import collections
from functools import partial
import string
import subprocess
import sys
import textwrap

import numpy as np
import pytest

import pandas.util._test_decorators as td

import pandas as pd
from pandas import Series
import pandas._testing as tm
from pandas.core import ops
import pandas.core.common as com
from pandas.util.version import Version


def test_get_callable_name():
    getname = com.get_callable_name

    def fn(x):
        return x

    lambda_ = lambda x: x
    part1 = partial(fn)
    part2 = partial(part1)

    class somecall:
        def __call__(self):
            # This shouldn't actually get called below; somecall.__init__
            #  should.
            raise NotImplementedError

    assert getname(fn) == "fn"
    assert getname(lambda_)
    assert getname(part1) == "fn"
    assert getname(part2) == "fn"
    assert getname(somecall()) == "somecall"
    assert getname(1) is None


def test_any_none():
    assert com.any_none(1, 2, 3, None)
    assert not com.any_none(1, 2, 3, 4)


def test_all_not_none():
    assert com.all_not_none(1, 2, 3, 4)
    assert not com.all_not_none(1, 2, 3, None)
    assert not com.all_not_none(None, None, None, None)


def test_random_state():
    # Check with seed
    state = com.random_state(5)
    assert state.uniform() == np.random.RandomState(5).uniform()

    # Check with random state object
    state2 = np.random.RandomState(10)
    assert com.random_state(state2).uniform() == np.random.RandomState(10).uniform()

    # check with no arg random state
    assert com.random_state() is np.random

    # check array-like
    # GH32503
    state_arr_like = np.random.default_rng(None).integers(
        0, 2**31, size=624, dtype="uint32"
    )
    assert (
        com.random_state(state_arr_like).uniform()
        == np.random.RandomState(state_arr_like).uniform()
    )

    # Check BitGenerators
    # GH32503
    assert (
        com.random_state(np.random.MT19937(3)).uniform()
        == np.random.RandomState(np.random.MT19937(3)).uniform()
    )
    assert (
        com.random_state(np.random.PCG64(11)).uniform()
        == np.random.RandomState(np.random.PCG64(11)).uniform()
    )

    # Error for floats or strings
    msg = (
        "random_state must be an integer, array-like, a BitGenerator, Generator, "
        "a numpy RandomState, or None"
    )
    with pytest.raises(ValueError, match=msg):
        com.random_state("test")

    with pytest.raises(ValueError, match=msg):
        com.random_state(5.5)


@pytest.mark.parametrize(
    "left, right, expected",
    [
        (Series([1], name="x"), Series([2], name="x"), "x"),
        (Series([1], name="x"), Series([2], name="y"), None),
        (Series([1]), Series([2], name="x"), None),
        (Series([1], name="x"), Series([2]), None),
        (Series([1], name="x"), [2], "x"),
        ([1], Series([2], name="y"), "y"),
        # matching NAs
        (Series([1], name=np.nan), pd.Index([], name=np.nan), np.nan),
        (Series([1], name=np.nan), pd.Index([], name=pd.NaT), None),
        (Series([1], name=pd.NA), pd.Index([], name=pd.NA), pd.NA),
        # tuple name GH#39757
        (
            Series([1], name=np.int64(1)),
            pd.Index([], name=(np.int64(1), np.int64(2))),
            None,
        ),
        (
            Series([1], name=(np.int64(1), np.int64(2))),
            pd.Index([], name=(np.int64(1), np.int64(2))),
            (np.int64(1), np.int64(2)),
        ),
        pytest.param(
            Series([1], name=(np.float64("nan"), np.int64(2))),
            pd.Index([], name=(np.float64("nan"), np.int64(2))),
            (np.float64("nan"), np.int64(2)),
            marks=pytest.mark.xfail(
                reason="Not checking for matching NAs inside tuples."
            ),
        ),
    ],
)
def test_maybe_match_name(left, right, expected):
    res = ops.common._maybe_match_name(left, right)
    assert res is expected or res == expected


def test_standardize_mapping():
    # No uninitialized defaultdicts
    msg = r"to_dict\(\) only accepts initialized defaultdicts"
    with pytest.raises(TypeError, match=msg):
        com.standardize_mapping(collections.defaultdict)

    # No non-mapping subtypes, instance
    msg = "unsupported type: <class 'list'>"
    with pytest.raises(TypeError, match=msg):
        com.standardize_mapping([])

    # No non-mapping subtypes, class
    with pytest.raises(TypeError, match=msg):
        com.standardize_mapping(list)

    fill = {"bad": "data"}
    assert com.standardize_mapping(fill) == dict

    # Convert instance to type
    assert com.standardize_mapping({}) == dict

    dd = collections.defaultdict(list)
    assert isinstance(com.standardize_mapping(dd), partial)


def test_git_version():
    # GH 21295
    git_version = pd.__git_version__
    assert len(git_version) == 40
    assert all(c in string.hexdigits for c in git_version)


def test_version_tag():
    version = Version(pd.__version__)
    try:
        version > Version("0.0.1")
    except TypeError:
        raise ValueError(
            "No git tags exist, please sync tags between upstream and your repo"
        )


@pytest.mark.parametrize(
    "obj", [(obj,) for obj in pd.__dict__.values() if callable(obj)]
)
def test_serializable(obj):
    # GH 35611
    unpickled = tm.round_trip_pickle(obj)
    assert type(obj) == type(unpickled)


class TestIsBoolIndexer:
    def test_non_bool_array_with_na(self):
        # in particular, this should not raise
        arr = np.array(["A", "B", np.nan], dtype=object)
        assert not com.is_bool_indexer(arr)

    def test_list_subclass(self):
        # GH#42433

        class MyList(list):
            pass

        val = MyList(["a"])

        assert not com.is_bool_indexer(val)

        val = MyList([True])
        assert com.is_bool_indexer(val)

    def test_frozenlist(self):
        # GH#42461
        data = {"col1": [1, 2], "col2": [3, 4]}
        df = pd.DataFrame(data=data)

        frozen = df.index.names[1:]
        assert not com.is_bool_indexer(frozen)

        result = df[frozen]
        expected = df[[]]
        tm.assert_frame_equal(result, expected)


@pytest.mark.parametrize("with_exception", [True, False])
def test_temp_setattr(with_exception):
    # GH#45954
    ser = Series(dtype=object)
    ser.name = "first"
    # Raise a ValueError in either case to satisfy pytest.raises
    match = "Inside exception raised" if with_exception else "Outside exception raised"
    with pytest.raises(ValueError, match=match):
        with com.temp_setattr(ser, "name", "second"):
            assert ser.name == "second"
            if with_exception:
                raise ValueError("Inside exception raised")
        raise ValueError("Outside exception raised")
    assert ser.name == "first"


@pytest.mark.single_cpu
def test_str_size():
    # GH#21758
    a = "a"
    expected = sys.getsizeof(a)
    pyexe = sys.executable.replace("\\", "/")
    call = [
        pyexe,
        "-c",
        "a='a';import sys;sys.getsizeof(a);import pandas;print(sys.getsizeof(a));",
    ]
    result = subprocess.check_output(call).decode()[-4:-1].strip("\n")
    assert int(result) == int(expected)


@pytest.mark.single_cpu
def test_bz2_missing_import():
    # Check whether bz2 missing import is handled correctly (issue #53857)
    code = """
        import sys
        sys.modules['bz2'] = None
        import pytest
        import pandas as pd
        from pandas.compat import get_bz2_file
        msg = 'bz2 module not available.'
        with pytest.raises(RuntimeError, match=msg):
            get_bz2_file()
    """
    code = textwrap.dedent(code)
    call = [sys.executable, "-c", code]
    subprocess.check_output(call)


@td.skip_if_installed("pyarrow")
@pytest.mark.parametrize("module", ["pandas", "pandas.arrays"])
def test_pyarrow_missing_warn(module):
    # GH56896
    response = subprocess.run(
        [sys.executable, "-c", f"import {module}"],
        capture_output=True,
        check=True,
    )
    msg = """
Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),
(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)
but was not found to be installed on your system.
If this would cause problems for you,
please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466
"""  # noqa: E501
    stderr_msg = response.stderr.decode("utf-8")
    # Split by \n to avoid \r\n vs \n differences on Windows/Unix
    # https://stackoverflow.com/questions/11989501/replacing-r-n-with-n
    stderr_msg = "\n".join(stderr_msg.splitlines())
    assert msg in stderr_msg
