# coding: utf-8

"""
    Hatchet API

    The Hatchet API

    The version of the OpenAPI document: 1.0.0
    Generated by OpenAPI Generator (https://openapi-generator.tech)

    Do not edit the class manually.
"""  # noqa: E501


from __future__ import annotations

import json
import pprint
import re  # noqa: F401
from typing import Any, ClassVar, Dict, List, Optional, Set

from pydantic import BaseModel, ConfigDict, Field, StrictStr
from typing_extensions import Self

from hatchet_sdk.clients.rest.models.api_resource_meta import APIResourceMeta
from hatchet_sdk.clients.rest.models.job import Job
from hatchet_sdk.clients.rest.models.workflow_deployment_config import (
    WorkflowDeploymentConfig,
)
from hatchet_sdk.clients.rest.models.workflow_tag import WorkflowTag


class Workflow(BaseModel):
    """
    Workflow
    """  # noqa: E501

    metadata: APIResourceMeta
    name: StrictStr = Field(description="The name of the workflow.")
    description: Optional[StrictStr] = Field(
        default=None, description="The description of the workflow."
    )
    versions: Optional[List[WorkflowVersionMeta]] = None
    tags: Optional[List[WorkflowTag]] = Field(
        default=None, description="The tags of the workflow."
    )
    last_run: Optional[WorkflowRun] = Field(default=None, alias="lastRun")
    jobs: Optional[List[Job]] = Field(
        default=None, description="The jobs of the workflow."
    )
    deployment: Optional[WorkflowDeploymentConfig] = None
    __properties: ClassVar[List[str]] = [
        "metadata",
        "name",
        "description",
        "versions",
        "tags",
        "lastRun",
        "jobs",
        "deployment",
    ]

    model_config = ConfigDict(
        populate_by_name=True,
        validate_assignment=True,
        protected_namespaces=(),
    )

    def to_str(self) -> str:
        """Returns the string representation of the model using alias"""
        return pprint.pformat(self.model_dump(by_alias=True))

    def to_json(self) -> str:
        """Returns the JSON representation of the model using alias"""
        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
        return json.dumps(self.to_dict())

    @classmethod
    def from_json(cls, json_str: str) -> Optional[Self]:
        """Create an instance of Workflow from a JSON string"""
        return cls.from_dict(json.loads(json_str))

    def to_dict(self) -> Dict[str, Any]:
        """Return the dictionary representation of the model using alias.

        This has the following differences from calling pydantic's
        `self.model_dump(by_alias=True)`:

        * `None` is only added to the output dict for nullable fields that
          were set at model initialization. Other fields with value `None`
          are ignored.
        """
        excluded_fields: Set[str] = set([])

        _dict = self.model_dump(
            by_alias=True,
            exclude=excluded_fields,
            exclude_none=True,
        )
        # override the default output from pydantic by calling `to_dict()` of metadata
        if self.metadata:
            _dict["metadata"] = self.metadata.to_dict()
        # override the default output from pydantic by calling `to_dict()` of each item in versions (list)
        _items = []
        if self.versions:
            for _item in self.versions:
                if _item:
                    _items.append(_item.to_dict())
            _dict["versions"] = _items
        # override the default output from pydantic by calling `to_dict()` of each item in tags (list)
        _items = []
        if self.tags:
            for _item in self.tags:
                if _item:
                    _items.append(_item.to_dict())
            _dict["tags"] = _items
        # override the default output from pydantic by calling `to_dict()` of last_run
        if self.last_run:
            _dict["lastRun"] = self.last_run.to_dict()
        # override the default output from pydantic by calling `to_dict()` of each item in jobs (list)
        _items = []
        if self.jobs:
            for _item in self.jobs:
                if _item:
                    _items.append(_item.to_dict())
            _dict["jobs"] = _items
        # override the default output from pydantic by calling `to_dict()` of deployment
        if self.deployment:
            _dict["deployment"] = self.deployment.to_dict()
        return _dict

    @classmethod
    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
        """Create an instance of Workflow from a dict"""
        if obj is None:
            return None

        if not isinstance(obj, dict):
            return cls.model_validate(obj)

        _obj = cls.model_validate(
            {
                "metadata": (
                    APIResourceMeta.from_dict(obj["metadata"])
                    if obj.get("metadata") is not None
                    else None
                ),
                "name": obj.get("name"),
                "description": obj.get("description"),
                "versions": (
                    [WorkflowVersionMeta.from_dict(_item) for _item in obj["versions"]]
                    if obj.get("versions") is not None
                    else None
                ),
                "tags": (
                    [WorkflowTag.from_dict(_item) for _item in obj["tags"]]
                    if obj.get("tags") is not None
                    else None
                ),
                "lastRun": (
                    WorkflowRun.from_dict(obj["lastRun"])
                    if obj.get("lastRun") is not None
                    else None
                ),
                "jobs": (
                    [Job.from_dict(_item) for _item in obj["jobs"]]
                    if obj.get("jobs") is not None
                    else None
                ),
                "deployment": (
                    WorkflowDeploymentConfig.from_dict(obj["deployment"])
                    if obj.get("deployment") is not None
                    else None
                ),
            }
        )
        return _obj


from hatchet_sdk.clients.rest.models.workflow_run import WorkflowRun
from hatchet_sdk.clients.rest.models.workflow_version_meta import WorkflowVersionMeta

# TODO: Rewrite to not use raise_errors
Workflow.model_rebuild(raise_errors=False)
