset(
            translation_dataset_metadata=translation.TranslationDatasetMetadata(
                source_language_code="source_language_code_value"
            )
        )
        assert arg == mock_val


def test_create_dataset_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.create_dataset(
            service.CreateDatasetRequest(),
            parent="parent_value",
            dataset=gca_dataset.Dataset(
                translation_dataset_metadata=translation.TranslationDatasetMetadata(
                    source_language_code="source_language_code_value"
                )
            ),
        )


@pytest.mark.asyncio
async def test_create_dataset_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = gca_dataset.Dataset()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(gca_dataset.Dataset())
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.create_dataset(
            parent="parent_value",
            dataset=gca_dataset.Dataset(
                translation_dataset_metadata=translation.TranslationDatasetMetadata(
                    source_language_code="source_language_code_value"
                )
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val
        arg = args[0].dataset
        mock_val = gca_dataset.Dataset(
            translation_dataset_metadata=translation.TranslationDatasetMetadata(
                source_language_code="source_language_code_value"
            )
        )
        assert arg == mock_val


@pytest.mark.asyncio
async def test_create_dataset_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.create_dataset(
            service.CreateDatasetRequest(),
            parent="parent_value",
            dataset=gca_dataset.Dataset(
                translation_dataset_metadata=translation.TranslationDatasetMetadata(
                    source_language_code="source_language_code_value"
                )
            ),
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.GetDatasetRequest,
        dict,
    ],
)
def test_get_dataset(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = dataset.Dataset(
            name="name_value",
            display_name="display_name_value",
            description="description_value",
            example_count=1396,
            etag="etag_value",
        )
        response = client.get_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetDatasetRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, dataset.Dataset)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.description == "description_value"
    assert response.example_count == 1396
    assert response.etag == "etag_value"


def test_get_dataset_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_dataset), "__call__") as call:
        client.get_dataset()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetDatasetRequest()


@pytest.mark.asyncio
async def test_get_dataset_async(
    transport: str = "grpc_asyncio", request_type=service.GetDatasetRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            dataset.Dataset(
                name="name_value",
                display_name="display_name_value",
                description="description_value",
                example_count=1396,
                etag="etag_value",
            )
        )
        response = await client.get_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetDatasetRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, dataset.Dataset)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.description == "description_value"
    assert response.example_count == 1396
    assert response.etag == "etag_value"


@pytest.mark.asyncio
async def test_get_dataset_async_from_dict():
    await test_get_dataset_async(request_type=dict)


def test_get_dataset_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.GetDatasetRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_dataset), "__call__") as call:
        call.return_value = dataset.Dataset()
        client.get_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_get_dataset_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.GetDatasetRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_dataset), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(dataset.Dataset())
        await client.get_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_get_dataset_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = dataset.Dataset()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.get_dataset(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


def test_get_dataset_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.get_dataset(
            service.GetDatasetRequest(),
            name="name_value",
        )


@pytest.mark.asyncio
async def test_get_dataset_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = dataset.Dataset()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(dataset.Dataset())
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.get_dataset(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_get_dataset_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.get_dataset(
            service.GetDatasetRequest(),
            name="name_value",
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ListDatasetsRequest,
        dict,
    ],
)
def test_list_datasets(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_datasets), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListDatasetsResponse(
            next_page_token="next_page_token_value",
        )
        response = client.list_datasets(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListDatasetsRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListDatasetsPager)
    assert response.next_page_token == "next_page_token_value"


def test_list_datasets_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_datasets), "__call__") as call:
        client.list_datasets()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListDatasetsRequest()


@pytest.mark.asyncio
async def test_list_datasets_async(
    transport: str = "grpc_asyncio", request_type=service.ListDatasetsRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_datasets), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListDatasetsResponse(
                next_page_token="next_page_token_value",
            )
        )
        response = await client.list_datasets(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListDatasetsRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListDatasetsAsyncPager)
    assert response.next_page_token == "next_page_token_value"


@pytest.mark.asyncio
async def test_list_datasets_async_from_dict():
    await test_list_datasets_async(request_type=dict)


def test_list_datasets_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ListDatasetsRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_datasets), "__call__") as call:
        call.return_value = service.ListDatasetsResponse()
        client.list_datasets(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_list_datasets_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ListDatasetsRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_datasets), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListDatasetsResponse()
        )
        await client.list_datasets(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


def test_list_datasets_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_datasets), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListDatasetsResponse()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.list_datasets(
            parent="parent_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val


def test_list_datasets_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.list_datasets(
            service.ListDatasetsRequest(),
            parent="parent_value",
        )


@pytest.mark.asyncio
async def test_list_datasets_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_datasets), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListDatasetsResponse()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListDatasetsResponse()
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.list_datasets(
            parent="parent_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_list_datasets_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.list_datasets(
            service.ListDatasetsRequest(),
            parent="parent_value",
        )


def test_list_datasets_pager(transport_name: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport_name,
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_datasets), "__call__") as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                    dataset.Dataset(),
                    dataset.Dataset(),
                ],
                next_page_token="abc",
            ),
            service.ListDatasetsResponse(
                datasets=[],
                next_page_token="def",
            ),
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                ],
                next_page_token="ghi",
            ),
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                    dataset.Dataset(),
                ],
            ),
            RuntimeError,
        )

        metadata = ()
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", ""),)),
        )
        pager = client.list_datasets(request={})

        assert pager._metadata == metadata

        results = list(pager)
        assert len(results) == 6
        assert all(isinstance(i, dataset.Dataset) for i in results)


def test_list_datasets_pages(transport_name: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport_name,
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_datasets), "__call__") as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                    dataset.Dataset(),
                    dataset.Dataset(),
                ],
                next_page_token="abc",
            ),
            service.ListDatasetsResponse(
                datasets=[],
                next_page_token="def",
            ),
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                ],
                next_page_token="ghi",
            ),
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                    dataset.Dataset(),
                ],
            ),
            RuntimeError,
        )
        pages = list(client.list_datasets(request={}).pages)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.asyncio
async def test_list_datasets_async_pager():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_datasets), "__call__", new_callable=mock.AsyncMock
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                    dataset.Dataset(),
                    dataset.Dataset(),
                ],
                next_page_token="abc",
            ),
            service.ListDatasetsResponse(
                datasets=[],
                next_page_token="def",
            ),
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                ],
                next_page_token="ghi",
            ),
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                    dataset.Dataset(),
                ],
            ),
            RuntimeError,
        )
        async_pager = await client.list_datasets(
            request={},
        )
        assert async_pager.next_page_token == "abc"
        responses = []
        async for response in async_pager:  # pragma: no branch
            responses.append(response)

        assert len(responses) == 6
        assert all(isinstance(i, dataset.Dataset) for i in responses)


@pytest.mark.asyncio
async def test_list_datasets_async_pages():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_datasets), "__call__", new_callable=mock.AsyncMock
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                    dataset.Dataset(),
                    dataset.Dataset(),
                ],
                next_page_token="abc",
            ),
            service.ListDatasetsResponse(
                datasets=[],
                next_page_token="def",
            ),
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                ],
                next_page_token="ghi",
            ),
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                    dataset.Dataset(),
                ],
            ),
            RuntimeError,
        )
        pages = []
        # Workaround issue in python 3.9 related to code coverage by adding `# pragma: no branch`
        # See https://github.com/googleapis/gapic-generator-python/pull/1174#issuecomment-1025132372
        async for page_ in (  # pragma: no branch
            await client.list_datasets(request={})
        ).pages:
            pages.append(page_)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.parametrize(
    "request_type",
    [
        service.UpdateDatasetRequest,
        dict,
    ],
)
def test_update_dataset(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.update_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = gca_dataset.Dataset(
            name="name_value",
            display_name="display_name_value",
            description="description_value",
            example_count=1396,
            etag="etag_value",
        )
        response = client.update_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.UpdateDatasetRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, gca_dataset.Dataset)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.description == "description_value"
    assert response.example_count == 1396
    assert response.etag == "etag_value"


def test_update_dataset_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.update_dataset), "__call__") as call:
        client.update_dataset()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.UpdateDatasetRequest()


@pytest.mark.asyncio
async def test_update_dataset_async(
    transport: str = "grpc_asyncio", request_type=service.UpdateDatasetRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.update_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            gca_dataset.Dataset(
                name="name_value",
                display_name="display_name_value",
                description="description_value",
                example_count=1396,
                etag="etag_value",
            )
        )
        response = await client.update_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.UpdateDatasetRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, gca_dataset.Dataset)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.description == "description_value"
    assert response.example_count == 1396
    assert response.etag == "etag_value"


@pytest.mark.asyncio
async def test_update_dataset_async_from_dict():
    await test_update_dataset_async(request_type=dict)


def test_update_dataset_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.UpdateDatasetRequest()

    request.dataset.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.update_dataset), "__call__") as call:
        call.return_value = gca_dataset.Dataset()
        client.update_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "dataset.name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_update_dataset_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.UpdateDatasetRequest()

    request.dataset.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.update_dataset), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(gca_dataset.Dataset())
        await client.update_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "dataset.name=name_value",
    ) in kw["metadata"]


def test_update_dataset_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.update_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = gca_dataset.Dataset()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.update_dataset(
            dataset=gca_dataset.Dataset(
                translation_dataset_metadata=translation.TranslationDatasetMetadata(
                    source_language_code="source_language_code_value"
                )
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].dataset
        mock_val = gca_dataset.Dataset(
            translation_dataset_metadata=translation.TranslationDatasetMetadata(
                source_language_code="source_language_code_value"
            )
        )
        assert arg == mock_val


def test_update_dataset_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.update_dataset(
            service.UpdateDatasetRequest(),
            dataset=gca_dataset.Dataset(
                translation_dataset_metadata=translation.TranslationDatasetMetadata(
                    source_language_code="source_language_code_value"
                )
            ),
        )


@pytest.mark.asyncio
async def test_update_dataset_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.update_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = gca_dataset.Dataset()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(gca_dataset.Dataset())
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.update_dataset(
            dataset=gca_dataset.Dataset(
                translation_dataset_metadata=translation.TranslationDatasetMetadata(
                    source_language_code="source_language_code_value"
                )
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].dataset
        mock_val = gca_dataset.Dataset(
            translation_dataset_metadata=translation.TranslationDatasetMetadata(
                source_language_code="source_language_code_value"
            )
        )
        assert arg == mock_val


@pytest.mark.asyncio
async def test_update_dataset_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.update_dataset(
            service.UpdateDatasetRequest(),
            dataset=gca_dataset.Dataset(
                translation_dataset_metadata=translation.TranslationDatasetMetadata(
                    source_language_code="source_language_code_value"
                )
            ),
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.DeleteDatasetRequest,
        dict,
    ],
)
def test_delete_dataset(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/spam")
        response = client.delete_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.DeleteDatasetRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


def test_delete_dataset_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_dataset), "__call__") as call:
        client.delete_dataset()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.DeleteDatasetRequest()


@pytest.mark.asyncio
async def test_delete_dataset_async(
    transport: str = "grpc_asyncio", request_type=service.DeleteDatasetRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        response = await client.delete_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.DeleteDatasetRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


@pytest.mark.asyncio
async def test_delete_dataset_async_from_dict():
    await test_delete_dataset_async(request_type=dict)


def test_delete_dataset_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.DeleteDatasetRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_dataset), "__call__") as call:
        call.return_value = operations_pb2.Operation(name="operations/op")
        client.delete_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_delete_dataset_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.DeleteDatasetRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_dataset), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/op")
        )
        await client.delete_dataset(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_delete_dataset_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.delete_dataset(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


def test_delete_dataset_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.delete_dataset(
            service.DeleteDatasetRequest(),
            name="name_value",
        )


@pytest.mark.asyncio
async def test_delete_dataset_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_dataset), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.delete_dataset(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_delete_dataset_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.delete_dataset(
            service.DeleteDatasetRequest(),
            name="name_value",
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ImportDataRequest,
        dict,
    ],
)
def test_import_data(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.import_data), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/spam")
        response = client.import_data(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ImportDataRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


def test_import_data_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.import_data), "__call__") as call:
        client.import_data()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ImportDataRequest()


@pytest.mark.asyncio
async def test_import_data_async(
    transport: str = "grpc_asyncio", request_type=service.ImportDataRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.import_data), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        response = await client.import_data(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ImportDataRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


@pytest.mark.asyncio
async def test_import_data_async_from_dict():
    await test_import_data_async(request_type=dict)


def test_import_data_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ImportDataRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.import_data), "__call__") as call:
        call.return_value = operations_pb2.Operation(name="operations/op")
        client.import_data(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_import_data_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ImportDataRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.import_data), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/op")
        )
        await client.import_data(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_import_data_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.import_data), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.import_data(
            name="name_value",
            input_config=io.InputConfig(
                gcs_source=io.GcsSource(input_uris=["input_uris_value"])
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val
        arg = args[0].input_config
        mock_val = io.InputConfig(
            gcs_source=io.GcsSource(input_uris=["input_uris_value"])
        )
        assert arg == mock_val


def test_import_data_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.import_data(
            service.ImportDataRequest(),
            name="name_value",
            input_config=io.InputConfig(
                gcs_source=io.GcsSource(input_uris=["input_uris_value"])
            ),
        )


@pytest.mark.asyncio
async def test_import_data_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.import_data), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.import_data(
            name="name_value",
            input_config=io.InputConfig(
                gcs_source=io.GcsSource(input_uris=["input_uris_value"])
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val
        arg = args[0].input_config
        mock_val = io.InputConfig(
            gcs_source=io.GcsSource(input_uris=["input_uris_value"])
        )
        assert arg == mock_val


@pytest.mark.asyncio
async def test_import_data_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.import_data(
            service.ImportDataRequest(),
            name="name_value",
            input_config=io.InputConfig(
                gcs_source=io.GcsSource(input_uris=["input_uris_value"])
            ),
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ExportDataRequest,
        dict,
    ],
)
def test_export_data(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_data), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/spam")
        response = client.export_data(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ExportDataRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


def test_export_data_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_data), "__call__") as call:
        client.export_data()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ExportDataRequest()


@pytest.mark.asyncio
async def test_export_data_async(
    transport: str = "grpc_asyncio", request_type=service.ExportDataRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_data), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        response = await client.export_data(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ExportDataRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


@pytest.mark.asyncio
async def test_export_data_async_from_dict():
    await test_export_data_async(request_type=dict)


def test_export_data_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ExportDataRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_data), "__call__") as call:
        call.return_value = operations_pb2.Operation(name="operations/op")
        client.export_data(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_export_data_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ExportDataRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_data), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/op")
        )
        await client.export_data(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_export_data_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_data), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.export_data(
            name="name_value",
            output_config=io.OutputConfig(
                gcs_destination=io.GcsDestination(
                    output_uri_prefix="output_uri_prefix_value"
                )
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val
        arg = args[0].output_config
        mock_val = io.OutputConfig(
            gcs_destination=io.GcsDestination(
                output_uri_prefix="output_uri_prefix_value"
            )
        )
        assert arg == mock_val


def test_export_data_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.export_data(
            service.ExportDataRequest(),
            name="name_value",
            output_config=io.OutputConfig(
                gcs_destination=io.GcsDestination(
                    output_uri_prefix="output_uri_prefix_value"
                )
            ),
        )


@pytest.mark.asyncio
async def test_export_data_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_data), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.export_data(
            name="name_value",
            output_config=io.OutputConfig(
                gcs_destination=io.GcsDestination(
                    output_uri_prefix="output_uri_prefix_value"
                )
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val
        arg = args[0].output_config
        mock_val = io.OutputConfig(
            gcs_destination=io.GcsDestination(
                output_uri_prefix="output_uri_prefix_value"
            )
        )
        assert arg == mock_val


@pytest.mark.asyncio
async def test_export_data_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.export_data(
            service.ExportDataRequest(),
            name="name_value",
            output_config=io.OutputConfig(
                gcs_destination=io.GcsDestination(
                    output_uri_prefix="output_uri_prefix_value"
                )
            ),
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.GetAnnotationSpecRequest,
        dict,
    ],
)
def test_get_annotation_spec(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_annotation_spec), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = annotation_spec.AnnotationSpec(
            name="name_value",
            display_name="display_name_value",
            example_count=1396,
        )
        response = client.get_annotation_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetAnnotationSpecRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, annotation_spec.AnnotationSpec)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.example_count == 1396


def test_get_annotation_spec_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_annotation_spec), "__call__"
    ) as call:
        client.get_annotation_spec()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetAnnotationSpecRequest()


@pytest.mark.asyncio
async def test_get_annotation_spec_async(
    transport: str = "grpc_asyncio", request_type=service.GetAnnotationSpecRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_annotation_spec), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            annotation_spec.AnnotationSpec(
                name="name_value",
                display_name="display_name_value",
                example_count=1396,
            )
        )
        response = await client.get_annotation_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetAnnotationSpecRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, annotation_spec.AnnotationSpec)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.example_count == 1396


@pytest.mark.asyncio
async def test_get_annotation_spec_async_from_dict():
    await test_get_annotation_spec_async(request_type=dict)


def test_get_annotation_spec_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.GetAnnotationSpecRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_annotation_spec), "__call__"
    ) as call:
        call.return_value = annotation_spec.AnnotationSpec()
        client.get_annotation_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_get_annotation_spec_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.GetAnnotationSpecRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_annotation_spec), "__call__"
    ) as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            annotation_spec.AnnotationSpec()
        )
        await client.get_annotation_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_get_annotation_spec_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_annotation_spec), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = annotation_spec.AnnotationSpec()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.get_annotation_spec(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


def test_get_annotation_spec_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.get_annotation_spec(
            service.GetAnnotationSpecRequest(),
            name="name_value",
        )


@pytest.mark.asyncio
async def test_get_annotation_spec_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_annotation_spec), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = annotation_spec.AnnotationSpec()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            annotation_spec.AnnotationSpec()
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.get_annotation_spec(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_get_annotation_spec_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.get_annotation_spec(
            service.GetAnnotationSpecRequest(),
            name="name_value",
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.GetTableSpecRequest,
        dict,
    ],
)
def test_get_table_spec(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_table_spec), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = table_spec.TableSpec(
            name="name_value",
            time_column_spec_id="time_column_spec_id_value",
            row_count=992,
            valid_row_count=1615,
            column_count=1302,
            etag="etag_value",
        )
        response = client.get_table_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetTableSpecRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, table_spec.TableSpec)
    assert response.name == "name_value"
    assert response.time_column_spec_id == "time_column_spec_id_value"
    assert response.row_count == 992
    assert response.valid_row_count == 1615
    assert response.column_count == 1302
    assert response.etag == "etag_value"


def test_get_table_spec_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_table_spec), "__call__") as call:
        client.get_table_spec()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetTableSpecRequest()


@pytest.mark.asyncio
async def test_get_table_spec_async(
    transport: str = "grpc_asyncio", request_type=service.GetTableSpecRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_table_spec), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            table_spec.TableSpec(
                name="name_value",
                time_column_spec_id="time_column_spec_id_value",
                row_count=992,
                valid_row_count=1615,
                column_count=1302,
                etag="etag_value",
            )
        )
        response = await client.get_table_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetTableSpecRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, table_spec.TableSpec)
    assert response.name == "name_value"
    assert response.time_column_spec_id == "time_column_spec_id_value"
    assert response.row_count == 992
    assert response.valid_row_count == 1615
    assert response.column_count == 1302
    assert response.etag == "etag_value"


@pytest.mark.asyncio
async def test_get_table_spec_async_from_dict():
    await test_get_table_spec_async(request_type=dict)


def test_get_table_spec_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.GetTableSpecRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_table_spec), "__call__") as call:
        call.return_value = table_spec.TableSpec()
        client.get_table_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_get_table_spec_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.GetTableSpecRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_table_spec), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            table_spec.TableSpec()
        )
        await client.get_table_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_get_table_spec_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_table_spec), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = table_spec.TableSpec()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.get_table_spec(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


def test_get_table_spec_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.get_table_spec(
            service.GetTableSpecRequest(),
            name="name_value",
        )


@pytest.mark.asyncio
async def test_get_table_spec_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_table_spec), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = table_spec.TableSpec()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            table_spec.TableSpec()
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.get_table_spec(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_get_table_spec_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.get_table_spec(
            service.GetTableSpecRequest(),
            name="name_value",
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ListTableSpecsRequest,
        dict,
    ],
)
def test_list_table_specs(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_table_specs), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListTableSpecsResponse(
            next_page_token="next_page_token_value",
        )
        response = client.list_table_specs(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListTableSpecsRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListTableSpecsPager)
    assert response.next_page_token == "next_page_token_value"


def test_list_table_specs_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_table_specs), "__call__") as call:
        client.list_table_specs()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListTableSpecsRequest()


@pytest.mark.asyncio
async def test_list_table_specs_async(
    transport: str = "grpc_asyncio", request_type=service.ListTableSpecsRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_table_specs), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListTableSpecsResponse(
                next_page_token="next_page_token_value",
            )
        )
        response = await client.list_table_specs(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListTableSpecsRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListTableSpecsAsyncPager)
    assert response.next_page_token == "next_page_token_value"


@pytest.mark.asyncio
async def test_list_table_specs_async_from_dict():
    await test_list_table_specs_async(request_type=dict)


def test_list_table_specs_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ListTableSpecsRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_table_specs), "__call__") as call:
        call.return_value = service.ListTableSpecsResponse()
        client.list_table_specs(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_list_table_specs_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ListTableSpecsRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_table_specs), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListTableSpecsResponse()
        )
        await client.list_table_specs(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


def test_list_table_specs_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_table_specs), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListTableSpecsResponse()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.list_table_specs(
            parent="parent_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val


def test_list_table_specs_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.list_table_specs(
            service.ListTableSpecsRequest(),
            parent="parent_value",
        )


@pytest.mark.asyncio
async def test_list_table_specs_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_table_specs), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListTableSpecsResponse()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListTableSpecsResponse()
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.list_table_specs(
            parent="parent_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_list_table_specs_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.list_table_specs(
            service.ListTableSpecsRequest(),
            parent="parent_value",
        )


def test_list_table_specs_pager(transport_name: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport_name,
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_table_specs), "__call__") as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                ],
                next_page_token="abc",
            ),
            service.ListTableSpecsResponse(
                table_specs=[],
                next_page_token="def",
            ),
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                ],
                next_page_token="ghi",
            ),
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                ],
            ),
            RuntimeError,
        )

        metadata = ()
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", ""),)),
        )
        pager = client.list_table_specs(request={})

        assert pager._metadata == metadata

        results = list(pager)
        assert len(results) == 6
        assert all(isinstance(i, table_spec.TableSpec) for i in results)


def test_list_table_specs_pages(transport_name: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport_name,
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_table_specs), "__call__") as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                ],
                next_page_token="abc",
            ),
            service.ListTableSpecsResponse(
                table_specs=[],
                next_page_token="def",
            ),
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                ],
                next_page_token="ghi",
            ),
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                ],
            ),
            RuntimeError,
        )
        pages = list(client.list_table_specs(request={}).pages)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.asyncio
async def test_list_table_specs_async_pager():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_table_specs), "__call__", new_callable=mock.AsyncMock
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                ],
                next_page_token="abc",
            ),
            service.ListTableSpecsResponse(
                table_specs=[],
                next_page_token="def",
            ),
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                ],
                next_page_token="ghi",
            ),
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                ],
            ),
            RuntimeError,
        )
        async_pager = await client.list_table_specs(
            request={},
        )
        assert async_pager.next_page_token == "abc"
        responses = []
        async for response in async_pager:  # pragma: no branch
            responses.append(response)

        assert len(responses) == 6
        assert all(isinstance(i, table_spec.TableSpec) for i in responses)


@pytest.mark.asyncio
async def test_list_table_specs_async_pages():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_table_specs), "__call__", new_callable=mock.AsyncMock
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                ],
                next_page_token="abc",
            ),
            service.ListTableSpecsResponse(
                table_specs=[],
                next_page_token="def",
            ),
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                ],
                next_page_token="ghi",
            ),
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                ],
            ),
            RuntimeError,
        )
        pages = []
        # Workaround issue in python 3.9 related to code coverage by adding `# pragma: no branch`
        # See https://github.com/googleapis/gapic-generator-python/pull/1174#issuecomment-1025132372
        async for page_ in (  # pragma: no branch
            await client.list_table_specs(request={})
        ).pages:
            pages.append(page_)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.parametrize(
    "request_type",
    [
        service.UpdateTableSpecRequest,
        dict,
    ],
)
def test_update_table_spec(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_table_spec), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = gca_table_spec.TableSpec(
            name="name_value",
            time_column_spec_id="time_column_spec_id_value",
            row_count=992,
            valid_row_count=1615,
            column_count=1302,
            etag="etag_value",
        )
        response = client.update_table_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.UpdateTableSpecRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, gca_table_spec.TableSpec)
    assert response.name == "name_value"
    assert response.time_column_spec_id == "time_column_spec_id_value"
    assert response.row_count == 992
    assert response.valid_row_count == 1615
    assert response.column_count == 1302
    assert response.etag == "etag_value"


def test_update_table_spec_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_table_spec), "__call__"
    ) as call:
        client.update_table_spec()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.UpdateTableSpecRequest()


@pytest.mark.asyncio
async def test_update_table_spec_async(
    transport: str = "grpc_asyncio", request_type=service.UpdateTableSpecRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_table_spec), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            gca_table_spec.TableSpec(
                name="name_value",
                time_column_spec_id="time_column_spec_id_value",
                row_count=992,
                valid_row_count=1615,
                column_count=1302,
                etag="etag_value",
            )
        )
        response = await client.update_table_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.UpdateTableSpecRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, gca_table_spec.TableSpec)
    assert response.name == "name_value"
    assert response.time_column_spec_id == "time_column_spec_id_value"
    assert response.row_count == 992
    assert response.valid_row_count == 1615
    assert response.column_count == 1302
    assert response.etag == "etag_value"


@pytest.mark.asyncio
async def test_update_table_spec_async_from_dict():
    await test_update_table_spec_async(request_type=dict)


def test_update_table_spec_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.UpdateTableSpecRequest()

    request.table_spec.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_table_spec), "__call__"
    ) as call:
        call.return_value = gca_table_spec.TableSpec()
        client.update_table_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "table_spec.name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_update_table_spec_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.UpdateTableSpecRequest()

    request.table_spec.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_table_spec), "__call__"
    ) as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            gca_table_spec.TableSpec()
        )
        await client.update_table_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "table_spec.name=name_value",
    ) in kw["metadata"]


def test_update_table_spec_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_table_spec), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = gca_table_spec.TableSpec()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.update_table_spec(
            table_spec=gca_table_spec.TableSpec(name="name_value"),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].table_spec
        mock_val = gca_table_spec.TableSpec(name="name_value")
        assert arg == mock_val


def test_update_table_spec_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.update_table_spec(
            service.UpdateTableSpecRequest(),
            table_spec=gca_table_spec.TableSpec(name="name_value"),
        )


@pytest.mark.asyncio
async def test_update_table_spec_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_table_spec), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = gca_table_spec.TableSpec()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            gca_table_spec.TableSpec()
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.update_table_spec(
            table_spec=gca_table_spec.TableSpec(name="name_value"),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].table_spec
        mock_val = gca_table_spec.TableSpec(name="name_value")
        assert arg == mock_val


@pytest.mark.asyncio
async def test_update_table_spec_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.update_table_spec(
            service.UpdateTableSpecRequest(),
            table_spec=gca_table_spec.TableSpec(name="name_value"),
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.GetColumnSpecRequest,
        dict,
    ],
)
def test_get_column_spec(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_column_spec), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = column_spec.ColumnSpec(
            name="name_value",
            display_name="display_name_value",
            etag="etag_value",
        )
        response = client.get_column_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetColumnSpecRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, column_spec.ColumnSpec)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.etag == "etag_value"


def test_get_column_spec_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_column_spec), "__call__") as call:
        client.get_column_spec()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetColumnSpecRequest()


@pytest.mark.asyncio
async def test_get_column_spec_async(
    transport: str = "grpc_asyncio", request_type=service.GetColumnSpecRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_column_spec), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            column_spec.ColumnSpec(
                name="name_value",
                display_name="display_name_value",
                etag="etag_value",
            )
        )
        response = await client.get_column_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetColumnSpecRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, column_spec.ColumnSpec)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.etag == "etag_value"


@pytest.mark.asyncio
async def test_get_column_spec_async_from_dict():
    await test_get_column_spec_async(request_type=dict)


def test_get_column_spec_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.GetColumnSpecRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_column_spec), "__call__") as call:
        call.return_value = column_spec.ColumnSpec()
        client.get_column_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_get_column_spec_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.GetColumnSpecRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_column_spec), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            column_spec.ColumnSpec()
        )
        await client.get_column_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_get_column_spec_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_column_spec), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = column_spec.ColumnSpec()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.get_column_spec(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


def test_get_column_spec_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.get_column_spec(
            service.GetColumnSpecRequest(),
            name="name_value",
        )


@pytest.mark.asyncio
async def test_get_column_spec_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_column_spec), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = column_spec.ColumnSpec()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            column_spec.ColumnSpec()
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.get_column_spec(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_get_column_spec_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.get_column_spec(
            service.GetColumnSpecRequest(),
            name="name_value",
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ListColumnSpecsRequest,
        dict,
    ],
)
def test_list_column_specs(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_column_specs), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListColumnSpecsResponse(
            next_page_token="next_page_token_value",
        )
        response = client.list_column_specs(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListColumnSpecsRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListColumnSpecsPager)
    assert response.next_page_token == "next_page_token_value"


def test_list_column_specs_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_column_specs), "__call__"
    ) as call:
        client.list_column_specs()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListColumnSpecsRequest()


@pytest.mark.asyncio
async def test_list_column_specs_async(
    transport: str = "grpc_asyncio", request_type=service.ListColumnSpecsRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_column_specs), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListColumnSpecsResponse(
                next_page_token="next_page_token_value",
            )
        )
        response = await client.list_column_specs(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListColumnSpecsRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListColumnSpecsAsyncPager)
    assert response.next_page_token == "next_page_token_value"


@pytest.mark.asyncio
async def test_list_column_specs_async_from_dict():
    await test_list_column_specs_async(request_type=dict)


def test_list_column_specs_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ListColumnSpecsRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_column_specs), "__call__"
    ) as call:
        call.return_value = service.ListColumnSpecsResponse()
        client.list_column_specs(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_list_column_specs_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ListColumnSpecsRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_column_specs), "__call__"
    ) as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListColumnSpecsResponse()
        )
        await client.list_column_specs(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


def test_list_column_specs_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_column_specs), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListColumnSpecsResponse()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.list_column_specs(
            parent="parent_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val


def test_list_column_specs_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.list_column_specs(
            service.ListColumnSpecsRequest(),
            parent="parent_value",
        )


@pytest.mark.asyncio
async def test_list_column_specs_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_column_specs), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListColumnSpecsResponse()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListColumnSpecsResponse()
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.list_column_specs(
            parent="parent_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_list_column_specs_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.list_column_specs(
            service.ListColumnSpecsRequest(),
            parent="parent_value",
        )


def test_list_column_specs_pager(transport_name: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport_name,
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_column_specs), "__call__"
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                ],
                next_page_token="abc",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[],
                next_page_token="def",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                ],
                next_page_token="ghi",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                ],
            ),
            RuntimeError,
        )

        metadata = ()
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", ""),)),
        )
        pager = client.list_column_specs(request={})

        assert pager._metadata == metadata

        results = list(pager)
        assert len(results) == 6
        assert all(isinstance(i, column_spec.ColumnSpec) for i in results)


def test_list_column_specs_pages(transport_name: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport_name,
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_column_specs), "__call__"
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                ],
                next_page_token="abc",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[],
                next_page_token="def",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                ],
                next_page_token="ghi",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                ],
            ),
            RuntimeError,
        )
        pages = list(client.list_column_specs(request={}).pages)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.asyncio
async def test_list_column_specs_async_pager():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_column_specs),
        "__call__",
        new_callable=mock.AsyncMock,
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                ],
                next_page_token="abc",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[],
                next_page_token="def",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                ],
                next_page_token="ghi",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                ],
            ),
            RuntimeError,
        )
        async_pager = await client.list_column_specs(
            request={},
        )
        assert async_pager.next_page_token == "abc"
        responses = []
        async for response in async_pager:  # pragma: no branch
            responses.append(response)

        assert len(responses) == 6
        assert all(isinstance(i, column_spec.ColumnSpec) for i in responses)


@pytest.mark.asyncio
async def test_list_column_specs_async_pages():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_column_specs),
        "__call__",
        new_callable=mock.AsyncMock,
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                ],
                next_page_token="abc",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[],
                next_page_token="def",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                ],
                next_page_token="ghi",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                ],
            ),
            RuntimeError,
        )
        pages = []
        # Workaround issue in python 3.9 related to code coverage by adding `# pragma: no branch`
        # See https://github.com/googleapis/gapic-generator-python/pull/1174#issuecomment-1025132372
        async for page_ in (  # pragma: no branch
            await client.list_column_specs(request={})
        ).pages:
            pages.append(page_)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.parametrize(
    "request_type",
    [
        service.UpdateColumnSpecRequest,
        dict,
    ],
)
def test_update_column_spec(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_column_spec), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = gca_column_spec.ColumnSpec(
            name="name_value",
            display_name="display_name_value",
            etag="etag_value",
        )
        response = client.update_column_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.UpdateColumnSpecRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, gca_column_spec.ColumnSpec)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.etag == "etag_value"


def test_update_column_spec_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_column_spec), "__call__"
    ) as call:
        client.update_column_spec()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.UpdateColumnSpecRequest()


@pytest.mark.asyncio
async def test_update_column_spec_async(
    transport: str = "grpc_asyncio", request_type=service.UpdateColumnSpecRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_column_spec), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            gca_column_spec.ColumnSpec(
                name="name_value",
                display_name="display_name_value",
                etag="etag_value",
            )
        )
        response = await client.update_column_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.UpdateColumnSpecRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, gca_column_spec.ColumnSpec)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.etag == "etag_value"


@pytest.mark.asyncio
async def test_update_column_spec_async_from_dict():
    await test_update_column_spec_async(request_type=dict)


def test_update_column_spec_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.UpdateColumnSpecRequest()

    request.column_spec.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_column_spec), "__call__"
    ) as call:
        call.return_value = gca_column_spec.ColumnSpec()
        client.update_column_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "column_spec.name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_update_column_spec_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.UpdateColumnSpecRequest()

    request.column_spec.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_column_spec), "__call__"
    ) as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            gca_column_spec.ColumnSpec()
        )
        await client.update_column_spec(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "column_spec.name=name_value",
    ) in kw["metadata"]


def test_update_column_spec_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_column_spec), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = gca_column_spec.ColumnSpec()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.update_column_spec(
            column_spec=gca_column_spec.ColumnSpec(name="name_value"),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].column_spec
        mock_val = gca_column_spec.ColumnSpec(name="name_value")
        assert arg == mock_val


def test_update_column_spec_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.update_column_spec(
            service.UpdateColumnSpecRequest(),
            column_spec=gca_column_spec.ColumnSpec(name="name_value"),
        )


@pytest.mark.asyncio
async def test_update_column_spec_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.update_column_spec), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = gca_column_spec.ColumnSpec()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            gca_column_spec.ColumnSpec()
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.update_column_spec(
            column_spec=gca_column_spec.ColumnSpec(name="name_value"),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].column_spec
        mock_val = gca_column_spec.ColumnSpec(name="name_value")
        assert arg == mock_val


@pytest.mark.asyncio
async def test_update_column_spec_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.update_column_spec(
            service.UpdateColumnSpecRequest(),
            column_spec=gca_column_spec.ColumnSpec(name="name_value"),
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.CreateModelRequest,
        dict,
    ],
)
def test_create_model(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/spam")
        response = client.create_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.CreateModelRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


def test_create_model_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_model), "__call__") as call:
        client.create_model()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.CreateModelRequest()


@pytest.mark.asyncio
async def test_create_model_async(
    transport: str = "grpc_asyncio", request_type=service.CreateModelRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        response = await client.create_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.CreateModelRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


@pytest.mark.asyncio
async def test_create_model_async_from_dict():
    await test_create_model_async(request_type=dict)


def test_create_model_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.CreateModelRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_model), "__call__") as call:
        call.return_value = operations_pb2.Operation(name="operations/op")
        client.create_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_create_model_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.CreateModelRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_model), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/op")
        )
        await client.create_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


def test_create_model_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.create_model(
            parent="parent_value",
            model=gca_model.Model(
                translation_model_metadata=translation.TranslationModelMetadata(
                    base_model="base_model_value"
                )
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val
        arg = args[0].model
        mock_val = gca_model.Model(
            translation_model_metadata=translation.TranslationModelMetadata(
                base_model="base_model_value"
            )
        )
        assert arg == mock_val


def test_create_model_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.create_model(
            service.CreateModelRequest(),
            parent="parent_value",
            model=gca_model.Model(
                translation_model_metadata=translation.TranslationModelMetadata(
                    base_model="base_model_value"
                )
            ),
        )


@pytest.mark.asyncio
async def test_create_model_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.create_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.create_model(
            parent="parent_value",
            model=gca_model.Model(
                translation_model_metadata=translation.TranslationModelMetadata(
                    base_model="base_model_value"
                )
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val
        arg = args[0].model
        mock_val = gca_model.Model(
            translation_model_metadata=translation.TranslationModelMetadata(
                base_model="base_model_value"
            )
        )
        assert arg == mock_val


@pytest.mark.asyncio
async def test_create_model_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.create_model(
            service.CreateModelRequest(),
            parent="parent_value",
            model=gca_model.Model(
                translation_model_metadata=translation.TranslationModelMetadata(
                    base_model="base_model_value"
                )
            ),
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.GetModelRequest,
        dict,
    ],
)
def test_get_model(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = model.Model(
            name="name_value",
            display_name="display_name_value",
            dataset_id="dataset_id_value",
            deployment_state=model.Model.DeploymentState.DEPLOYED,
        )
        response = client.get_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetModelRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, model.Model)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.dataset_id == "dataset_id_value"
    assert response.deployment_state == model.Model.DeploymentState.DEPLOYED


def test_get_model_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_model), "__call__") as call:
        client.get_model()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetModelRequest()


@pytest.mark.asyncio
async def test_get_model_async(
    transport: str = "grpc_asyncio", request_type=service.GetModelRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            model.Model(
                name="name_value",
                display_name="display_name_value",
                dataset_id="dataset_id_value",
                deployment_state=model.Model.DeploymentState.DEPLOYED,
            )
        )
        response = await client.get_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetModelRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, model.Model)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.dataset_id == "dataset_id_value"
    assert response.deployment_state == model.Model.DeploymentState.DEPLOYED


@pytest.mark.asyncio
async def test_get_model_async_from_dict():
    await test_get_model_async(request_type=dict)


def test_get_model_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.GetModelRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_model), "__call__") as call:
        call.return_value = model.Model()
        client.get_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_get_model_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.GetModelRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_model), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(model.Model())
        await client.get_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_get_model_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = model.Model()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.get_model(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


def test_get_model_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.get_model(
            service.GetModelRequest(),
            name="name_value",
        )


@pytest.mark.asyncio
async def test_get_model_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.get_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = model.Model()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(model.Model())
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.get_model(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_get_model_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.get_model(
            service.GetModelRequest(),
            name="name_value",
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ListModelsRequest,
        dict,
    ],
)
def test_list_models(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_models), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListModelsResponse(
            next_page_token="next_page_token_value",
        )
        response = client.list_models(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListModelsRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListModelsPager)
    assert response.next_page_token == "next_page_token_value"


def test_list_models_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_models), "__call__") as call:
        client.list_models()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListModelsRequest()


@pytest.mark.asyncio
async def test_list_models_async(
    transport: str = "grpc_asyncio", request_type=service.ListModelsRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_models), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListModelsResponse(
                next_page_token="next_page_token_value",
            )
        )
        response = await client.list_models(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListModelsRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListModelsAsyncPager)
    assert response.next_page_token == "next_page_token_value"


@pytest.mark.asyncio
async def test_list_models_async_from_dict():
    await test_list_models_async(request_type=dict)


def test_list_models_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ListModelsRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_models), "__call__") as call:
        call.return_value = service.ListModelsResponse()
        client.list_models(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_list_models_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ListModelsRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_models), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListModelsResponse()
        )
        await client.list_models(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


def test_list_models_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_models), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListModelsResponse()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.list_models(
            parent="parent_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val


def test_list_models_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.list_models(
            service.ListModelsRequest(),
            parent="parent_value",
        )


@pytest.mark.asyncio
async def test_list_models_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_models), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListModelsResponse()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListModelsResponse()
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.list_models(
            parent="parent_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_list_models_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.list_models(
            service.ListModelsRequest(),
            parent="parent_value",
        )


def test_list_models_pager(transport_name: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport_name,
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_models), "__call__") as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListModelsResponse(
                model=[
                    model.Model(),
                    model.Model(),
                    model.Model(),
                ],
                next_page_token="abc",
            ),
            service.ListModelsResponse(
                model=[],
                next_page_token="def",
            ),
            service.ListModelsResponse(
                model=[
                    model.Model(),
                ],
                next_page_token="ghi",
            ),
            service.ListModelsResponse(
                model=[
                    model.Model(),
                    model.Model(),
                ],
            ),
            RuntimeError,
        )

        metadata = ()
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", ""),)),
        )
        pager = client.list_models(request={})

        assert pager._metadata == metadata

        results = list(pager)
        assert len(results) == 6
        assert all(isinstance(i, model.Model) for i in results)


def test_list_models_pages(transport_name: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport_name,
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.list_models), "__call__") as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListModelsResponse(
                model=[
                    model.Model(),
                    model.Model(),
                    model.Model(),
                ],
                next_page_token="abc",
            ),
            service.ListModelsResponse(
                model=[],
                next_page_token="def",
            ),
            service.ListModelsResponse(
                model=[
                    model.Model(),
                ],
                next_page_token="ghi",
            ),
            service.ListModelsResponse(
                model=[
                    model.Model(),
                    model.Model(),
                ],
            ),
            RuntimeError,
        )
        pages = list(client.list_models(request={}).pages)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.asyncio
async def test_list_models_async_pager():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_models), "__call__", new_callable=mock.AsyncMock
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListModelsResponse(
                model=[
                    model.Model(),
                    model.Model(),
                    model.Model(),
                ],
                next_page_token="abc",
            ),
            service.ListModelsResponse(
                model=[],
                next_page_token="def",
            ),
            service.ListModelsResponse(
                model=[
                    model.Model(),
                ],
                next_page_token="ghi",
            ),
            service.ListModelsResponse(
                model=[
                    model.Model(),
                    model.Model(),
                ],
            ),
            RuntimeError,
        )
        async_pager = await client.list_models(
            request={},
        )
        assert async_pager.next_page_token == "abc"
        responses = []
        async for response in async_pager:  # pragma: no branch
            responses.append(response)

        assert len(responses) == 6
        assert all(isinstance(i, model.Model) for i in responses)


@pytest.mark.asyncio
async def test_list_models_async_pages():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_models), "__call__", new_callable=mock.AsyncMock
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListModelsResponse(
                model=[
                    model.Model(),
                    model.Model(),
                    model.Model(),
                ],
                next_page_token="abc",
            ),
            service.ListModelsResponse(
                model=[],
                next_page_token="def",
            ),
            service.ListModelsResponse(
                model=[
                    model.Model(),
                ],
                next_page_token="ghi",
            ),
            service.ListModelsResponse(
                model=[
                    model.Model(),
                    model.Model(),
                ],
            ),
            RuntimeError,
        )
        pages = []
        # Workaround issue in python 3.9 related to code coverage by adding `# pragma: no branch`
        # See https://github.com/googleapis/gapic-generator-python/pull/1174#issuecomment-1025132372
        async for page_ in (  # pragma: no branch
            await client.list_models(request={})
        ).pages:
            pages.append(page_)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.parametrize(
    "request_type",
    [
        service.DeleteModelRequest,
        dict,
    ],
)
def test_delete_model(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/spam")
        response = client.delete_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.DeleteModelRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


def test_delete_model_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_model), "__call__") as call:
        client.delete_model()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.DeleteModelRequest()


@pytest.mark.asyncio
async def test_delete_model_async(
    transport: str = "grpc_asyncio", request_type=service.DeleteModelRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        response = await client.delete_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.DeleteModelRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


@pytest.mark.asyncio
async def test_delete_model_async_from_dict():
    await test_delete_model_async(request_type=dict)


def test_delete_model_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.DeleteModelRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_model), "__call__") as call:
        call.return_value = operations_pb2.Operation(name="operations/op")
        client.delete_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_delete_model_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.DeleteModelRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_model), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/op")
        )
        await client.delete_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_delete_model_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.delete_model(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


def test_delete_model_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.delete_model(
            service.DeleteModelRequest(),
            name="name_value",
        )


@pytest.mark.asyncio
async def test_delete_model_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.delete_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.delete_model(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_delete_model_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.delete_model(
            service.DeleteModelRequest(),
            name="name_value",
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.DeployModelRequest,
        dict,
    ],
)
def test_deploy_model(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.deploy_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/spam")
        response = client.deploy_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.DeployModelRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


def test_deploy_model_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.deploy_model), "__call__") as call:
        client.deploy_model()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.DeployModelRequest()


@pytest.mark.asyncio
async def test_deploy_model_async(
    transport: str = "grpc_asyncio", request_type=service.DeployModelRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.deploy_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        response = await client.deploy_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.DeployModelRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


@pytest.mark.asyncio
async def test_deploy_model_async_from_dict():
    await test_deploy_model_async(request_type=dict)


def test_deploy_model_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.DeployModelRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.deploy_model), "__call__") as call:
        call.return_value = operations_pb2.Operation(name="operations/op")
        client.deploy_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_deploy_model_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.DeployModelRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.deploy_model), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/op")
        )
        await client.deploy_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_deploy_model_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.deploy_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.deploy_model(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


def test_deploy_model_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.deploy_model(
            service.DeployModelRequest(),
            name="name_value",
        )


@pytest.mark.asyncio
async def test_deploy_model_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.deploy_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.deploy_model(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_deploy_model_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.deploy_model(
            service.DeployModelRequest(),
            name="name_value",
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.UndeployModelRequest,
        dict,
    ],
)
def test_undeploy_model(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.undeploy_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/spam")
        response = client.undeploy_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.UndeployModelRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


def test_undeploy_model_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.undeploy_model), "__call__") as call:
        client.undeploy_model()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.UndeployModelRequest()


@pytest.mark.asyncio
async def test_undeploy_model_async(
    transport: str = "grpc_asyncio", request_type=service.UndeployModelRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.undeploy_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        response = await client.undeploy_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.UndeployModelRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


@pytest.mark.asyncio
async def test_undeploy_model_async_from_dict():
    await test_undeploy_model_async(request_type=dict)


def test_undeploy_model_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.UndeployModelRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.undeploy_model), "__call__") as call:
        call.return_value = operations_pb2.Operation(name="operations/op")
        client.undeploy_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_undeploy_model_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.UndeployModelRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.undeploy_model), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/op")
        )
        await client.undeploy_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_undeploy_model_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.undeploy_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.undeploy_model(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


def test_undeploy_model_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.undeploy_model(
            service.UndeployModelRequest(),
            name="name_value",
        )


@pytest.mark.asyncio
async def test_undeploy_model_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.undeploy_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.undeploy_model(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_undeploy_model_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.undeploy_model(
            service.UndeployModelRequest(),
            name="name_value",
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ExportModelRequest,
        dict,
    ],
)
def test_export_model(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/spam")
        response = client.export_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ExportModelRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


def test_export_model_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_model), "__call__") as call:
        client.export_model()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ExportModelRequest()


@pytest.mark.asyncio
async def test_export_model_async(
    transport: str = "grpc_asyncio", request_type=service.ExportModelRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        response = await client.export_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ExportModelRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


@pytest.mark.asyncio
async def test_export_model_async_from_dict():
    await test_export_model_async(request_type=dict)


def test_export_model_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ExportModelRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_model), "__call__") as call:
        call.return_value = operations_pb2.Operation(name="operations/op")
        client.export_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_export_model_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ExportModelRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_model), "__call__") as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/op")
        )
        await client.export_model(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_export_model_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.export_model(
            name="name_value",
            output_config=io.ModelExportOutputConfig(
                gcs_destination=io.GcsDestination(
                    output_uri_prefix="output_uri_prefix_value"
                )
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val
        arg = args[0].output_config
        mock_val = io.ModelExportOutputConfig(
            gcs_destination=io.GcsDestination(
                output_uri_prefix="output_uri_prefix_value"
            )
        )
        assert arg == mock_val


def test_export_model_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.export_model(
            service.ExportModelRequest(),
            name="name_value",
            output_config=io.ModelExportOutputConfig(
                gcs_destination=io.GcsDestination(
                    output_uri_prefix="output_uri_prefix_value"
                )
            ),
        )


@pytest.mark.asyncio
async def test_export_model_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(type(client.transport.export_model), "__call__") as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.export_model(
            name="name_value",
            output_config=io.ModelExportOutputConfig(
                gcs_destination=io.GcsDestination(
                    output_uri_prefix="output_uri_prefix_value"
                )
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val
        arg = args[0].output_config
        mock_val = io.ModelExportOutputConfig(
            gcs_destination=io.GcsDestination(
                output_uri_prefix="output_uri_prefix_value"
            )
        )
        assert arg == mock_val


@pytest.mark.asyncio
async def test_export_model_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.export_model(
            service.ExportModelRequest(),
            name="name_value",
            output_config=io.ModelExportOutputConfig(
                gcs_destination=io.GcsDestination(
                    output_uri_prefix="output_uri_prefix_value"
                )
            ),
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ExportEvaluatedExamplesRequest,
        dict,
    ],
)
def test_export_evaluated_examples(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.export_evaluated_examples), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/spam")
        response = client.export_evaluated_examples(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ExportEvaluatedExamplesRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


def test_export_evaluated_examples_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.export_evaluated_examples), "__call__"
    ) as call:
        client.export_evaluated_examples()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ExportEvaluatedExamplesRequest()


@pytest.mark.asyncio
async def test_export_evaluated_examples_async(
    transport: str = "grpc_asyncio", request_type=service.ExportEvaluatedExamplesRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.export_evaluated_examples), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        response = await client.export_evaluated_examples(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ExportEvaluatedExamplesRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, future.Future)


@pytest.mark.asyncio
async def test_export_evaluated_examples_async_from_dict():
    await test_export_evaluated_examples_async(request_type=dict)


def test_export_evaluated_examples_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ExportEvaluatedExamplesRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.export_evaluated_examples), "__call__"
    ) as call:
        call.return_value = operations_pb2.Operation(name="operations/op")
        client.export_evaluated_examples(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_export_evaluated_examples_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ExportEvaluatedExamplesRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.export_evaluated_examples), "__call__"
    ) as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/op")
        )
        await client.export_evaluated_examples(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_export_evaluated_examples_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.export_evaluated_examples), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.export_evaluated_examples(
            name="name_value",
            output_config=io.ExportEvaluatedExamplesOutputConfig(
                bigquery_destination=io.BigQueryDestination(
                    output_uri="output_uri_value"
                )
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val
        arg = args[0].output_config
        mock_val = io.ExportEvaluatedExamplesOutputConfig(
            bigquery_destination=io.BigQueryDestination(output_uri="output_uri_value")
        )
        assert arg == mock_val


def test_export_evaluated_examples_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.export_evaluated_examples(
            service.ExportEvaluatedExamplesRequest(),
            name="name_value",
            output_config=io.ExportEvaluatedExamplesOutputConfig(
                bigquery_destination=io.BigQueryDestination(
                    output_uri="output_uri_value"
                )
            ),
        )


@pytest.mark.asyncio
async def test_export_evaluated_examples_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.export_evaluated_examples), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = operations_pb2.Operation(name="operations/op")

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            operations_pb2.Operation(name="operations/spam")
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.export_evaluated_examples(
            name="name_value",
            output_config=io.ExportEvaluatedExamplesOutputConfig(
                bigquery_destination=io.BigQueryDestination(
                    output_uri="output_uri_value"
                )
            ),
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val
        arg = args[0].output_config
        mock_val = io.ExportEvaluatedExamplesOutputConfig(
            bigquery_destination=io.BigQueryDestination(output_uri="output_uri_value")
        )
        assert arg == mock_val


@pytest.mark.asyncio
async def test_export_evaluated_examples_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.export_evaluated_examples(
            service.ExportEvaluatedExamplesRequest(),
            name="name_value",
            output_config=io.ExportEvaluatedExamplesOutputConfig(
                bigquery_destination=io.BigQueryDestination(
                    output_uri="output_uri_value"
                )
            ),
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.GetModelEvaluationRequest,
        dict,
    ],
)
def test_get_model_evaluation(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_model_evaluation), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = model_evaluation.ModelEvaluation(
            name="name_value",
            annotation_spec_id="annotation_spec_id_value",
            display_name="display_name_value",
            evaluated_example_count=2446,
        )
        response = client.get_model_evaluation(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetModelEvaluationRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, model_evaluation.ModelEvaluation)
    assert response.name == "name_value"
    assert response.annotation_spec_id == "annotation_spec_id_value"
    assert response.display_name == "display_name_value"
    assert response.evaluated_example_count == 2446


def test_get_model_evaluation_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_model_evaluation), "__call__"
    ) as call:
        client.get_model_evaluation()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetModelEvaluationRequest()


@pytest.mark.asyncio
async def test_get_model_evaluation_async(
    transport: str = "grpc_asyncio", request_type=service.GetModelEvaluationRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_model_evaluation), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            model_evaluation.ModelEvaluation(
                name="name_value",
                annotation_spec_id="annotation_spec_id_value",
                display_name="display_name_value",
                evaluated_example_count=2446,
            )
        )
        response = await client.get_model_evaluation(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.GetModelEvaluationRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, model_evaluation.ModelEvaluation)
    assert response.name == "name_value"
    assert response.annotation_spec_id == "annotation_spec_id_value"
    assert response.display_name == "display_name_value"
    assert response.evaluated_example_count == 2446


@pytest.mark.asyncio
async def test_get_model_evaluation_async_from_dict():
    await test_get_model_evaluation_async(request_type=dict)


def test_get_model_evaluation_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.GetModelEvaluationRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_model_evaluation), "__call__"
    ) as call:
        call.return_value = model_evaluation.ModelEvaluation()
        client.get_model_evaluation(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_get_model_evaluation_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.GetModelEvaluationRequest()

    request.name = "name_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_model_evaluation), "__call__"
    ) as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            model_evaluation.ModelEvaluation()
        )
        await client.get_model_evaluation(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "name=name_value",
    ) in kw["metadata"]


def test_get_model_evaluation_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_model_evaluation), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = model_evaluation.ModelEvaluation()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.get_model_evaluation(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


def test_get_model_evaluation_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.get_model_evaluation(
            service.GetModelEvaluationRequest(),
            name="name_value",
        )


@pytest.mark.asyncio
async def test_get_model_evaluation_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.get_model_evaluation), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = model_evaluation.ModelEvaluation()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            model_evaluation.ModelEvaluation()
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.get_model_evaluation(
            name="name_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].name
        mock_val = "name_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_get_model_evaluation_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.get_model_evaluation(
            service.GetModelEvaluationRequest(),
            name="name_value",
        )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ListModelEvaluationsRequest,
        dict,
    ],
)
def test_list_model_evaluations(request_type, transport: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_model_evaluations), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListModelEvaluationsResponse(
            next_page_token="next_page_token_value",
        )
        response = client.list_model_evaluations(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListModelEvaluationsRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListModelEvaluationsPager)
    assert response.next_page_token == "next_page_token_value"


def test_list_model_evaluations_empty_call():
    # This test is a coverage failsafe to make sure that totally empty calls,
    # i.e. request == None and no flattened fields passed, work.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_model_evaluations), "__call__"
    ) as call:
        client.list_model_evaluations()
        call.assert_called()
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListModelEvaluationsRequest()


@pytest.mark.asyncio
async def test_list_model_evaluations_async(
    transport: str = "grpc_asyncio", request_type=service.ListModelEvaluationsRequest
):
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Everything is optional in proto3 as far as the runtime is concerned,
    # and we are mocking out the actual API, so just send an empty request.
    request = request_type()

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_model_evaluations), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListModelEvaluationsResponse(
                next_page_token="next_page_token_value",
            )
        )
        response = await client.list_model_evaluations(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == service.ListModelEvaluationsRequest()

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListModelEvaluationsAsyncPager)
    assert response.next_page_token == "next_page_token_value"


@pytest.mark.asyncio
async def test_list_model_evaluations_async_from_dict():
    await test_list_model_evaluations_async(request_type=dict)


def test_list_model_evaluations_field_headers():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ListModelEvaluationsRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_model_evaluations), "__call__"
    ) as call:
        call.return_value = service.ListModelEvaluationsResponse()
        client.list_model_evaluations(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


@pytest.mark.asyncio
async def test_list_model_evaluations_field_headers_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Any value that is part of the HTTP/1.1 URI should be sent as
    # a field header. Set these to a non-empty value.
    request = service.ListModelEvaluationsRequest()

    request.parent = "parent_value"

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_model_evaluations), "__call__"
    ) as call:
        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListModelEvaluationsResponse()
        )
        await client.list_model_evaluations(request)

        # Establish that the underlying gRPC stub method was called.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        assert args[0] == request

    # Establish that the field header was sent.
    _, _, kw = call.mock_calls[0]
    assert (
        "x-goog-request-params",
        "parent=parent_value",
    ) in kw["metadata"]


def test_list_model_evaluations_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_model_evaluations), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListModelEvaluationsResponse()
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        client.list_model_evaluations(
            parent="parent_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls) == 1
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val


def test_list_model_evaluations_flattened_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.list_model_evaluations(
            service.ListModelEvaluationsRequest(),
            parent="parent_value",
        )


@pytest.mark.asyncio
async def test_list_model_evaluations_flattened_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_model_evaluations), "__call__"
    ) as call:
        # Designate an appropriate return value for the call.
        call.return_value = service.ListModelEvaluationsResponse()

        call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(
            service.ListModelEvaluationsResponse()
        )
        # Call the method with a truthy value for each flattened field,
        # using the keyword arguments to the method.
        response = await client.list_model_evaluations(
            parent="parent_value",
        )

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(call.mock_calls)
        _, args, _ = call.mock_calls[0]
        arg = args[0].parent
        mock_val = "parent_value"
        assert arg == mock_val


@pytest.mark.asyncio
async def test_list_model_evaluations_flattened_error_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        await client.list_model_evaluations(
            service.ListModelEvaluationsRequest(),
            parent="parent_value",
        )


def test_list_model_evaluations_pager(transport_name: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport_name,
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_model_evaluations), "__call__"
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                ],
                next_page_token="abc",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[],
                next_page_token="def",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                ],
                next_page_token="ghi",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                ],
            ),
            RuntimeError,
        )

        metadata = ()
        metadata = tuple(metadata) + (
            gapic_v1.routing_header.to_grpc_metadata((("parent", ""),)),
        )
        pager = client.list_model_evaluations(request={})

        assert pager._metadata == metadata

        results = list(pager)
        assert len(results) == 6
        assert all(isinstance(i, model_evaluation.ModelEvaluation) for i in results)


def test_list_model_evaluations_pages(transport_name: str = "grpc"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport_name,
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_model_evaluations), "__call__"
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                ],
                next_page_token="abc",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[],
                next_page_token="def",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                ],
                next_page_token="ghi",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                ],
            ),
            RuntimeError,
        )
        pages = list(client.list_model_evaluations(request={}).pages)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.asyncio
async def test_list_model_evaluations_async_pager():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_model_evaluations),
        "__call__",
        new_callable=mock.AsyncMock,
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                ],
                next_page_token="abc",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[],
                next_page_token="def",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                ],
                next_page_token="ghi",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                ],
            ),
            RuntimeError,
        )
        async_pager = await client.list_model_evaluations(
            request={},
        )
        assert async_pager.next_page_token == "abc"
        responses = []
        async for response in async_pager:  # pragma: no branch
            responses.append(response)

        assert len(responses) == 6
        assert all(isinstance(i, model_evaluation.ModelEvaluation) for i in responses)


@pytest.mark.asyncio
async def test_list_model_evaluations_async_pages():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )

    # Mock the actual call within the gRPC stub, and fake the request.
    with mock.patch.object(
        type(client.transport.list_model_evaluations),
        "__call__",
        new_callable=mock.AsyncMock,
    ) as call:
        # Set the response to a series of pages.
        call.side_effect = (
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                ],
                next_page_token="abc",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[],
                next_page_token="def",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                ],
                next_page_token="ghi",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                ],
            ),
            RuntimeError,
        )
        pages = []
        # Workaround issue in python 3.9 related to code coverage by adding `# pragma: no branch`
        # See https://github.com/googleapis/gapic-generator-python/pull/1174#issuecomment-1025132372
        async for page_ in (  # pragma: no branch
            await client.list_model_evaluations(request={})
        ).pages:
            pages.append(page_)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.parametrize(
    "request_type",
    [
        service.CreateDatasetRequest,
        dict,
    ],
)
def test_create_dataset_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"parent": "projects/sample1/locations/sample2"}
    request_init["dataset"] = {
        "translation_dataset_metadata": {
            "source_language_code": "source_language_code_value",
            "target_language_code": "target_language_code_value",
        },
        "image_classification_dataset_metadata": {"classification_type": 1},
        "text_classification_dataset_metadata": {"classification_type": 1},
        "image_object_detection_dataset_metadata": {},
        "video_classification_dataset_metadata": {},
        "video_object_tracking_dataset_metadata": {},
        "text_extraction_dataset_metadata": {},
        "text_sentiment_dataset_metadata": {"sentiment_max": 1404},
        "tables_dataset_metadata": {
            "primary_table_spec_id": "primary_table_spec_id_value",
            "target_column_spec_id": "target_column_spec_id_value",
            "weight_column_spec_id": "weight_column_spec_id_value",
            "ml_use_column_spec_id": "ml_use_column_spec_id_value",
            "target_column_correlations": {},
            "stats_update_time": {"seconds": 751, "nanos": 543},
        },
        "name": "name_value",
        "display_name": "display_name_value",
        "description": "description_value",
        "example_count": 1396,
        "create_time": {},
        "etag": "etag_value",
    }
    # The version of a generated dependency at test runtime may differ from the version used during generation.
    # Delete any fields which are not present in the current runtime dependency
    # See https://github.com/googleapis/gapic-generator-python/issues/1748

    # Determine if the message type is proto-plus or protobuf
    test_field = service.CreateDatasetRequest.meta.fields["dataset"]

    def get_message_fields(field):
        # Given a field which is a message (composite type), return a list with
        # all the fields of the message.
        # If the field is not a composite type, return an empty list.
        message_fields = []

        if hasattr(field, "message") and field.message:
            is_field_type_proto_plus_type = not hasattr(field.message, "DESCRIPTOR")

            if is_field_type_proto_plus_type:
                message_fields = field.message.meta.fields.values()
            # Add `# pragma: NO COVER` because there may not be any `*_pb2` field types
            else:  # pragma: NO COVER
                message_fields = field.message.DESCRIPTOR.fields
        return message_fields

    runtime_nested_fields = [
        (field.name, nested_field.name)
        for field in get_message_fields(test_field)
        for nested_field in get_message_fields(field)
    ]

    subfields_not_in_runtime = []

    # For each item in the sample request, create a list of sub fields which are not present at runtime
    # Add `# pragma: NO COVER` because this test code will not run if all subfields are present at runtime
    for field, value in request_init["dataset"].items():  # pragma: NO COVER
        result = None
        is_repeated = False
        # For repeated fields
        if isinstance(value, list) and len(value):
            is_repeated = True
            result = value[0]
        # For fields where the type is another message
        if isinstance(value, dict):
            result = value

        if result and hasattr(result, "keys"):
            for subfield in result.keys():
                if (field, subfield) not in runtime_nested_fields:
                    subfields_not_in_runtime.append(
                        {
                            "field": field,
                            "subfield": subfield,
                            "is_repeated": is_repeated,
                        }
                    )

    # Remove fields from the sample request which are not present in the runtime version of the dependency
    # Add `# pragma: NO COVER` because this test code will not run if all subfields are present at runtime
    for subfield_to_delete in subfields_not_in_runtime:  # pragma: NO COVER
        field = subfield_to_delete.get("field")
        field_repeated = subfield_to_delete.get("is_repeated")
        subfield = subfield_to_delete.get("subfield")
        if subfield:
            if field_repeated:
                for i in range(0, len(request_init["dataset"][field])):
                    del request_init["dataset"][field][i][subfield]
            else:
                del request_init["dataset"][field][subfield]
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = gca_dataset.Dataset(
            name="name_value",
            display_name="display_name_value",
            description="description_value",
            example_count=1396,
            etag="etag_value",
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = gca_dataset.Dataset.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.create_dataset(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, gca_dataset.Dataset)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.description == "description_value"
    assert response.example_count == 1396
    assert response.etag == "etag_value"


def test_create_dataset_rest_required_fields(request_type=service.CreateDatasetRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["parent"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).create_dataset._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["parent"] = "parent_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).create_dataset._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "parent" in jsonified_request
    assert jsonified_request["parent"] == "parent_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = gca_dataset.Dataset()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "post",
                "query_params": pb_request,
            }
            transcode_result["body"] = pb_request
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = gca_dataset.Dataset.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.create_dataset(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_create_dataset_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.create_dataset._get_unset_required_fields({})
    assert set(unset_fields) == (
        set(())
        & set(
            (
                "parent",
                "dataset",
            )
        )
    )


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_create_dataset_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_create_dataset"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_create_dataset"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.CreateDatasetRequest.pb(service.CreateDatasetRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = gca_dataset.Dataset.to_json(gca_dataset.Dataset())

        request = service.CreateDatasetRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = gca_dataset.Dataset()

        client.create_dataset(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_create_dataset_rest_bad_request(
    transport: str = "rest", request_type=service.CreateDatasetRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"parent": "projects/sample1/locations/sample2"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.create_dataset(request)


def test_create_dataset_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = gca_dataset.Dataset()

        # get arguments that satisfy an http rule for this method
        sample_request = {"parent": "projects/sample1/locations/sample2"}

        # get truthy value for each flattened field
        mock_args = dict(
            parent="parent_value",
            dataset=gca_dataset.Dataset(
                translation_dataset_metadata=translation.TranslationDatasetMetadata(
                    source_language_code="source_language_code_value"
                )
            ),
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = gca_dataset.Dataset.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.create_dataset(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{parent=projects/*/locations/*}/datasets"
            % client.transport._host,
            args[1],
        )


def test_create_dataset_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.create_dataset(
            service.CreateDatasetRequest(),
            parent="parent_value",
            dataset=gca_dataset.Dataset(
                translation_dataset_metadata=translation.TranslationDatasetMetadata(
                    source_language_code="source_language_code_value"
                )
            ),
        )


def test_create_dataset_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.GetDatasetRequest,
        dict,
    ],
)
def test_get_dataset_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/datasets/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = dataset.Dataset(
            name="name_value",
            display_name="display_name_value",
            description="description_value",
            example_count=1396,
            etag="etag_value",
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = dataset.Dataset.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.get_dataset(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, dataset.Dataset)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.description == "description_value"
    assert response.example_count == 1396
    assert response.etag == "etag_value"


def test_get_dataset_rest_required_fields(request_type=service.GetDatasetRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).get_dataset._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).get_dataset._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = dataset.Dataset()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "get",
                "query_params": pb_request,
            }
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = dataset.Dataset.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.get_dataset(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_get_dataset_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.get_dataset._get_unset_required_fields({})
    assert set(unset_fields) == (set(()) & set(("name",)))


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_get_dataset_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_get_dataset"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_get_dataset"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.GetDatasetRequest.pb(service.GetDatasetRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = dataset.Dataset.to_json(dataset.Dataset())

        request = service.GetDatasetRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = dataset.Dataset()

        client.get_dataset(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_get_dataset_rest_bad_request(
    transport: str = "rest", request_type=service.GetDatasetRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/datasets/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.get_dataset(request)


def test_get_dataset_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = dataset.Dataset()

        # get arguments that satisfy an http rule for this method
        sample_request = {"name": "projects/sample1/locations/sample2/datasets/sample3"}

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = dataset.Dataset.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.get_dataset(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/datasets/*}"
            % client.transport._host,
            args[1],
        )


def test_get_dataset_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.get_dataset(
            service.GetDatasetRequest(),
            name="name_value",
        )


def test_get_dataset_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ListDatasetsRequest,
        dict,
    ],
)
def test_list_datasets_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"parent": "projects/sample1/locations/sample2"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = service.ListDatasetsResponse(
            next_page_token="next_page_token_value",
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = service.ListDatasetsResponse.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.list_datasets(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListDatasetsPager)
    assert response.next_page_token == "next_page_token_value"


def test_list_datasets_rest_required_fields(request_type=service.ListDatasetsRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["parent"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).list_datasets._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["parent"] = "parent_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).list_datasets._get_unset_required_fields(jsonified_request)
    # Check that path parameters and body parameters are not mixing in.
    assert not set(unset_fields) - set(
        (
            "filter",
            "page_size",
            "page_token",
        )
    )
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "parent" in jsonified_request
    assert jsonified_request["parent"] == "parent_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = service.ListDatasetsResponse()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "get",
                "query_params": pb_request,
            }
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = service.ListDatasetsResponse.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.list_datasets(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_list_datasets_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.list_datasets._get_unset_required_fields({})
    assert set(unset_fields) == (
        set(
            (
                "filter",
                "pageSize",
                "pageToken",
            )
        )
        & set(("parent",))
    )


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_list_datasets_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_list_datasets"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_list_datasets"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.ListDatasetsRequest.pb(service.ListDatasetsRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = service.ListDatasetsResponse.to_json(
            service.ListDatasetsResponse()
        )

        request = service.ListDatasetsRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = service.ListDatasetsResponse()

        client.list_datasets(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_list_datasets_rest_bad_request(
    transport: str = "rest", request_type=service.ListDatasetsRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"parent": "projects/sample1/locations/sample2"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.list_datasets(request)


def test_list_datasets_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = service.ListDatasetsResponse()

        # get arguments that satisfy an http rule for this method
        sample_request = {"parent": "projects/sample1/locations/sample2"}

        # get truthy value for each flattened field
        mock_args = dict(
            parent="parent_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = service.ListDatasetsResponse.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.list_datasets(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{parent=projects/*/locations/*}/datasets"
            % client.transport._host,
            args[1],
        )


def test_list_datasets_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.list_datasets(
            service.ListDatasetsRequest(),
            parent="parent_value",
        )


def test_list_datasets_rest_pager(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # TODO(kbandes): remove this mock unless there's a good reason for it.
        # with mock.patch.object(path_template, 'transcode') as transcode:
        # Set the response as a series of pages
        response = (
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                    dataset.Dataset(),
                    dataset.Dataset(),
                ],
                next_page_token="abc",
            ),
            service.ListDatasetsResponse(
                datasets=[],
                next_page_token="def",
            ),
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                ],
                next_page_token="ghi",
            ),
            service.ListDatasetsResponse(
                datasets=[
                    dataset.Dataset(),
                    dataset.Dataset(),
                ],
            ),
        )
        # Two responses for two calls
        response = response + response

        # Wrap the values into proper Response objs
        response = tuple(service.ListDatasetsResponse.to_json(x) for x in response)
        return_values = tuple(Response() for i in response)
        for return_val, response_val in zip(return_values, response):
            return_val._content = response_val.encode("UTF-8")
            return_val.status_code = 200
        req.side_effect = return_values

        sample_request = {"parent": "projects/sample1/locations/sample2"}

        pager = client.list_datasets(request=sample_request)

        results = list(pager)
        assert len(results) == 6
        assert all(isinstance(i, dataset.Dataset) for i in results)

        pages = list(client.list_datasets(request=sample_request).pages)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.parametrize(
    "request_type",
    [
        service.UpdateDatasetRequest,
        dict,
    ],
)
def test_update_dataset_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {
        "dataset": {"name": "projects/sample1/locations/sample2/datasets/sample3"}
    }
    request_init["dataset"] = {
        "translation_dataset_metadata": {
            "source_language_code": "source_language_code_value",
            "target_language_code": "target_language_code_value",
        },
        "image_classification_dataset_metadata": {"classification_type": 1},
        "text_classification_dataset_metadata": {"classification_type": 1},
        "image_object_detection_dataset_metadata": {},
        "video_classification_dataset_metadata": {},
        "video_object_tracking_dataset_metadata": {},
        "text_extraction_dataset_metadata": {},
        "text_sentiment_dataset_metadata": {"sentiment_max": 1404},
        "tables_dataset_metadata": {
            "primary_table_spec_id": "primary_table_spec_id_value",
            "target_column_spec_id": "target_column_spec_id_value",
            "weight_column_spec_id": "weight_column_spec_id_value",
            "ml_use_column_spec_id": "ml_use_column_spec_id_value",
            "target_column_correlations": {},
            "stats_update_time": {"seconds": 751, "nanos": 543},
        },
        "name": "projects/sample1/locations/sample2/datasets/sample3",
        "display_name": "display_name_value",
        "description": "description_value",
        "example_count": 1396,
        "create_time": {},
        "etag": "etag_value",
    }
    # The version of a generated dependency at test runtime may differ from the version used during generation.
    # Delete any fields which are not present in the current runtime dependency
    # See https://github.com/googleapis/gapic-generator-python/issues/1748

    # Determine if the message type is proto-plus or protobuf
    test_field = service.UpdateDatasetRequest.meta.fields["dataset"]

    def get_message_fields(field):
        # Given a field which is a message (composite type), return a list with
        # all the fields of the message.
        # If the field is not a composite type, return an empty list.
        message_fields = []

        if hasattr(field, "message") and field.message:
            is_field_type_proto_plus_type = not hasattr(field.message, "DESCRIPTOR")

            if is_field_type_proto_plus_type:
                message_fields = field.message.meta.fields.values()
            # Add `# pragma: NO COVER` because there may not be any `*_pb2` field types
            else:  # pragma: NO COVER
                message_fields = field.message.DESCRIPTOR.fields
        return message_fields

    runtime_nested_fields = [
        (field.name, nested_field.name)
        for field in get_message_fields(test_field)
        for nested_field in get_message_fields(field)
    ]

    subfields_not_in_runtime = []

    # For each item in the sample request, create a list of sub fields which are not present at runtime
    # Add `# pragma: NO COVER` because this test code will not run if all subfields are present at runtime
    for field, value in request_init["dataset"].items():  # pragma: NO COVER
        result = None
        is_repeated = False
        # For repeated fields
        if isinstance(value, list) and len(value):
            is_repeated = True
            result = value[0]
        # For fields where the type is another message
        if isinstance(value, dict):
            result = value

        if result and hasattr(result, "keys"):
            for subfield in result.keys():
                if (field, subfield) not in runtime_nested_fields:
                    subfields_not_in_runtime.append(
                        {
                            "field": field,
                            "subfield": subfield,
                            "is_repeated": is_repeated,
                        }
                    )

    # Remove fields from the sample request which are not present in the runtime version of the dependency
    # Add `# pragma: NO COVER` because this test code will not run if all subfields are present at runtime
    for subfield_to_delete in subfields_not_in_runtime:  # pragma: NO COVER
        field = subfield_to_delete.get("field")
        field_repeated = subfield_to_delete.get("is_repeated")
        subfield = subfield_to_delete.get("subfield")
        if subfield:
            if field_repeated:
                for i in range(0, len(request_init["dataset"][field])):
                    del request_init["dataset"][field][i][subfield]
            else:
                del request_init["dataset"][field][subfield]
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = gca_dataset.Dataset(
            name="name_value",
            display_name="display_name_value",
            description="description_value",
            example_count=1396,
            etag="etag_value",
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = gca_dataset.Dataset.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.update_dataset(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, gca_dataset.Dataset)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.description == "description_value"
    assert response.example_count == 1396
    assert response.etag == "etag_value"


def test_update_dataset_rest_required_fields(request_type=service.UpdateDatasetRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).update_dataset._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).update_dataset._get_unset_required_fields(jsonified_request)
    # Check that path parameters and body parameters are not mixing in.
    assert not set(unset_fields) - set(("update_mask",))
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = gca_dataset.Dataset()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "patch",
                "query_params": pb_request,
            }
            transcode_result["body"] = pb_request
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = gca_dataset.Dataset.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.update_dataset(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_update_dataset_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.update_dataset._get_unset_required_fields({})
    assert set(unset_fields) == (set(("updateMask",)) & set(("dataset",)))


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_update_dataset_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_update_dataset"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_update_dataset"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.UpdateDatasetRequest.pb(service.UpdateDatasetRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = gca_dataset.Dataset.to_json(gca_dataset.Dataset())

        request = service.UpdateDatasetRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = gca_dataset.Dataset()

        client.update_dataset(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_update_dataset_rest_bad_request(
    transport: str = "rest", request_type=service.UpdateDatasetRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {
        "dataset": {"name": "projects/sample1/locations/sample2/datasets/sample3"}
    }
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.update_dataset(request)


def test_update_dataset_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = gca_dataset.Dataset()

        # get arguments that satisfy an http rule for this method
        sample_request = {
            "dataset": {"name": "projects/sample1/locations/sample2/datasets/sample3"}
        }

        # get truthy value for each flattened field
        mock_args = dict(
            dataset=gca_dataset.Dataset(
                translation_dataset_metadata=translation.TranslationDatasetMetadata(
                    source_language_code="source_language_code_value"
                )
            ),
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = gca_dataset.Dataset.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.update_dataset(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{dataset.name=projects/*/locations/*/datasets/*}"
            % client.transport._host,
            args[1],
        )


def test_update_dataset_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.update_dataset(
            service.UpdateDatasetRequest(),
            dataset=gca_dataset.Dataset(
                translation_dataset_metadata=translation.TranslationDatasetMetadata(
                    source_language_code="source_language_code_value"
                )
            ),
        )


def test_update_dataset_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.DeleteDatasetRequest,
        dict,
    ],
)
def test_delete_dataset_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/datasets/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.delete_dataset(request)

    # Establish that the response is the type that we expect.
    assert response.operation.name == "operations/spam"


def test_delete_dataset_rest_required_fields(request_type=service.DeleteDatasetRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).delete_dataset._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).delete_dataset._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = operations_pb2.Operation(name="operations/spam")
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "delete",
                "query_params": pb_request,
            }
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.delete_dataset(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_delete_dataset_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.delete_dataset._get_unset_required_fields({})
    assert set(unset_fields) == (set(()) & set(("name",)))


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_delete_dataset_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        operation.Operation, "_set_result_from_operation"
    ), mock.patch.object(
        transports.AutoMlRestInterceptor, "post_delete_dataset"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_delete_dataset"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.DeleteDatasetRequest.pb(service.DeleteDatasetRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = json_format.MessageToJson(
            operations_pb2.Operation()
        )

        request = service.DeleteDatasetRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = operations_pb2.Operation()

        client.delete_dataset(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_delete_dataset_rest_bad_request(
    transport: str = "rest", request_type=service.DeleteDatasetRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/datasets/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.delete_dataset(request)


def test_delete_dataset_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # get arguments that satisfy an http rule for this method
        sample_request = {"name": "projects/sample1/locations/sample2/datasets/sample3"}

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.delete_dataset(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/datasets/*}"
            % client.transport._host,
            args[1],
        )


def test_delete_dataset_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.delete_dataset(
            service.DeleteDatasetRequest(),
            name="name_value",
        )


def test_delete_dataset_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ImportDataRequest,
        dict,
    ],
)
def test_import_data_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/datasets/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.import_data(request)

    # Establish that the response is the type that we expect.
    assert response.operation.name == "operations/spam"


def test_import_data_rest_required_fields(request_type=service.ImportDataRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).import_data._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).import_data._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = operations_pb2.Operation(name="operations/spam")
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "post",
                "query_params": pb_request,
            }
            transcode_result["body"] = pb_request
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.import_data(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_import_data_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.import_data._get_unset_required_fields({})
    assert set(unset_fields) == (
        set(())
        & set(
            (
                "name",
                "inputConfig",
            )
        )
    )


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_import_data_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        operation.Operation, "_set_result_from_operation"
    ), mock.patch.object(
        transports.AutoMlRestInterceptor, "post_import_data"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_import_data"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.ImportDataRequest.pb(service.ImportDataRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = json_format.MessageToJson(
            operations_pb2.Operation()
        )

        request = service.ImportDataRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = operations_pb2.Operation()

        client.import_data(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_import_data_rest_bad_request(
    transport: str = "rest", request_type=service.ImportDataRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/datasets/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.import_data(request)


def test_import_data_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # get arguments that satisfy an http rule for this method
        sample_request = {"name": "projects/sample1/locations/sample2/datasets/sample3"}

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
            input_config=io.InputConfig(
                gcs_source=io.GcsSource(input_uris=["input_uris_value"])
            ),
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.import_data(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/datasets/*}:importData"
            % client.transport._host,
            args[1],
        )


def test_import_data_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.import_data(
            service.ImportDataRequest(),
            name="name_value",
            input_config=io.InputConfig(
                gcs_source=io.GcsSource(input_uris=["input_uris_value"])
            ),
        )


def test_import_data_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ExportDataRequest,
        dict,
    ],
)
def test_export_data_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/datasets/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.export_data(request)

    # Establish that the response is the type that we expect.
    assert response.operation.name == "operations/spam"


def test_export_data_rest_required_fields(request_type=service.ExportDataRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).export_data._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).export_data._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = operations_pb2.Operation(name="operations/spam")
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "post",
                "query_params": pb_request,
            }
            transcode_result["body"] = pb_request
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.export_data(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_export_data_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.export_data._get_unset_required_fields({})
    assert set(unset_fields) == (
        set(())
        & set(
            (
                "name",
                "outputConfig",
            )
        )
    )


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_export_data_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        operation.Operation, "_set_result_from_operation"
    ), mock.patch.object(
        transports.AutoMlRestInterceptor, "post_export_data"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_export_data"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.ExportDataRequest.pb(service.ExportDataRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = json_format.MessageToJson(
            operations_pb2.Operation()
        )

        request = service.ExportDataRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = operations_pb2.Operation()

        client.export_data(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_export_data_rest_bad_request(
    transport: str = "rest", request_type=service.ExportDataRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/datasets/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.export_data(request)


def test_export_data_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # get arguments that satisfy an http rule for this method
        sample_request = {"name": "projects/sample1/locations/sample2/datasets/sample3"}

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
            output_config=io.OutputConfig(
                gcs_destination=io.GcsDestination(
                    output_uri_prefix="output_uri_prefix_value"
                )
            ),
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.export_data(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/datasets/*}:exportData"
            % client.transport._host,
            args[1],
        )


def test_export_data_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.export_data(
            service.ExportDataRequest(),
            name="name_value",
            output_config=io.OutputConfig(
                gcs_destination=io.GcsDestination(
                    output_uri_prefix="output_uri_prefix_value"
                )
            ),
        )


def test_export_data_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.GetAnnotationSpecRequest,
        dict,
    ],
)
def test_get_annotation_spec_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {
        "name": "projects/sample1/locations/sample2/datasets/sample3/annotationSpecs/sample4"
    }
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = annotation_spec.AnnotationSpec(
            name="name_value",
            display_name="display_name_value",
            example_count=1396,
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = annotation_spec.AnnotationSpec.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.get_annotation_spec(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, annotation_spec.AnnotationSpec)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.example_count == 1396


def test_get_annotation_spec_rest_required_fields(
    request_type=service.GetAnnotationSpecRequest,
):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).get_annotation_spec._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).get_annotation_spec._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = annotation_spec.AnnotationSpec()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "get",
                "query_params": pb_request,
            }
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = annotation_spec.AnnotationSpec.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.get_annotation_spec(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_get_annotation_spec_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.get_annotation_spec._get_unset_required_fields({})
    assert set(unset_fields) == (set(()) & set(("name",)))


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_get_annotation_spec_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_get_annotation_spec"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_get_annotation_spec"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.GetAnnotationSpecRequest.pb(
            service.GetAnnotationSpecRequest()
        )
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = annotation_spec.AnnotationSpec.to_json(
            annotation_spec.AnnotationSpec()
        )

        request = service.GetAnnotationSpecRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = annotation_spec.AnnotationSpec()

        client.get_annotation_spec(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_get_annotation_spec_rest_bad_request(
    transport: str = "rest", request_type=service.GetAnnotationSpecRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {
        "name": "projects/sample1/locations/sample2/datasets/sample3/annotationSpecs/sample4"
    }
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.get_annotation_spec(request)


def test_get_annotation_spec_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = annotation_spec.AnnotationSpec()

        # get arguments that satisfy an http rule for this method
        sample_request = {
            "name": "projects/sample1/locations/sample2/datasets/sample3/annotationSpecs/sample4"
        }

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = annotation_spec.AnnotationSpec.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.get_annotation_spec(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/datasets/*/annotationSpecs/*}"
            % client.transport._host,
            args[1],
        )


def test_get_annotation_spec_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.get_annotation_spec(
            service.GetAnnotationSpecRequest(),
            name="name_value",
        )


def test_get_annotation_spec_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.GetTableSpecRequest,
        dict,
    ],
)
def test_get_table_spec_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {
        "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4"
    }
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = table_spec.TableSpec(
            name="name_value",
            time_column_spec_id="time_column_spec_id_value",
            row_count=992,
            valid_row_count=1615,
            column_count=1302,
            etag="etag_value",
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = table_spec.TableSpec.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.get_table_spec(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, table_spec.TableSpec)
    assert response.name == "name_value"
    assert response.time_column_spec_id == "time_column_spec_id_value"
    assert response.row_count == 992
    assert response.valid_row_count == 1615
    assert response.column_count == 1302
    assert response.etag == "etag_value"


def test_get_table_spec_rest_required_fields(request_type=service.GetTableSpecRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).get_table_spec._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).get_table_spec._get_unset_required_fields(jsonified_request)
    # Check that path parameters and body parameters are not mixing in.
    assert not set(unset_fields) - set(("field_mask",))
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = table_spec.TableSpec()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "get",
                "query_params": pb_request,
            }
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = table_spec.TableSpec.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.get_table_spec(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_get_table_spec_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.get_table_spec._get_unset_required_fields({})
    assert set(unset_fields) == (set(("fieldMask",)) & set(("name",)))


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_get_table_spec_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_get_table_spec"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_get_table_spec"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.GetTableSpecRequest.pb(service.GetTableSpecRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = table_spec.TableSpec.to_json(table_spec.TableSpec())

        request = service.GetTableSpecRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = table_spec.TableSpec()

        client.get_table_spec(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_get_table_spec_rest_bad_request(
    transport: str = "rest", request_type=service.GetTableSpecRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {
        "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4"
    }
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.get_table_spec(request)


def test_get_table_spec_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = table_spec.TableSpec()

        # get arguments that satisfy an http rule for this method
        sample_request = {
            "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4"
        }

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = table_spec.TableSpec.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.get_table_spec(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/datasets/*/tableSpecs/*}"
            % client.transport._host,
            args[1],
        )


def test_get_table_spec_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.get_table_spec(
            service.GetTableSpecRequest(),
            name="name_value",
        )


def test_get_table_spec_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ListTableSpecsRequest,
        dict,
    ],
)
def test_list_table_specs_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"parent": "projects/sample1/locations/sample2/datasets/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = service.ListTableSpecsResponse(
            next_page_token="next_page_token_value",
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = service.ListTableSpecsResponse.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.list_table_specs(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListTableSpecsPager)
    assert response.next_page_token == "next_page_token_value"


def test_list_table_specs_rest_required_fields(
    request_type=service.ListTableSpecsRequest,
):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["parent"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).list_table_specs._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["parent"] = "parent_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).list_table_specs._get_unset_required_fields(jsonified_request)
    # Check that path parameters and body parameters are not mixing in.
    assert not set(unset_fields) - set(
        (
            "field_mask",
            "filter",
            "page_size",
            "page_token",
        )
    )
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "parent" in jsonified_request
    assert jsonified_request["parent"] == "parent_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = service.ListTableSpecsResponse()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "get",
                "query_params": pb_request,
            }
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = service.ListTableSpecsResponse.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.list_table_specs(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_list_table_specs_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.list_table_specs._get_unset_required_fields({})
    assert set(unset_fields) == (
        set(
            (
                "fieldMask",
                "filter",
                "pageSize",
                "pageToken",
            )
        )
        & set(("parent",))
    )


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_list_table_specs_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_list_table_specs"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_list_table_specs"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.ListTableSpecsRequest.pb(service.ListTableSpecsRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = service.ListTableSpecsResponse.to_json(
            service.ListTableSpecsResponse()
        )

        request = service.ListTableSpecsRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = service.ListTableSpecsResponse()

        client.list_table_specs(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_list_table_specs_rest_bad_request(
    transport: str = "rest", request_type=service.ListTableSpecsRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"parent": "projects/sample1/locations/sample2/datasets/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.list_table_specs(request)


def test_list_table_specs_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = service.ListTableSpecsResponse()

        # get arguments that satisfy an http rule for this method
        sample_request = {
            "parent": "projects/sample1/locations/sample2/datasets/sample3"
        }

        # get truthy value for each flattened field
        mock_args = dict(
            parent="parent_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = service.ListTableSpecsResponse.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.list_table_specs(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{parent=projects/*/locations/*/datasets/*}/tableSpecs"
            % client.transport._host,
            args[1],
        )


def test_list_table_specs_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.list_table_specs(
            service.ListTableSpecsRequest(),
            parent="parent_value",
        )


def test_list_table_specs_rest_pager(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # TODO(kbandes): remove this mock unless there's a good reason for it.
        # with mock.patch.object(path_template, 'transcode') as transcode:
        # Set the response as a series of pages
        response = (
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                ],
                next_page_token="abc",
            ),
            service.ListTableSpecsResponse(
                table_specs=[],
                next_page_token="def",
            ),
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                ],
                next_page_token="ghi",
            ),
            service.ListTableSpecsResponse(
                table_specs=[
                    table_spec.TableSpec(),
                    table_spec.TableSpec(),
                ],
            ),
        )
        # Two responses for two calls
        response = response + response

        # Wrap the values into proper Response objs
        response = tuple(service.ListTableSpecsResponse.to_json(x) for x in response)
        return_values = tuple(Response() for i in response)
        for return_val, response_val in zip(return_values, response):
            return_val._content = response_val.encode("UTF-8")
            return_val.status_code = 200
        req.side_effect = return_values

        sample_request = {
            "parent": "projects/sample1/locations/sample2/datasets/sample3"
        }

        pager = client.list_table_specs(request=sample_request)

        results = list(pager)
        assert len(results) == 6
        assert all(isinstance(i, table_spec.TableSpec) for i in results)

        pages = list(client.list_table_specs(request=sample_request).pages)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.parametrize(
    "request_type",
    [
        service.UpdateTableSpecRequest,
        dict,
    ],
)
def test_update_table_spec_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {
        "table_spec": {
            "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4"
        }
    }
    request_init["table_spec"] = {
        "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4",
        "time_column_spec_id": "time_column_spec_id_value",
        "row_count": 992,
        "valid_row_count": 1615,
        "column_count": 1302,
        "input_configs": [
            {
                "gcs_source": {
                    "input_uris": ["input_uris_value1", "input_uris_value2"]
                },
                "bigquery_source": {"input_uri": "input_uri_value"},
                "params": {},
            }
        ],
        "etag": "etag_value",
    }
    # The version of a generated dependency at test runtime may differ from the version used during generation.
    # Delete any fields which are not present in the current runtime dependency
    # See https://github.com/googleapis/gapic-generator-python/issues/1748

    # Determine if the message type is proto-plus or protobuf
    test_field = service.UpdateTableSpecRequest.meta.fields["table_spec"]

    def get_message_fields(field):
        # Given a field which is a message (composite type), return a list with
        # all the fields of the message.
        # If the field is not a composite type, return an empty list.
        message_fields = []

        if hasattr(field, "message") and field.message:
            is_field_type_proto_plus_type = not hasattr(field.message, "DESCRIPTOR")

            if is_field_type_proto_plus_type:
                message_fields = field.message.meta.fields.values()
            # Add `# pragma: NO COVER` because there may not be any `*_pb2` field types
            else:  # pragma: NO COVER
                message_fields = field.message.DESCRIPTOR.fields
        return message_fields

    runtime_nested_fields = [
        (field.name, nested_field.name)
        for field in get_message_fields(test_field)
        for nested_field in get_message_fields(field)
    ]

    subfields_not_in_runtime = []

    # For each item in the sample request, create a list of sub fields which are not present at runtime
    # Add `# pragma: NO COVER` because this test code will not run if all subfields are present at runtime
    for field, value in request_init["table_spec"].items():  # pragma: NO COVER
        result = None
        is_repeated = False
        # For repeated fields
        if isinstance(value, list) and len(value):
            is_repeated = True
            result = value[0]
        # For fields where the type is another message
        if isinstance(value, dict):
            result = value

        if result and hasattr(result, "keys"):
            for subfield in result.keys():
                if (field, subfield) not in runtime_nested_fields:
                    subfields_not_in_runtime.append(
                        {
                            "field": field,
                            "subfield": subfield,
                            "is_repeated": is_repeated,
                        }
                    )

    # Remove fields from the sample request which are not present in the runtime version of the dependency
    # Add `# pragma: NO COVER` because this test code will not run if all subfields are present at runtime
    for subfield_to_delete in subfields_not_in_runtime:  # pragma: NO COVER
        field = subfield_to_delete.get("field")
        field_repeated = subfield_to_delete.get("is_repeated")
        subfield = subfield_to_delete.get("subfield")
        if subfield:
            if field_repeated:
                for i in range(0, len(request_init["table_spec"][field])):
                    del request_init["table_spec"][field][i][subfield]
            else:
                del request_init["table_spec"][field][subfield]
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = gca_table_spec.TableSpec(
            name="name_value",
            time_column_spec_id="time_column_spec_id_value",
            row_count=992,
            valid_row_count=1615,
            column_count=1302,
            etag="etag_value",
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = gca_table_spec.TableSpec.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.update_table_spec(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, gca_table_spec.TableSpec)
    assert response.name == "name_value"
    assert response.time_column_spec_id == "time_column_spec_id_value"
    assert response.row_count == 992
    assert response.valid_row_count == 1615
    assert response.column_count == 1302
    assert response.etag == "etag_value"


def test_update_table_spec_rest_required_fields(
    request_type=service.UpdateTableSpecRequest,
):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).update_table_spec._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).update_table_spec._get_unset_required_fields(jsonified_request)
    # Check that path parameters and body parameters are not mixing in.
    assert not set(unset_fields) - set(("update_mask",))
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = gca_table_spec.TableSpec()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "patch",
                "query_params": pb_request,
            }
            transcode_result["body"] = pb_request
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = gca_table_spec.TableSpec.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.update_table_spec(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_update_table_spec_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.update_table_spec._get_unset_required_fields({})
    assert set(unset_fields) == (set(("updateMask",)) & set(("tableSpec",)))


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_update_table_spec_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_update_table_spec"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_update_table_spec"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.UpdateTableSpecRequest.pb(service.UpdateTableSpecRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = gca_table_spec.TableSpec.to_json(
            gca_table_spec.TableSpec()
        )

        request = service.UpdateTableSpecRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = gca_table_spec.TableSpec()

        client.update_table_spec(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_update_table_spec_rest_bad_request(
    transport: str = "rest", request_type=service.UpdateTableSpecRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {
        "table_spec": {
            "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4"
        }
    }
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.update_table_spec(request)


def test_update_table_spec_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = gca_table_spec.TableSpec()

        # get arguments that satisfy an http rule for this method
        sample_request = {
            "table_spec": {
                "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4"
            }
        }

        # get truthy value for each flattened field
        mock_args = dict(
            table_spec=gca_table_spec.TableSpec(name="name_value"),
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = gca_table_spec.TableSpec.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.update_table_spec(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{table_spec.name=projects/*/locations/*/datasets/*/tableSpecs/*}"
            % client.transport._host,
            args[1],
        )


def test_update_table_spec_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.update_table_spec(
            service.UpdateTableSpecRequest(),
            table_spec=gca_table_spec.TableSpec(name="name_value"),
        )


def test_update_table_spec_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.GetColumnSpecRequest,
        dict,
    ],
)
def test_get_column_spec_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {
        "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4/columnSpecs/sample5"
    }
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = column_spec.ColumnSpec(
            name="name_value",
            display_name="display_name_value",
            etag="etag_value",
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = column_spec.ColumnSpec.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.get_column_spec(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, column_spec.ColumnSpec)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.etag == "etag_value"


def test_get_column_spec_rest_required_fields(
    request_type=service.GetColumnSpecRequest,
):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).get_column_spec._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).get_column_spec._get_unset_required_fields(jsonified_request)
    # Check that path parameters and body parameters are not mixing in.
    assert not set(unset_fields) - set(("field_mask",))
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = column_spec.ColumnSpec()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "get",
                "query_params": pb_request,
            }
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = column_spec.ColumnSpec.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.get_column_spec(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_get_column_spec_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.get_column_spec._get_unset_required_fields({})
    assert set(unset_fields) == (set(("fieldMask",)) & set(("name",)))


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_get_column_spec_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_get_column_spec"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_get_column_spec"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.GetColumnSpecRequest.pb(service.GetColumnSpecRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = column_spec.ColumnSpec.to_json(
            column_spec.ColumnSpec()
        )

        request = service.GetColumnSpecRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = column_spec.ColumnSpec()

        client.get_column_spec(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_get_column_spec_rest_bad_request(
    transport: str = "rest", request_type=service.GetColumnSpecRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {
        "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4/columnSpecs/sample5"
    }
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.get_column_spec(request)


def test_get_column_spec_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = column_spec.ColumnSpec()

        # get arguments that satisfy an http rule for this method
        sample_request = {
            "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4/columnSpecs/sample5"
        }

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = column_spec.ColumnSpec.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.get_column_spec(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/datasets/*/tableSpecs/*/columnSpecs/*}"
            % client.transport._host,
            args[1],
        )


def test_get_column_spec_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.get_column_spec(
            service.GetColumnSpecRequest(),
            name="name_value",
        )


def test_get_column_spec_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ListColumnSpecsRequest,
        dict,
    ],
)
def test_list_column_specs_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {
        "parent": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4"
    }
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = service.ListColumnSpecsResponse(
            next_page_token="next_page_token_value",
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = service.ListColumnSpecsResponse.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.list_column_specs(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListColumnSpecsPager)
    assert response.next_page_token == "next_page_token_value"


def test_list_column_specs_rest_required_fields(
    request_type=service.ListColumnSpecsRequest,
):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["parent"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).list_column_specs._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["parent"] = "parent_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).list_column_specs._get_unset_required_fields(jsonified_request)
    # Check that path parameters and body parameters are not mixing in.
    assert not set(unset_fields) - set(
        (
            "field_mask",
            "filter",
            "page_size",
            "page_token",
        )
    )
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "parent" in jsonified_request
    assert jsonified_request["parent"] == "parent_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = service.ListColumnSpecsResponse()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "get",
                "query_params": pb_request,
            }
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = service.ListColumnSpecsResponse.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.list_column_specs(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_list_column_specs_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.list_column_specs._get_unset_required_fields({})
    assert set(unset_fields) == (
        set(
            (
                "fieldMask",
                "filter",
                "pageSize",
                "pageToken",
            )
        )
        & set(("parent",))
    )


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_list_column_specs_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_list_column_specs"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_list_column_specs"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.ListColumnSpecsRequest.pb(service.ListColumnSpecsRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = service.ListColumnSpecsResponse.to_json(
            service.ListColumnSpecsResponse()
        )

        request = service.ListColumnSpecsRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = service.ListColumnSpecsResponse()

        client.list_column_specs(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_list_column_specs_rest_bad_request(
    transport: str = "rest", request_type=service.ListColumnSpecsRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {
        "parent": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4"
    }
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.list_column_specs(request)


def test_list_column_specs_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = service.ListColumnSpecsResponse()

        # get arguments that satisfy an http rule for this method
        sample_request = {
            "parent": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4"
        }

        # get truthy value for each flattened field
        mock_args = dict(
            parent="parent_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = service.ListColumnSpecsResponse.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.list_column_specs(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{parent=projects/*/locations/*/datasets/*/tableSpecs/*}/columnSpecs"
            % client.transport._host,
            args[1],
        )


def test_list_column_specs_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.list_column_specs(
            service.ListColumnSpecsRequest(),
            parent="parent_value",
        )


def test_list_column_specs_rest_pager(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # TODO(kbandes): remove this mock unless there's a good reason for it.
        # with mock.patch.object(path_template, 'transcode') as transcode:
        # Set the response as a series of pages
        response = (
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                ],
                next_page_token="abc",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[],
                next_page_token="def",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                ],
                next_page_token="ghi",
            ),
            service.ListColumnSpecsResponse(
                column_specs=[
                    column_spec.ColumnSpec(),
                    column_spec.ColumnSpec(),
                ],
            ),
        )
        # Two responses for two calls
        response = response + response

        # Wrap the values into proper Response objs
        response = tuple(service.ListColumnSpecsResponse.to_json(x) for x in response)
        return_values = tuple(Response() for i in response)
        for return_val, response_val in zip(return_values, response):
            return_val._content = response_val.encode("UTF-8")
            return_val.status_code = 200
        req.side_effect = return_values

        sample_request = {
            "parent": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4"
        }

        pager = client.list_column_specs(request=sample_request)

        results = list(pager)
        assert len(results) == 6
        assert all(isinstance(i, column_spec.ColumnSpec) for i in results)

        pages = list(client.list_column_specs(request=sample_request).pages)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.parametrize(
    "request_type",
    [
        service.UpdateColumnSpecRequest,
        dict,
    ],
)
def test_update_column_spec_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {
        "column_spec": {
            "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4/columnSpecs/sample5"
        }
    }
    request_init["column_spec"] = {
        "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4/columnSpecs/sample5",
        "data_type": {
            "list_element_type": {},
            "struct_type": {"fields": {}},
            "time_format": "time_format_value",
            "type_code": 3,
            "nullable": True,
        },
        "display_name": "display_name_value",
        "data_stats": {
            "float64_stats": {
                "mean": 0.417,
                "standard_deviation": 0.1907,
                "quantiles": [0.983, 0.984],
                "histogram_buckets": [{"min_": 0.419, "max_": 0.421, "count": 553}],
            },
            "string_stats": {
                "top_unigram_stats": [{"value": "value_value", "count": 553}]
            },
            "timestamp_stats": {"granular_stats": {}},
            "array_stats": {"member_stats": {}},
            "struct_stats": {"field_stats": {}},
            "category_stats": {
                "top_category_stats": [{"value": "value_value", "count": 553}]
            },
            "distinct_value_count": 2150,
            "null_value_count": 1727,
            "valid_value_count": 1812,
        },
        "top_correlated_columns": [
            {
                "column_spec_id": "column_spec_id_value",
                "correlation_stats": {"cramers_v": 0.962},
            }
        ],
        "etag": "etag_value",
    }
    # The version of a generated dependency at test runtime may differ from the version used during generation.
    # Delete any fields which are not present in the current runtime dependency
    # See https://github.com/googleapis/gapic-generator-python/issues/1748

    # Determine if the message type is proto-plus or protobuf
    test_field = service.UpdateColumnSpecRequest.meta.fields["column_spec"]

    def get_message_fields(field):
        # Given a field which is a message (composite type), return a list with
        # all the fields of the message.
        # If the field is not a composite type, return an empty list.
        message_fields = []

        if hasattr(field, "message") and field.message:
            is_field_type_proto_plus_type = not hasattr(field.message, "DESCRIPTOR")

            if is_field_type_proto_plus_type:
                message_fields = field.message.meta.fields.values()
            # Add `# pragma: NO COVER` because there may not be any `*_pb2` field types
            else:  # pragma: NO COVER
                message_fields = field.message.DESCRIPTOR.fields
        return message_fields

    runtime_nested_fields = [
        (field.name, nested_field.name)
        for field in get_message_fields(test_field)
        for nested_field in get_message_fields(field)
    ]

    subfields_not_in_runtime = []

    # For each item in the sample request, create a list of sub fields which are not present at runtime
    # Add `# pragma: NO COVER` because this test code will not run if all subfields are present at runtime
    for field, value in request_init["column_spec"].items():  # pragma: NO COVER
        result = None
        is_repeated = False
        # For repeated fields
        if isinstance(value, list) and len(value):
            is_repeated = True
            result = value[0]
        # For fields where the type is another message
        if isinstance(value, dict):
            result = value

        if result and hasattr(result, "keys"):
            for subfield in result.keys():
                if (field, subfield) not in runtime_nested_fields:
                    subfields_not_in_runtime.append(
                        {
                            "field": field,
                            "subfield": subfield,
                            "is_repeated": is_repeated,
                        }
                    )

    # Remove fields from the sample request which are not present in the runtime version of the dependency
    # Add `# pragma: NO COVER` because this test code will not run if all subfields are present at runtime
    for subfield_to_delete in subfields_not_in_runtime:  # pragma: NO COVER
        field = subfield_to_delete.get("field")
        field_repeated = subfield_to_delete.get("is_repeated")
        subfield = subfield_to_delete.get("subfield")
        if subfield:
            if field_repeated:
                for i in range(0, len(request_init["column_spec"][field])):
                    del request_init["column_spec"][field][i][subfield]
            else:
                del request_init["column_spec"][field][subfield]
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = gca_column_spec.ColumnSpec(
            name="name_value",
            display_name="display_name_value",
            etag="etag_value",
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = gca_column_spec.ColumnSpec.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.update_column_spec(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, gca_column_spec.ColumnSpec)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.etag == "etag_value"


def test_update_column_spec_rest_required_fields(
    request_type=service.UpdateColumnSpecRequest,
):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).update_column_spec._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).update_column_spec._get_unset_required_fields(jsonified_request)
    # Check that path parameters and body parameters are not mixing in.
    assert not set(unset_fields) - set(("update_mask",))
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = gca_column_spec.ColumnSpec()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "patch",
                "query_params": pb_request,
            }
            transcode_result["body"] = pb_request
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = gca_column_spec.ColumnSpec.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.update_column_spec(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_update_column_spec_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.update_column_spec._get_unset_required_fields({})
    assert set(unset_fields) == (set(("updateMask",)) & set(("columnSpec",)))


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_update_column_spec_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_update_column_spec"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_update_column_spec"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.UpdateColumnSpecRequest.pb(
            service.UpdateColumnSpecRequest()
        )
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = gca_column_spec.ColumnSpec.to_json(
            gca_column_spec.ColumnSpec()
        )

        request = service.UpdateColumnSpecRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = gca_column_spec.ColumnSpec()

        client.update_column_spec(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_update_column_spec_rest_bad_request(
    transport: str = "rest", request_type=service.UpdateColumnSpecRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {
        "column_spec": {
            "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4/columnSpecs/sample5"
        }
    }
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.update_column_spec(request)


def test_update_column_spec_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = gca_column_spec.ColumnSpec()

        # get arguments that satisfy an http rule for this method
        sample_request = {
            "column_spec": {
                "name": "projects/sample1/locations/sample2/datasets/sample3/tableSpecs/sample4/columnSpecs/sample5"
            }
        }

        # get truthy value for each flattened field
        mock_args = dict(
            column_spec=gca_column_spec.ColumnSpec(name="name_value"),
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = gca_column_spec.ColumnSpec.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.update_column_spec(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{column_spec.name=projects/*/locations/*/datasets/*/tableSpecs/*/columnSpecs/*}"
            % client.transport._host,
            args[1],
        )


def test_update_column_spec_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.update_column_spec(
            service.UpdateColumnSpecRequest(),
            column_spec=gca_column_spec.ColumnSpec(name="name_value"),
        )


def test_update_column_spec_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.CreateModelRequest,
        dict,
    ],
)
def test_create_model_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"parent": "projects/sample1/locations/sample2"}
    request_init["model"] = {
        "translation_model_metadata": {
            "base_model": "base_model_value",
            "source_language_code": "source_language_code_value",
            "target_language_code": "target_language_code_value",
        },
        "image_classification_model_metadata": {
            "base_model_id": "base_model_id_value",
            "train_budget": 1272,
            "train_cost": 1078,
            "stop_reason": "stop_reason_value",
            "model_type": "model_type_value",
            "node_qps": 0.857,
            "node_count": 1070,
        },
        "text_classification_model_metadata": {"classification_type": 1},
        "image_object_detection_model_metadata": {
            "model_type": "model_type_value",
            "node_count": 1070,
            "node_qps": 0.857,
            "stop_reason": "stop_reason_value",
            "train_budget_milli_node_hours": 3075,
            "train_cost_milli_node_hours": 2881,
        },
        "video_classification_model_metadata": {},
        "video_object_tracking_model_metadata": {},
        "text_extraction_model_metadata": {"model_hint": "model_hint_value"},
        "tables_model_metadata": {
            "optimization_objective_recall_value": 0.37270000000000003,
            "optimization_objective_precision_value": 0.4072,
            "target_column_spec": {
                "name": "name_value",
                "data_type": {
                    "list_element_type": {},
                    "struct_type": {"fields": {}},
                    "time_format": "time_format_value",
                    "type_code": 3,
                    "nullable": True,
                },
                "display_name": "display_name_value",
                "data_stats": {
                    "float64_stats": {
                        "mean": 0.417,
                        "standard_deviation": 0.1907,
                        "quantiles": [0.983, 0.984],
                        "histogram_buckets": [
                            {"min_": 0.419, "max_": 0.421, "count": 553}
                        ],
                    },
                    "string_stats": {
                        "top_unigram_stats": [{"value": "value_value", "count": 553}]
                    },
                    "timestamp_stats": {"granular_stats": {}},
                    "array_stats": {"member_stats": {}},
                    "struct_stats": {"field_stats": {}},
                    "category_stats": {
                        "top_category_stats": [{"value": "value_value", "count": 553}]
                    },
                    "distinct_value_count": 2150,
                    "null_value_count": 1727,
                    "valid_value_count": 1812,
                },
                "top_correlated_columns": [
                    {
                        "column_spec_id": "column_spec_id_value",
                        "correlation_stats": {"cramers_v": 0.962},
                    }
                ],
                "etag": "etag_value",
            },
            "input_feature_column_specs": {},
            "optimization_objective": "optimization_objective_value",
            "tables_model_column_info": [
                {
                    "column_spec_name": "column_spec_name_value",
                    "column_display_name": "column_display_name_value",
                    "feature_importance": 0.1917,
                }
            ],
            "train_budget_milli_node_hours": 3075,
            "train_cost_milli_node_hours": 2881,
            "disable_early_stopping": True,
        },
        "text_sentiment_model_metadata": {},
        "name": "name_value",
        "display_name": "display_name_value",
        "dataset_id": "dataset_id_value",
        "create_time": {"seconds": 751, "nanos": 543},
        "update_time": {},
        "deployment_state": 1,
    }
    # The version of a generated dependency at test runtime may differ from the version used during generation.
    # Delete any fields which are not present in the current runtime dependency
    # See https://github.com/googleapis/gapic-generator-python/issues/1748

    # Determine if the message type is proto-plus or protobuf
    test_field = service.CreateModelRequest.meta.fields["model"]

    def get_message_fields(field):
        # Given a field which is a message (composite type), return a list with
        # all the fields of the message.
        # If the field is not a composite type, return an empty list.
        message_fields = []

        if hasattr(field, "message") and field.message:
            is_field_type_proto_plus_type = not hasattr(field.message, "DESCRIPTOR")

            if is_field_type_proto_plus_type:
                message_fields = field.message.meta.fields.values()
            # Add `# pragma: NO COVER` because there may not be any `*_pb2` field types
            else:  # pragma: NO COVER
                message_fields = field.message.DESCRIPTOR.fields
        return message_fields

    runtime_nested_fields = [
        (field.name, nested_field.name)
        for field in get_message_fields(test_field)
        for nested_field in get_message_fields(field)
    ]

    subfields_not_in_runtime = []

    # For each item in the sample request, create a list of sub fields which are not present at runtime
    # Add `# pragma: NO COVER` because this test code will not run if all subfields are present at runtime
    for field, value in request_init["model"].items():  # pragma: NO COVER
        result = None
        is_repeated = False
        # For repeated fields
        if isinstance(value, list) and len(value):
            is_repeated = True
            result = value[0]
        # For fields where the type is another message
        if isinstance(value, dict):
            result = value

        if result and hasattr(result, "keys"):
            for subfield in result.keys():
                if (field, subfield) not in runtime_nested_fields:
                    subfields_not_in_runtime.append(
                        {
                            "field": field,
                            "subfield": subfield,
                            "is_repeated": is_repeated,
                        }
                    )

    # Remove fields from the sample request which are not present in the runtime version of the dependency
    # Add `# pragma: NO COVER` because this test code will not run if all subfields are present at runtime
    for subfield_to_delete in subfields_not_in_runtime:  # pragma: NO COVER
        field = subfield_to_delete.get("field")
        field_repeated = subfield_to_delete.get("is_repeated")
        subfield = subfield_to_delete.get("subfield")
        if subfield:
            if field_repeated:
                for i in range(0, len(request_init["model"][field])):
                    del request_init["model"][field][i][subfield]
            else:
                del request_init["model"][field][subfield]
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.create_model(request)

    # Establish that the response is the type that we expect.
    assert response.operation.name == "operations/spam"


def test_create_model_rest_required_fields(request_type=service.CreateModelRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["parent"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).create_model._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["parent"] = "parent_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).create_model._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "parent" in jsonified_request
    assert jsonified_request["parent"] == "parent_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = operations_pb2.Operation(name="operations/spam")
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "post",
                "query_params": pb_request,
            }
            transcode_result["body"] = pb_request
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.create_model(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_create_model_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.create_model._get_unset_required_fields({})
    assert set(unset_fields) == (
        set(())
        & set(
            (
                "parent",
                "model",
            )
        )
    )


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_create_model_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        operation.Operation, "_set_result_from_operation"
    ), mock.patch.object(
        transports.AutoMlRestInterceptor, "post_create_model"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_create_model"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.CreateModelRequest.pb(service.CreateModelRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = json_format.MessageToJson(
            operations_pb2.Operation()
        )

        request = service.CreateModelRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = operations_pb2.Operation()

        client.create_model(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_create_model_rest_bad_request(
    transport: str = "rest", request_type=service.CreateModelRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"parent": "projects/sample1/locations/sample2"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.create_model(request)


def test_create_model_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # get arguments that satisfy an http rule for this method
        sample_request = {"parent": "projects/sample1/locations/sample2"}

        # get truthy value for each flattened field
        mock_args = dict(
            parent="parent_value",
            model=gca_model.Model(
                translation_model_metadata=translation.TranslationModelMetadata(
                    base_model="base_model_value"
                )
            ),
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.create_model(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{parent=projects/*/locations/*}/models"
            % client.transport._host,
            args[1],
        )


def test_create_model_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.create_model(
            service.CreateModelRequest(),
            parent="parent_value",
            model=gca_model.Model(
                translation_model_metadata=translation.TranslationModelMetadata(
                    base_model="base_model_value"
                )
            ),
        )


def test_create_model_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.GetModelRequest,
        dict,
    ],
)
def test_get_model_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = model.Model(
            name="name_value",
            display_name="display_name_value",
            dataset_id="dataset_id_value",
            deployment_state=model.Model.DeploymentState.DEPLOYED,
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = model.Model.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.get_model(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, model.Model)
    assert response.name == "name_value"
    assert response.display_name == "display_name_value"
    assert response.dataset_id == "dataset_id_value"
    assert response.deployment_state == model.Model.DeploymentState.DEPLOYED


def test_get_model_rest_required_fields(request_type=service.GetModelRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).get_model._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).get_model._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = model.Model()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "get",
                "query_params": pb_request,
            }
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = model.Model.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.get_model(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_get_model_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.get_model._get_unset_required_fields({})
    assert set(unset_fields) == (set(()) & set(("name",)))


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_get_model_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_get_model"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_get_model"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.GetModelRequest.pb(service.GetModelRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = model.Model.to_json(model.Model())

        request = service.GetModelRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = model.Model()

        client.get_model(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_get_model_rest_bad_request(
    transport: str = "rest", request_type=service.GetModelRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.get_model(request)


def test_get_model_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = model.Model()

        # get arguments that satisfy an http rule for this method
        sample_request = {"name": "projects/sample1/locations/sample2/models/sample3"}

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = model.Model.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.get_model(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/models/*}"
            % client.transport._host,
            args[1],
        )


def test_get_model_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.get_model(
            service.GetModelRequest(),
            name="name_value",
        )


def test_get_model_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ListModelsRequest,
        dict,
    ],
)
def test_list_models_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"parent": "projects/sample1/locations/sample2"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = service.ListModelsResponse(
            next_page_token="next_page_token_value",
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = service.ListModelsResponse.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.list_models(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListModelsPager)
    assert response.next_page_token == "next_page_token_value"


def test_list_models_rest_required_fields(request_type=service.ListModelsRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["parent"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).list_models._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["parent"] = "parent_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).list_models._get_unset_required_fields(jsonified_request)
    # Check that path parameters and body parameters are not mixing in.
    assert not set(unset_fields) - set(
        (
            "filter",
            "page_size",
            "page_token",
        )
    )
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "parent" in jsonified_request
    assert jsonified_request["parent"] == "parent_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = service.ListModelsResponse()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "get",
                "query_params": pb_request,
            }
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = service.ListModelsResponse.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.list_models(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_list_models_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.list_models._get_unset_required_fields({})
    assert set(unset_fields) == (
        set(
            (
                "filter",
                "pageSize",
                "pageToken",
            )
        )
        & set(("parent",))
    )


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_list_models_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_list_models"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_list_models"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.ListModelsRequest.pb(service.ListModelsRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = service.ListModelsResponse.to_json(
            service.ListModelsResponse()
        )

        request = service.ListModelsRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = service.ListModelsResponse()

        client.list_models(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_list_models_rest_bad_request(
    transport: str = "rest", request_type=service.ListModelsRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"parent": "projects/sample1/locations/sample2"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.list_models(request)


def test_list_models_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = service.ListModelsResponse()

        # get arguments that satisfy an http rule for this method
        sample_request = {"parent": "projects/sample1/locations/sample2"}

        # get truthy value for each flattened field
        mock_args = dict(
            parent="parent_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = service.ListModelsResponse.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.list_models(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{parent=projects/*/locations/*}/models"
            % client.transport._host,
            args[1],
        )


def test_list_models_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.list_models(
            service.ListModelsRequest(),
            parent="parent_value",
        )


def test_list_models_rest_pager(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # TODO(kbandes): remove this mock unless there's a good reason for it.
        # with mock.patch.object(path_template, 'transcode') as transcode:
        # Set the response as a series of pages
        response = (
            service.ListModelsResponse(
                model=[
                    model.Model(),
                    model.Model(),
                    model.Model(),
                ],
                next_page_token="abc",
            ),
            service.ListModelsResponse(
                model=[],
                next_page_token="def",
            ),
            service.ListModelsResponse(
                model=[
                    model.Model(),
                ],
                next_page_token="ghi",
            ),
            service.ListModelsResponse(
                model=[
                    model.Model(),
                    model.Model(),
                ],
            ),
        )
        # Two responses for two calls
        response = response + response

        # Wrap the values into proper Response objs
        response = tuple(service.ListModelsResponse.to_json(x) for x in response)
        return_values = tuple(Response() for i in response)
        for return_val, response_val in zip(return_values, response):
            return_val._content = response_val.encode("UTF-8")
            return_val.status_code = 200
        req.side_effect = return_values

        sample_request = {"parent": "projects/sample1/locations/sample2"}

        pager = client.list_models(request=sample_request)

        results = list(pager)
        assert len(results) == 6
        assert all(isinstance(i, model.Model) for i in results)

        pages = list(client.list_models(request=sample_request).pages)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


@pytest.mark.parametrize(
    "request_type",
    [
        service.DeleteModelRequest,
        dict,
    ],
)
def test_delete_model_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.delete_model(request)

    # Establish that the response is the type that we expect.
    assert response.operation.name == "operations/spam"


def test_delete_model_rest_required_fields(request_type=service.DeleteModelRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).delete_model._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).delete_model._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = operations_pb2.Operation(name="operations/spam")
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "delete",
                "query_params": pb_request,
            }
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.delete_model(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_delete_model_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.delete_model._get_unset_required_fields({})
    assert set(unset_fields) == (set(()) & set(("name",)))


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_delete_model_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        operation.Operation, "_set_result_from_operation"
    ), mock.patch.object(
        transports.AutoMlRestInterceptor, "post_delete_model"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_delete_model"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.DeleteModelRequest.pb(service.DeleteModelRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = json_format.MessageToJson(
            operations_pb2.Operation()
        )

        request = service.DeleteModelRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = operations_pb2.Operation()

        client.delete_model(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_delete_model_rest_bad_request(
    transport: str = "rest", request_type=service.DeleteModelRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.delete_model(request)


def test_delete_model_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # get arguments that satisfy an http rule for this method
        sample_request = {"name": "projects/sample1/locations/sample2/models/sample3"}

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.delete_model(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/models/*}"
            % client.transport._host,
            args[1],
        )


def test_delete_model_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.delete_model(
            service.DeleteModelRequest(),
            name="name_value",
        )


def test_delete_model_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.DeployModelRequest,
        dict,
    ],
)
def test_deploy_model_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.deploy_model(request)

    # Establish that the response is the type that we expect.
    assert response.operation.name == "operations/spam"


def test_deploy_model_rest_required_fields(request_type=service.DeployModelRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).deploy_model._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).deploy_model._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = operations_pb2.Operation(name="operations/spam")
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "post",
                "query_params": pb_request,
            }
            transcode_result["body"] = pb_request
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.deploy_model(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_deploy_model_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.deploy_model._get_unset_required_fields({})
    assert set(unset_fields) == (set(()) & set(("name",)))


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_deploy_model_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        operation.Operation, "_set_result_from_operation"
    ), mock.patch.object(
        transports.AutoMlRestInterceptor, "post_deploy_model"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_deploy_model"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.DeployModelRequest.pb(service.DeployModelRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = json_format.MessageToJson(
            operations_pb2.Operation()
        )

        request = service.DeployModelRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = operations_pb2.Operation()

        client.deploy_model(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_deploy_model_rest_bad_request(
    transport: str = "rest", request_type=service.DeployModelRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.deploy_model(request)


def test_deploy_model_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # get arguments that satisfy an http rule for this method
        sample_request = {"name": "projects/sample1/locations/sample2/models/sample3"}

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.deploy_model(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/models/*}:deploy"
            % client.transport._host,
            args[1],
        )


def test_deploy_model_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.deploy_model(
            service.DeployModelRequest(),
            name="name_value",
        )


def test_deploy_model_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.UndeployModelRequest,
        dict,
    ],
)
def test_undeploy_model_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.undeploy_model(request)

    # Establish that the response is the type that we expect.
    assert response.operation.name == "operations/spam"


def test_undeploy_model_rest_required_fields(request_type=service.UndeployModelRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).undeploy_model._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).undeploy_model._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = operations_pb2.Operation(name="operations/spam")
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "post",
                "query_params": pb_request,
            }
            transcode_result["body"] = pb_request
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.undeploy_model(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_undeploy_model_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.undeploy_model._get_unset_required_fields({})
    assert set(unset_fields) == (set(()) & set(("name",)))


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_undeploy_model_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        operation.Operation, "_set_result_from_operation"
    ), mock.patch.object(
        transports.AutoMlRestInterceptor, "post_undeploy_model"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_undeploy_model"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.UndeployModelRequest.pb(service.UndeployModelRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = json_format.MessageToJson(
            operations_pb2.Operation()
        )

        request = service.UndeployModelRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = operations_pb2.Operation()

        client.undeploy_model(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_undeploy_model_rest_bad_request(
    transport: str = "rest", request_type=service.UndeployModelRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.undeploy_model(request)


def test_undeploy_model_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # get arguments that satisfy an http rule for this method
        sample_request = {"name": "projects/sample1/locations/sample2/models/sample3"}

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.undeploy_model(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/models/*}:undeploy"
            % client.transport._host,
            args[1],
        )


def test_undeploy_model_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.undeploy_model(
            service.UndeployModelRequest(),
            name="name_value",
        )


def test_undeploy_model_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ExportModelRequest,
        dict,
    ],
)
def test_export_model_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.export_model(request)

    # Establish that the response is the type that we expect.
    assert response.operation.name == "operations/spam"


def test_export_model_rest_required_fields(request_type=service.ExportModelRequest):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).export_model._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).export_model._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = operations_pb2.Operation(name="operations/spam")
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "post",
                "query_params": pb_request,
            }
            transcode_result["body"] = pb_request
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.export_model(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_export_model_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.export_model._get_unset_required_fields({})
    assert set(unset_fields) == (
        set(())
        & set(
            (
                "name",
                "outputConfig",
            )
        )
    )


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_export_model_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        operation.Operation, "_set_result_from_operation"
    ), mock.patch.object(
        transports.AutoMlRestInterceptor, "post_export_model"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_export_model"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.ExportModelRequest.pb(service.ExportModelRequest())
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = json_format.MessageToJson(
            operations_pb2.Operation()
        )

        request = service.ExportModelRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = operations_pb2.Operation()

        client.export_model(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_export_model_rest_bad_request(
    transport: str = "rest", request_type=service.ExportModelRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.export_model(request)


def test_export_model_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # get arguments that satisfy an http rule for this method
        sample_request = {"name": "projects/sample1/locations/sample2/models/sample3"}

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
            output_config=io.ModelExportOutputConfig(
                gcs_destination=io.GcsDestination(
                    output_uri_prefix="output_uri_prefix_value"
                )
            ),
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.export_model(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/models/*}:export"
            % client.transport._host,
            args[1],
        )


def test_export_model_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.export_model(
            service.ExportModelRequest(),
            name="name_value",
            output_config=io.ModelExportOutputConfig(
                gcs_destination=io.GcsDestination(
                    output_uri_prefix="output_uri_prefix_value"
                )
            ),
        )


def test_export_model_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ExportEvaluatedExamplesRequest,
        dict,
    ],
)
def test_export_evaluated_examples_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.export_evaluated_examples(request)

    # Establish that the response is the type that we expect.
    assert response.operation.name == "operations/spam"


def test_export_evaluated_examples_rest_required_fields(
    request_type=service.ExportEvaluatedExamplesRequest,
):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).export_evaluated_examples._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).export_evaluated_examples._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = operations_pb2.Operation(name="operations/spam")
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "post",
                "query_params": pb_request,
            }
            transcode_result["body"] = pb_request
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.export_evaluated_examples(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_export_evaluated_examples_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.export_evaluated_examples._get_unset_required_fields({})
    assert set(unset_fields) == (
        set(())
        & set(
            (
                "name",
                "outputConfig",
            )
        )
    )


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_export_evaluated_examples_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        operation.Operation, "_set_result_from_operation"
    ), mock.patch.object(
        transports.AutoMlRestInterceptor, "post_export_evaluated_examples"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_export_evaluated_examples"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.ExportEvaluatedExamplesRequest.pb(
            service.ExportEvaluatedExamplesRequest()
        )
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = json_format.MessageToJson(
            operations_pb2.Operation()
        )

        request = service.ExportEvaluatedExamplesRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = operations_pb2.Operation()

        client.export_evaluated_examples(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_export_evaluated_examples_rest_bad_request(
    transport: str = "rest", request_type=service.ExportEvaluatedExamplesRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"name": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.export_evaluated_examples(request)


def test_export_evaluated_examples_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = operations_pb2.Operation(name="operations/spam")

        # get arguments that satisfy an http rule for this method
        sample_request = {"name": "projects/sample1/locations/sample2/models/sample3"}

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
            output_config=io.ExportEvaluatedExamplesOutputConfig(
                bigquery_destination=io.BigQueryDestination(
                    output_uri="output_uri_value"
                )
            ),
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.export_evaluated_examples(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/models/*}:exportEvaluatedExamples"
            % client.transport._host,
            args[1],
        )


def test_export_evaluated_examples_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.export_evaluated_examples(
            service.ExportEvaluatedExamplesRequest(),
            name="name_value",
            output_config=io.ExportEvaluatedExamplesOutputConfig(
                bigquery_destination=io.BigQueryDestination(
                    output_uri="output_uri_value"
                )
            ),
        )


def test_export_evaluated_examples_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.GetModelEvaluationRequest,
        dict,
    ],
)
def test_get_model_evaluation_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {
        "name": "projects/sample1/locations/sample2/models/sample3/modelEvaluations/sample4"
    }
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = model_evaluation.ModelEvaluation(
            name="name_value",
            annotation_spec_id="annotation_spec_id_value",
            display_name="display_name_value",
            evaluated_example_count=2446,
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = model_evaluation.ModelEvaluation.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.get_model_evaluation(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, model_evaluation.ModelEvaluation)
    assert response.name == "name_value"
    assert response.annotation_spec_id == "annotation_spec_id_value"
    assert response.display_name == "display_name_value"
    assert response.evaluated_example_count == 2446


def test_get_model_evaluation_rest_required_fields(
    request_type=service.GetModelEvaluationRequest,
):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["name"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).get_model_evaluation._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["name"] = "name_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).get_model_evaluation._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "name" in jsonified_request
    assert jsonified_request["name"] == "name_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = model_evaluation.ModelEvaluation()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "get",
                "query_params": pb_request,
            }
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = model_evaluation.ModelEvaluation.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.get_model_evaluation(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_get_model_evaluation_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.get_model_evaluation._get_unset_required_fields({})
    assert set(unset_fields) == (set(()) & set(("name",)))


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_get_model_evaluation_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_get_model_evaluation"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_get_model_evaluation"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.GetModelEvaluationRequest.pb(
            service.GetModelEvaluationRequest()
        )
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = model_evaluation.ModelEvaluation.to_json(
            model_evaluation.ModelEvaluation()
        )

        request = service.GetModelEvaluationRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = model_evaluation.ModelEvaluation()

        client.get_model_evaluation(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_get_model_evaluation_rest_bad_request(
    transport: str = "rest", request_type=service.GetModelEvaluationRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {
        "name": "projects/sample1/locations/sample2/models/sample3/modelEvaluations/sample4"
    }
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.get_model_evaluation(request)


def test_get_model_evaluation_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = model_evaluation.ModelEvaluation()

        # get arguments that satisfy an http rule for this method
        sample_request = {
            "name": "projects/sample1/locations/sample2/models/sample3/modelEvaluations/sample4"
        }

        # get truthy value for each flattened field
        mock_args = dict(
            name="name_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = model_evaluation.ModelEvaluation.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.get_model_evaluation(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{name=projects/*/locations/*/models/*/modelEvaluations/*}"
            % client.transport._host,
            args[1],
        )


def test_get_model_evaluation_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.get_model_evaluation(
            service.GetModelEvaluationRequest(),
            name="name_value",
        )


def test_get_model_evaluation_rest_error():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(), transport="rest"
    )


@pytest.mark.parametrize(
    "request_type",
    [
        service.ListModelEvaluationsRequest,
        dict,
    ],
)
def test_list_model_evaluations_rest(request_type):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # send a request that will satisfy transcoding
    request_init = {"parent": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = service.ListModelEvaluationsResponse(
            next_page_token="next_page_token_value",
        )

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = service.ListModelEvaluationsResponse.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)

        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value
        response = client.list_model_evaluations(request)

    # Establish that the response is the type that we expect.
    assert isinstance(response, pagers.ListModelEvaluationsPager)
    assert response.next_page_token == "next_page_token_value"


def test_list_model_evaluations_rest_required_fields(
    request_type=service.ListModelEvaluationsRequest,
):
    transport_class = transports.AutoMlRestTransport

    request_init = {}
    request_init["parent"] = ""
    request = request_type(**request_init)
    pb_request = request_type.pb(request)
    jsonified_request = json.loads(
        json_format.MessageToJson(pb_request, use_integers_for_enums=False)
    )

    # verify fields with default values are dropped

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).list_model_evaluations._get_unset_required_fields(jsonified_request)
    jsonified_request.update(unset_fields)

    # verify required fields with default values are now present

    jsonified_request["parent"] = "parent_value"

    unset_fields = transport_class(
        credentials=ga_credentials.AnonymousCredentials()
    ).list_model_evaluations._get_unset_required_fields(jsonified_request)
    # Check that path parameters and body parameters are not mixing in.
    assert not set(unset_fields) - set(
        (
            "filter",
            "page_size",
            "page_token",
        )
    )
    jsonified_request.update(unset_fields)

    # verify required fields with non-default values are left alone
    assert "parent" in jsonified_request
    assert jsonified_request["parent"] == "parent_value"

    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    request = request_type(**request_init)

    # Designate an appropriate value for the returned response.
    return_value = service.ListModelEvaluationsResponse()
    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # We need to mock transcode() because providing default values
        # for required fields will fail the real version if the http_options
        # expect actual values for those fields.
        with mock.patch.object(path_template, "transcode") as transcode:
            # A uri without fields and an empty body will force all the
            # request fields to show up in the query_params.
            pb_request = request_type.pb(request)
            transcode_result = {
                "uri": "v1/sample_method",
                "method": "get",
                "query_params": pb_request,
            }
            transcode.return_value = transcode_result

            response_value = Response()
            response_value.status_code = 200

            # Convert return value to protobuf type
            return_value = service.ListModelEvaluationsResponse.pb(return_value)
            json_return_value = json_format.MessageToJson(return_value)

            response_value._content = json_return_value.encode("UTF-8")
            req.return_value = response_value

            response = client.list_model_evaluations(request)

            expected_params = [("$alt", "json;enum-encoding=int")]
            actual_params = req.call_args.kwargs["params"]
            assert expected_params == actual_params


def test_list_model_evaluations_rest_unset_required_fields():
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials
    )

    unset_fields = transport.list_model_evaluations._get_unset_required_fields({})
    assert set(unset_fields) == (
        set(
            (
                "filter",
                "pageSize",
                "pageToken",
            )
        )
        & set(("parent",))
    )


@pytest.mark.parametrize("null_interceptor", [True, False])
def test_list_model_evaluations_rest_interceptors(null_interceptor):
    transport = transports.AutoMlRestTransport(
        credentials=ga_credentials.AnonymousCredentials(),
        interceptor=None if null_interceptor else transports.AutoMlRestInterceptor(),
    )
    client = AutoMlClient(transport=transport)
    with mock.patch.object(
        type(client.transport._session), "request"
    ) as req, mock.patch.object(
        path_template, "transcode"
    ) as transcode, mock.patch.object(
        transports.AutoMlRestInterceptor, "post_list_model_evaluations"
    ) as post, mock.patch.object(
        transports.AutoMlRestInterceptor, "pre_list_model_evaluations"
    ) as pre:
        pre.assert_not_called()
        post.assert_not_called()
        pb_message = service.ListModelEvaluationsRequest.pb(
            service.ListModelEvaluationsRequest()
        )
        transcode.return_value = {
            "method": "post",
            "uri": "my_uri",
            "body": pb_message,
            "query_params": pb_message,
        }

        req.return_value = Response()
        req.return_value.status_code = 200
        req.return_value.request = PreparedRequest()
        req.return_value._content = service.ListModelEvaluationsResponse.to_json(
            service.ListModelEvaluationsResponse()
        )

        request = service.ListModelEvaluationsRequest()
        metadata = [
            ("key", "val"),
            ("cephalopod", "squid"),
        ]
        pre.return_value = request, metadata
        post.return_value = service.ListModelEvaluationsResponse()

        client.list_model_evaluations(
            request,
            metadata=[
                ("key", "val"),
                ("cephalopod", "squid"),
            ],
        )

        pre.assert_called_once()
        post.assert_called_once()


def test_list_model_evaluations_rest_bad_request(
    transport: str = "rest", request_type=service.ListModelEvaluationsRequest
):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # send a request that will satisfy transcoding
    request_init = {"parent": "projects/sample1/locations/sample2/models/sample3"}
    request = request_type(**request_init)

    # Mock the http request call within the method and fake a BadRequest error.
    with mock.patch.object(Session, "request") as req, pytest.raises(
        core_exceptions.BadRequest
    ):
        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 400
        response_value.request = Request()
        req.return_value = response_value
        client.list_model_evaluations(request)


def test_list_model_evaluations_rest_flattened():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(type(client.transport._session), "request") as req:
        # Designate an appropriate value for the returned response.
        return_value = service.ListModelEvaluationsResponse()

        # get arguments that satisfy an http rule for this method
        sample_request = {"parent": "projects/sample1/locations/sample2/models/sample3"}

        # get truthy value for each flattened field
        mock_args = dict(
            parent="parent_value",
        )
        mock_args.update(sample_request)

        # Wrap the value into a proper Response obj
        response_value = Response()
        response_value.status_code = 200
        # Convert return value to protobuf type
        return_value = service.ListModelEvaluationsResponse.pb(return_value)
        json_return_value = json_format.MessageToJson(return_value)
        response_value._content = json_return_value.encode("UTF-8")
        req.return_value = response_value

        client.list_model_evaluations(**mock_args)

        # Establish that the underlying call was made with the expected
        # request object values.
        assert len(req.mock_calls) == 1
        _, args, _ = req.mock_calls[0]
        assert path_template.validate(
            "%s/v1beta1/{parent=projects/*/locations/*/models/*}/modelEvaluations"
            % client.transport._host,
            args[1],
        )


def test_list_model_evaluations_rest_flattened_error(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Attempting to call a method with both a request object and flattened
    # fields is an error.
    with pytest.raises(ValueError):
        client.list_model_evaluations(
            service.ListModelEvaluationsRequest(),
            parent="parent_value",
        )


def test_list_model_evaluations_rest_pager(transport: str = "rest"):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport=transport,
    )

    # Mock the http request call within the method and fake a response.
    with mock.patch.object(Session, "request") as req:
        # TODO(kbandes): remove this mock unless there's a good reason for it.
        # with mock.patch.object(path_template, 'transcode') as transcode:
        # Set the response as a series of pages
        response = (
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                ],
                next_page_token="abc",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[],
                next_page_token="def",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                ],
                next_page_token="ghi",
            ),
            service.ListModelEvaluationsResponse(
                model_evaluation=[
                    model_evaluation.ModelEvaluation(),
                    model_evaluation.ModelEvaluation(),
                ],
            ),
        )
        # Two responses for two calls
        response = response + response

        # Wrap the values into proper Response objs
        response = tuple(
            service.ListModelEvaluationsResponse.to_json(x) for x in response
        )
        return_values = tuple(Response() for i in response)
        for return_val, response_val in zip(return_values, response):
            return_val._content = response_val.encode("UTF-8")
            return_val.status_code = 200
        req.side_effect = return_values

        sample_request = {"parent": "projects/sample1/locations/sample2/models/sample3"}

        pager = client.list_model_evaluations(request=sample_request)

        results = list(pager)
        assert len(results) == 6
        assert all(isinstance(i, model_evaluation.ModelEvaluation) for i in results)

        pages = list(client.list_model_evaluations(request=sample_request).pages)
        for page_, token in zip(pages, ["abc", "def", "ghi", ""]):
            assert page_.raw_page.next_page_token == token


def test_credentials_transport_error():
    # It is an error to provide credentials and a transport instance.
    transport = transports.AutoMlGrpcTransport(
        credentials=ga_credentials.AnonymousCredentials(),
    )
    with pytest.raises(ValueError):
        client = AutoMlClient(
            credentials=ga_credentials.AnonymousCredentials(),
            transport=transport,
        )

    # It is an error to provide a credentials file and a transport instance.
    transport = transports.AutoMlGrpcTransport(
        credentials=ga_credentials.AnonymousCredentials(),
    )
    with pytest.raises(ValueError):
        client = AutoMlClient(
            client_options={"credentials_file": "credentials.json"},
            transport=transport,
        )

    # It is an error to provide an api_key and a transport instance.
    transport = transports.AutoMlGrpcTransport(
        credentials=ga_credentials.AnonymousCredentials(),
    )
    options = client_options.ClientOptions()
    options.api_key = "api_key"
    with pytest.raises(ValueError):
        client = AutoMlClient(
            client_options=options,
            transport=transport,
        )

    # It is an error to provide an api_key and a credential.
    options = client_options.ClientOptions()
    options.api_key = "api_key"
    with pytest.raises(ValueError):
        client = AutoMlClient(
            client_options=options, credentials=ga_credentials.AnonymousCredentials()
        )

    # It is an error to provide scopes and a transport instance.
    transport = transports.AutoMlGrpcTransport(
        credentials=ga_credentials.AnonymousCredentials(),
    )
    with pytest.raises(ValueError):
        client = AutoMlClient(
            client_options={"scopes": ["1", "2"]},
            transport=transport,
        )


def test_transport_instance():
    # A client may be instantiated with a custom transport instance.
    transport = transports.AutoMlGrpcTransport(
        credentials=ga_credentials.AnonymousCredentials(),
    )
    client = AutoMlClient(transport=transport)
    assert client.transport is transport


def test_transport_get_channel():
    # A client may be instantiated with a custom transport instance.
    transport = transports.AutoMlGrpcTransport(
        credentials=ga_credentials.AnonymousCredentials(),
    )
    channel = transport.grpc_channel
    assert channel

    transport = transports.AutoMlGrpcAsyncIOTransport(
        credentials=ga_credentials.AnonymousCredentials(),
    )
    channel = transport.grpc_channel
    assert channel


@pytest.mark.parametrize(
    "transport_class",
    [
        transports.AutoMlGrpcTransport,
        transports.AutoMlGrpcAsyncIOTransport,
        transports.AutoMlRestTransport,
    ],
)
def test_transport_adc(transport_class):
    # Test default credentials are used if not provided.
    with mock.patch.object(google.auth, "default") as adc:
        adc.return_value = (ga_credentials.AnonymousCredentials(), None)
        transport_class()
        adc.assert_called_once()


@pytest.mark.parametrize(
    "transport_name",
    [
        "grpc",
        "rest",
    ],
)
def test_transport_kind(transport_name):
    transport = AutoMlClient.get_transport_class(transport_name)(
        credentials=ga_credentials.AnonymousCredentials(),
    )
    assert transport.kind == transport_name


def test_transport_grpc_default():
    # A client should use the gRPC transport by default.
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
    )
    assert isinstance(
        client.transport,
        transports.AutoMlGrpcTransport,
    )


def test_auto_ml_base_transport_error():
    # Passing both a credentials object and credentials_file should raise an error
    with pytest.raises(core_exceptions.DuplicateCredentialArgs):
        transport = transports.AutoMlTransport(
            credentials=ga_credentials.AnonymousCredentials(),
            credentials_file="credentials.json",
        )


def test_auto_ml_base_transport():
    # Instantiate the base transport.
    with mock.patch(
        "google.cloud.automl_v1beta1.services.auto_ml.transports.AutoMlTransport.__init__"
    ) as Transport:
        Transport.return_value = None
        transport = transports.AutoMlTransport(
            credentials=ga_credentials.AnonymousCredentials(),
        )

    # Every method on the transport should just blindly
    # raise NotImplementedError.
    methods = (
        "create_dataset",
        "get_dataset",
        "list_datasets",
        "update_dataset",
        "delete_dataset",
        "import_data",
        "export_data",
        "get_annotation_spec",
        "get_table_spec",
        "list_table_specs",
        "update_table_spec",
        "get_column_spec",
        "list_column_specs",
        "update_column_spec",
        "create_model",
        "get_model",
        "list_models",
        "delete_model",
        "deploy_model",
        "undeploy_model",
        "export_model",
        "export_evaluated_examples",
        "get_model_evaluation",
        "list_model_evaluations",
    )
    for method in methods:
        with pytest.raises(NotImplementedError):
            getattr(transport, method)(request=object())

    with pytest.raises(NotImplementedError):
        transport.close()

    # Additionally, the LRO client (a property) should
    # also raise NotImplementedError
    with pytest.raises(NotImplementedError):
        transport.operations_client

    # Catch all for all remaining methods and properties
    remainder = [
        "kind",
    ]
    for r in remainder:
        with pytest.raises(NotImplementedError):
            getattr(transport, r)()


def test_auto_ml_base_transport_with_credentials_file():
    # Instantiate the base transport with a credentials file
    with mock.patch.object(
        google.auth, "load_credentials_from_file", autospec=True
    ) as load_creds, mock.patch(
        "google.cloud.automl_v1beta1.services.auto_ml.transports.AutoMlTransport._prep_wrapped_messages"
    ) as Transport:
        Transport.return_value = None
        load_creds.return_value = (ga_credentials.AnonymousCredentials(), None)
        transport = transports.AutoMlTransport(
            credentials_file="credentials.json",
            quota_project_id="octopus",
        )
        load_creds.assert_called_once_with(
            "credentials.json",
            scopes=None,
            default_scopes=("https://www.googleapis.com/auth/cloud-platform",),
            quota_project_id="octopus",
        )


def test_auto_ml_base_transport_with_adc():
    # Test the default credentials are used if credentials and credentials_file are None.
    with mock.patch.object(google.auth, "default", autospec=True) as adc, mock.patch(
        "google.cloud.automl_v1beta1.services.auto_ml.transports.AutoMlTransport._prep_wrapped_messages"
    ) as Transport:
        Transport.return_value = None
        adc.return_value = (ga_credentials.AnonymousCredentials(), None)
        transport = transports.AutoMlTransport()
        adc.assert_called_once()


def test_auto_ml_auth_adc():
    # If no credentials are provided, we should use ADC credentials.
    with mock.patch.object(google.auth, "default", autospec=True) as adc:
        adc.return_value = (ga_credentials.AnonymousCredentials(), None)
        AutoMlClient()
        adc.assert_called_once_with(
            scopes=None,
            default_scopes=("https://www.googleapis.com/auth/cloud-platform",),
            quota_project_id=None,
        )


@pytest.mark.parametrize(
    "transport_class",
    [
        transports.AutoMlGrpcTransport,
        transports.AutoMlGrpcAsyncIOTransport,
    ],
)
def test_auto_ml_transport_auth_adc(transport_class):
    # If credentials and host are not provided, the transport class should use
    # ADC credentials.
    with mock.patch.object(google.auth, "default", autospec=True) as adc:
        adc.return_value = (ga_credentials.AnonymousCredentials(), None)
        transport_class(quota_project_id="octopus", scopes=["1", "2"])
        adc.assert_called_once_with(
            scopes=["1", "2"],
            default_scopes=("https://www.googleapis.com/auth/cloud-platform",),
            quota_project_id="octopus",
        )


@pytest.mark.parametrize(
    "transport_class",
    [
        transports.AutoMlGrpcTransport,
        transports.AutoMlGrpcAsyncIOTransport,
        transports.AutoMlRestTransport,
    ],
)
def test_auto_ml_transport_auth_gdch_credentials(transport_class):
    host = "https://language.com"
    api_audience_tests = [None, "https://language2.com"]
    api_audience_expect = [host, "https://language2.com"]
    for t, e in zip(api_audience_tests, api_audience_expect):
        with mock.patch.object(google.auth, "default", autospec=True) as adc:
            gdch_mock = mock.MagicMock()
            type(gdch_mock).with_gdch_audience = mock.PropertyMock(
                return_value=gdch_mock
            )
            adc.return_value = (gdch_mock, None)
            transport_class(host=host, api_audience=t)
            gdch_mock.with_gdch_audience.assert_called_once_with(e)


@pytest.mark.parametrize(
    "transport_class,grpc_helpers",
    [
        (transports.AutoMlGrpcTransport, grpc_helpers),
        (transports.AutoMlGrpcAsyncIOTransport, grpc_helpers_async),
    ],
)
def test_auto_ml_transport_create_channel(transport_class, grpc_helpers):
    # If credentials and host are not provided, the transport class should use
    # ADC credentials.
    with mock.patch.object(
        google.auth, "default", autospec=True
    ) as adc, mock.patch.object(
        grpc_helpers, "create_channel", autospec=True
    ) as create_channel:
        creds = ga_credentials.AnonymousCredentials()
        adc.return_value = (creds, None)
        transport_class(quota_project_id="octopus", scopes=["1", "2"])

        create_channel.assert_called_with(
            "automl.googleapis.com:443",
            credentials=creds,
            credentials_file=None,
            quota_project_id="octopus",
            default_scopes=("https://www.googleapis.com/auth/cloud-platform",),
            scopes=["1", "2"],
            default_host="automl.googleapis.com",
            ssl_credentials=None,
            options=[
                ("grpc.max_send_message_length", -1),
                ("grpc.max_receive_message_length", -1),
            ],
        )


@pytest.mark.parametrize(
    "transport_class",
    [transports.AutoMlGrpcTransport, transports.AutoMlGrpcAsyncIOTransport],
)
def test_auto_ml_grpc_transport_client_cert_source_for_mtls(transport_class):
    cred = ga_credentials.AnonymousCredentials()

    # Check ssl_channel_credentials is used if provided.
    with mock.patch.object(transport_class, "create_channel") as mock_create_channel:
        mock_ssl_channel_creds = mock.Mock()
        transport_class(
            host="squid.clam.whelk",
            credentials=cred,
            ssl_channel_credentials=mock_ssl_channel_creds,
        )
        mock_create_channel.assert_called_once_with(
            "squid.clam.whelk:443",
            credentials=cred,
            credentials_file=None,
            scopes=None,
            ssl_credentials=mock_ssl_channel_creds,
            quota_project_id=None,
            options=[
                ("grpc.max_send_message_length", -1),
                ("grpc.max_receive_message_length", -1),
            ],
        )

    # Check if ssl_channel_credentials is not provided, then client_cert_source_for_mtls
    # is used.
    with mock.patch.object(transport_class, "create_channel", return_value=mock.Mock()):
        with mock.patch("grpc.ssl_channel_credentials") as mock_ssl_cred:
            transport_class(
                credentials=cred,
                client_cert_source_for_mtls=client_cert_source_callback,
            )
            expected_cert, expected_key = client_cert_source_callback()
            mock_ssl_cred.assert_called_once_with(
                certificate_chain=expected_cert, private_key=expected_key
            )


def test_auto_ml_http_transport_client_cert_source_for_mtls():
    cred = ga_credentials.AnonymousCredentials()
    with mock.patch(
        "google.auth.transport.requests.AuthorizedSession.configure_mtls_channel"
    ) as mock_configure_mtls_channel:
        transports.AutoMlRestTransport(
            credentials=cred, client_cert_source_for_mtls=client_cert_source_callback
        )
        mock_configure_mtls_channel.assert_called_once_with(client_cert_source_callback)


def test_auto_ml_rest_lro_client():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="rest",
    )
    transport = client.transport

    # Ensure that we have a api-core operations client.
    assert isinstance(
        transport.operations_client,
        operations_v1.AbstractOperationsClient,
    )

    # Ensure that subsequent calls to the property send the exact same object.
    assert transport.operations_client is transport.operations_client


@pytest.mark.parametrize(
    "transport_name",
    [
        "grpc",
        "grpc_asyncio",
        "rest",
    ],
)
def test_auto_ml_host_no_port(transport_name):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        client_options=client_options.ClientOptions(
            api_endpoint="automl.googleapis.com"
        ),
        transport=transport_name,
    )
    assert client.transport._host == (
        "automl.googleapis.com:443"
        if transport_name in ["grpc", "grpc_asyncio"]
        else "https://automl.googleapis.com"
    )


@pytest.mark.parametrize(
    "transport_name",
    [
        "grpc",
        "grpc_asyncio",
        "rest",
    ],
)
def test_auto_ml_host_with_port(transport_name):
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        client_options=client_options.ClientOptions(
            api_endpoint="automl.googleapis.com:8000"
        ),
        transport=transport_name,
    )
    assert client.transport._host == (
        "automl.googleapis.com:8000"
        if transport_name in ["grpc", "grpc_asyncio"]
        else "https://automl.googleapis.com:8000"
    )


@pytest.mark.parametrize(
    "transport_name",
    [
        "rest",
    ],
)
def test_auto_ml_client_transport_session_collision(transport_name):
    creds1 = ga_credentials.AnonymousCredentials()
    creds2 = ga_credentials.AnonymousCredentials()
    client1 = AutoMlClient(
        credentials=creds1,
        transport=transport_name,
    )
    client2 = AutoMlClient(
        credentials=creds2,
        transport=transport_name,
    )
    session1 = client1.transport.create_dataset._session
    session2 = client2.transport.create_dataset._session
    assert session1 != session2
    session1 = client1.transport.get_dataset._session
    session2 = client2.transport.get_dataset._session
    assert session1 != session2
    session1 = client1.transport.list_datasets._session
    session2 = client2.transport.list_datasets._session
    assert session1 != session2
    session1 = client1.transport.update_dataset._session
    session2 = client2.transport.update_dataset._session
    assert session1 != session2
    session1 = client1.transport.delete_dataset._session
    session2 = client2.transport.delete_dataset._session
    assert session1 != session2
    session1 = client1.transport.import_data._session
    session2 = client2.transport.import_data._session
    assert session1 != session2
    session1 = client1.transport.export_data._session
    session2 = client2.transport.export_data._session
    assert session1 != session2
    session1 = client1.transport.get_annotation_spec._session
    session2 = client2.transport.get_annotation_spec._session
    assert session1 != session2
    session1 = client1.transport.get_table_spec._session
    session2 = client2.transport.get_table_spec._session
    assert session1 != session2
    session1 = client1.transport.list_table_specs._session
    session2 = client2.transport.list_table_specs._session
    assert session1 != session2
    session1 = client1.transport.update_table_spec._session
    session2 = client2.transport.update_table_spec._session
    assert session1 != session2
    session1 = client1.transport.get_column_spec._session
    session2 = client2.transport.get_column_spec._session
    assert session1 != session2
    session1 = client1.transport.list_column_specs._session
    session2 = client2.transport.list_column_specs._session
    assert session1 != session2
    session1 = client1.transport.update_column_spec._session
    session2 = client2.transport.update_column_spec._session
    assert session1 != session2
    session1 = client1.transport.create_model._session
    session2 = client2.transport.create_model._session
    assert session1 != session2
    session1 = client1.transport.get_model._session
    session2 = client2.transport.get_model._session
    assert session1 != session2
    session1 = client1.transport.list_models._session
    session2 = client2.transport.list_models._session
    assert session1 != session2
    session1 = client1.transport.delete_model._session
    session2 = client2.transport.delete_model._session
    assert session1 != session2
    session1 = client1.transport.deploy_model._session
    session2 = client2.transport.deploy_model._session
    assert session1 != session2
    session1 = client1.transport.undeploy_model._session
    session2 = client2.transport.undeploy_model._session
    assert session1 != session2
    session1 = client1.transport.export_model._session
    session2 = client2.transport.export_model._session
    assert session1 != session2
    session1 = client1.transport.export_evaluated_examples._session
    session2 = client2.transport.export_evaluated_examples._session
    assert session1 != session2
    session1 = client1.transport.get_model_evaluation._session
    session2 = client2.transport.get_model_evaluation._session
    assert session1 != session2
    session1 = client1.transport.list_model_evaluations._session
    session2 = client2.transport.list_model_evaluations._session
    assert session1 != session2


def test_auto_ml_grpc_transport_channel():
    channel = grpc.secure_channel("http://localhost/", grpc.local_channel_credentials())

    # Check that channel is used if provided.
    transport = transports.AutoMlGrpcTransport(
        host="squid.clam.whelk",
        channel=channel,
    )
    assert transport.grpc_channel == channel
    assert transport._host == "squid.clam.whelk:443"
    assert transport._ssl_channel_credentials == None


def test_auto_ml_grpc_asyncio_transport_channel():
    channel = aio.secure_channel("http://localhost/", grpc.local_channel_credentials())

    # Check that channel is used if provided.
    transport = transports.AutoMlGrpcAsyncIOTransport(
        host="squid.clam.whelk",
        channel=channel,
    )
    assert transport.grpc_channel == channel
    assert transport._host == "squid.clam.whelk:443"
    assert transport._ssl_channel_credentials == None


# Remove this test when deprecated arguments (api_mtls_endpoint, client_cert_source) are
# removed from grpc/grpc_asyncio transport constructor.
@pytest.mark.parametrize(
    "transport_class",
    [transports.AutoMlGrpcTransport, transports.AutoMlGrpcAsyncIOTransport],
)
def test_auto_ml_transport_channel_mtls_with_client_cert_source(transport_class):
    with mock.patch(
        "grpc.ssl_channel_credentials", autospec=True
    ) as grpc_ssl_channel_cred:
        with mock.patch.object(
            transport_class, "create_channel"
        ) as grpc_create_channel:
            mock_ssl_cred = mock.Mock()
            grpc_ssl_channel_cred.return_value = mock_ssl_cred

            mock_grpc_channel = mock.Mock()
            grpc_create_channel.return_value = mock_grpc_channel

            cred = ga_credentials.AnonymousCredentials()
            with pytest.warns(DeprecationWarning):
                with mock.patch.object(google.auth, "default") as adc:
                    adc.return_value = (cred, None)
                    transport = transport_class(
                        host="squid.clam.whelk",
                        api_mtls_endpoint="mtls.squid.clam.whelk",
                        client_cert_source=client_cert_source_callback,
                    )
                    adc.assert_called_once()

            grpc_ssl_channel_cred.assert_called_once_with(
                certificate_chain=b"cert bytes", private_key=b"key bytes"
            )
            grpc_create_channel.assert_called_once_with(
                "mtls.squid.clam.whelk:443",
                credentials=cred,
                credentials_file=None,
                scopes=None,
                ssl_credentials=mock_ssl_cred,
                quota_project_id=None,
                options=[
                    ("grpc.max_send_message_length", -1),
                    ("grpc.max_receive_message_length", -1),
                ],
            )
            assert transport.grpc_channel == mock_grpc_channel
            assert transport._ssl_channel_credentials == mock_ssl_cred


# Remove this test when deprecated arguments (api_mtls_endpoint, client_cert_source) are
# removed from grpc/grpc_asyncio transport constructor.
@pytest.mark.parametrize(
    "transport_class",
    [transports.AutoMlGrpcTransport, transports.AutoMlGrpcAsyncIOTransport],
)
def test_auto_ml_transport_channel_mtls_with_adc(transport_class):
    mock_ssl_cred = mock.Mock()
    with mock.patch.multiple(
        "google.auth.transport.grpc.SslCredentials",
        __init__=mock.Mock(return_value=None),
        ssl_credentials=mock.PropertyMock(return_value=mock_ssl_cred),
    ):
        with mock.patch.object(
            transport_class, "create_channel"
        ) as grpc_create_channel:
            mock_grpc_channel = mock.Mock()
            grpc_create_channel.return_value = mock_grpc_channel
            mock_cred = mock.Mock()

            with pytest.warns(DeprecationWarning):
                transport = transport_class(
                    host="squid.clam.whelk",
                    credentials=mock_cred,
                    api_mtls_endpoint="mtls.squid.clam.whelk",
                    client_cert_source=None,
                )

            grpc_create_channel.assert_called_once_with(
                "mtls.squid.clam.whelk:443",
                credentials=mock_cred,
                credentials_file=None,
                scopes=None,
                ssl_credentials=mock_ssl_cred,
                quota_project_id=None,
                options=[
                    ("grpc.max_send_message_length", -1),
                    ("grpc.max_receive_message_length", -1),
                ],
            )
            assert transport.grpc_channel == mock_grpc_channel


def test_auto_ml_grpc_lro_client():
    client = AutoMlClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc",
    )
    transport = client.transport

    # Ensure that we have a api-core operations client.
    assert isinstance(
        transport.operations_client,
        operations_v1.OperationsClient,
    )

    # Ensure that subsequent calls to the property send the exact same object.
    assert transport.operations_client is transport.operations_client


def test_auto_ml_grpc_lro_async_client():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc_asyncio",
    )
    transport = client.transport

    # Ensure that we have a api-core operations client.
    assert isinstance(
        transport.operations_client,
        operations_v1.OperationsAsyncClient,
    )

    # Ensure that subsequent calls to the property send the exact same object.
    assert transport.operations_client is transport.operations_client


def test_annotation_spec_path():
    project = "squid"
    location = "clam"
    dataset = "whelk"
    annotation_spec = "octopus"
    expected = "projects/{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{annotation_spec}".format(
        project=project,
        location=location,
        dataset=dataset,
        annotation_spec=annotation_spec,
    )
    actual = AutoMlClient.annotation_spec_path(
        project, location, dataset, annotation_spec
    )
    assert expected == actual


def test_parse_annotation_spec_path():
    expected = {
        "project": "oyster",
        "location": "nudibranch",
        "dataset": "cuttlefish",
        "annotation_spec": "mussel",
    }
    path = AutoMlClient.annotation_spec_path(**expected)

    # Check that the path construction is reversible.
    actual = AutoMlClient.parse_annotation_spec_path(path)
    assert expected == actual


def test_column_spec_path():
    project = "winkle"
    location = "nautilus"
    dataset = "scallop"
    table_spec = "abalone"
    column_spec = "squid"
    expected = "projects/{project}/locations/{location}/datasets/{dataset}/tableSpecs/{table_spec}/columnSpecs/{column_spec}".format(
        project=project,
        location=location,
        dataset=dataset,
        table_spec=table_spec,
        column_spec=column_spec,
    )
    actual = AutoMlClient.column_spec_path(
        project, location, dataset, table_spec, column_spec
    )
    assert expected == actual


def test_parse_column_spec_path():
    expected = {
        "project": "clam",
        "location": "whelk",
        "dataset": "octopus",
        "table_spec": "oyster",
        "column_spec": "nudibranch",
    }
    path = AutoMlClient.column_spec_path(**expected)

    # Check that the path construction is reversible.
    actual = AutoMlClient.parse_column_spec_path(path)
    assert expected == actual


def test_dataset_path():
    project = "cuttlefish"
    location = "mussel"
    dataset = "winkle"
    expected = "projects/{project}/locations/{location}/datasets/{dataset}".format(
        project=project,
        location=location,
        dataset=dataset,
    )
    actual = AutoMlClient.dataset_path(project, location, dataset)
    assert expected == actual


def test_parse_dataset_path():
    expected = {
        "project": "nautilus",
        "location": "scallop",
        "dataset": "abalone",
    }
    path = AutoMlClient.dataset_path(**expected)

    # Check that the path construction is reversible.
    actual = AutoMlClient.parse_dataset_path(path)
    assert expected == actual


def test_model_path():
    project = "squid"
    location = "clam"
    model = "whelk"
    expected = "projects/{project}/locations/{location}/models/{model}".format(
        project=project,
        location=location,
        model=model,
    )
    actual = AutoMlClient.model_path(project, location, model)
    assert expected == actual


def test_parse_model_path():
    expected = {
        "project": "octopus",
        "location": "oyster",
        "model": "nudibranch",
    }
    path = AutoMlClient.model_path(**expected)

    # Check that the path construction is reversible.
    actual = AutoMlClient.parse_model_path(path)
    assert expected == actual


def test_model_evaluation_path():
    project = "cuttlefish"
    location = "mussel"
    model = "winkle"
    model_evaluation = "nautilus"
    expected = "projects/{project}/locations/{location}/models/{model}/modelEvaluations/{model_evaluation}".format(
        project=project,
        location=location,
        model=model,
        model_evaluation=model_evaluation,
    )
    actual = AutoMlClient.model_evaluation_path(
        project, location, model, model_evaluation
    )
    assert expected == actual


def test_parse_model_evaluation_path():
    expected = {
        "project": "scallop",
        "location": "abalone",
        "model": "squid",
        "model_evaluation": "clam",
    }
    path = AutoMlClient.model_evaluation_path(**expected)

    # Check that the path construction is reversible.
    actual = AutoMlClient.parse_model_evaluation_path(path)
    assert expected == actual


def test_table_spec_path():
    project = "whelk"
    location = "octopus"
    dataset = "oyster"
    table_spec = "nudibranch"
    expected = "projects/{project}/locations/{location}/datasets/{dataset}/tableSpecs/{table_spec}".format(
        project=project,
        location=location,
        dataset=dataset,
        table_spec=table_spec,
    )
    actual = AutoMlClient.table_spec_path(project, location, dataset, table_spec)
    assert expected == actual


def test_parse_table_spec_path():
    expected = {
        "project": "cuttlefish",
        "location": "mussel",
        "dataset": "winkle",
        "table_spec": "nautilus",
    }
    path = AutoMlClient.table_spec_path(**expected)

    # Check that the path construction is reversible.
    actual = AutoMlClient.parse_table_spec_path(path)
    assert expected == actual


def test_common_billing_account_path():
    billing_account = "scallop"
    expected = "billingAccounts/{billing_account}".format(
        billing_account=billing_account,
    )
    actual = AutoMlClient.common_billing_account_path(billing_account)
    assert expected == actual


def test_parse_common_billing_account_path():
    expected = {
        "billing_account": "abalone",
    }
    path = AutoMlClient.common_billing_account_path(**expected)

    # Check that the path construction is reversible.
    actual = AutoMlClient.parse_common_billing_account_path(path)
    assert expected == actual


def test_common_folder_path():
    folder = "squid"
    expected = "folders/{folder}".format(
        folder=folder,
    )
    actual = AutoMlClient.common_folder_path(folder)
    assert expected == actual


def test_parse_common_folder_path():
    expected = {
        "folder": "clam",
    }
    path = AutoMlClient.common_folder_path(**expected)

    # Check that the path construction is reversible.
    actual = AutoMlClient.parse_common_folder_path(path)
    assert expected == actual


def test_common_organization_path():
    organization = "whelk"
    expected = "organizations/{organization}".format(
        organization=organization,
    )
    actual = AutoMlClient.common_organization_path(organization)
    assert expected == actual


def test_parse_common_organization_path():
    expected = {
        "organization": "octopus",
    }
    path = AutoMlClient.common_organization_path(**expected)

    # Check that the path construction is reversible.
    actual = AutoMlClient.parse_common_organization_path(path)
    assert expected == actual


def test_common_project_path():
    project = "oyster"
    expected = "projects/{project}".format(
        project=project,
    )
    actual = AutoMlClient.common_project_path(project)
    assert expected == actual


def test_parse_common_project_path():
    expected = {
        "project": "nudibranch",
    }
    path = AutoMlClient.common_project_path(**expected)

    # Check that the path construction is reversible.
    actual = AutoMlClient.parse_common_project_path(path)
    assert expected == actual


def test_common_location_path():
    project = "cuttlefish"
    location = "mussel"
    expected = "projects/{project}/locations/{location}".format(
        project=project,
        location=location,
    )
    actual = AutoMlClient.common_location_path(project, location)
    assert expected == actual


def test_parse_common_location_path():
    expected = {
        "project": "winkle",
        "location": "nautilus",
    }
    path = AutoMlClient.common_location_path(**expected)

    # Check that the path construction is reversible.
    actual = AutoMlClient.parse_common_location_path(path)
    assert expected == actual


def test_client_with_default_client_info():
    client_info = gapic_v1.client_info.ClientInfo()

    with mock.patch.object(
        transports.AutoMlTransport, "_prep_wrapped_messages"
    ) as prep:
        client = AutoMlClient(
            credentials=ga_credentials.AnonymousCredentials(),
            client_info=client_info,
        )
        prep.assert_called_once_with(client_info)

    with mock.patch.object(
        transports.AutoMlTransport, "_prep_wrapped_messages"
    ) as prep:
        transport_class = AutoMlClient.get_transport_class()
        transport = transport_class(
            credentials=ga_credentials.AnonymousCredentials(),
            client_info=client_info,
        )
        prep.assert_called_once_with(client_info)


@pytest.mark.asyncio
async def test_transport_close_async():
    client = AutoMlAsyncClient(
        credentials=ga_credentials.AnonymousCredentials(),
        transport="grpc_asyncio",
    )
    with mock.patch.object(
        type(getattr(client.transport, "grpc_channel")), "close"
    ) as close:
        async with client:
            close.assert_not_called()
        close.assert_called_once()


def test_transport_close():
    transports = {
        "rest": "_session",
        "grpc": "_grpc_channel",
    }

    for transport, close_name in transports.items():
        client = AutoMlClient(
            credentials=ga_credentials.AnonymousCredentials(), transport=transport
        )
        with mock.patch.object(
            type(getattr(client.transport, close_name)), "close"
        ) as close:
            with client:
                close.assert_not_called()
            close.assert_called_once()


def test_client_ctx():
    transports = [
        "rest",
        "grpc",
    ]
    for transport in transports:
        client = AutoMlClient(
            credentials=ga_credentials.AnonymousCredentials(), transport=transport
        )
        # Test client calls underlying transport.
        with mock.patch.object(type(client.transport), "close") as close:
            close.assert_not_called()
            with client:
                pass
            close.assert_called()


@pytest.mark.parametrize(
    "client_class,transport_class",
    [
        (AutoMlClient, transports.AutoMlGrpcTransport),
        (AutoMlAsyncClient, transports.AutoMlGrpcAsyncIOTransport),
    ],
)
def test_api_key_credentials(client_class, transport_class):
    with mock.patch.object(
        google.auth._default, "get_api_key_credentials", create=True
    ) as get_api_key_credentials:
        mock_cred = mock.Mock()
        get_api_key_credentials.return_value = mock_cred
        options = client_options.ClientOptions()
        options.api_key = "api_key"
        with mock.patch.object(transport_class, "__init__") as patched:
            patched.return_value = None
            client = client_class(client_options=options)
            patched.assert_called_once_with(
                credentials=mock_cred,
                credentials_file=None,
                host=client._DEFAULT_ENDPOINT_TEMPLATE.format(
                    UNIVERSE_DOMAIN=client._DEFAULT_UNIVERSE
                ),
                scopes=None,
                client_cert_source_for_mtls=None,
                quota_project_id=None,
                client_info=transports.base.DEFAULT_CLIENT_INFO,
                always_use_jwt_access=True,
                api_audience=None,
            )
