Source code for openapi_client.models.datasource_flows_update

# coding: utf-8

"""
    Amorphic Data Platform

    Amorphic Data Platform - API Definition documentation

    The version of the OpenAPI document: 0.3.0
    Generated by OpenAPI Generator (https://openapi-generator.tech)

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


from __future__ import annotations
import pprint
import re  # noqa: F401
import json

from pydantic import BaseModel, ConfigDict, Field, StrictBool, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from openapi_client.models.datasource_flows_details_dataset_details_inner import DatasourceFlowsDetailsDatasetDetailsInner
from openapi_client.models.datasource_flows_update_dataflow_config import DatasourceFlowsUpdateDataflowConfig
from typing import Optional, Set
from typing_extensions import Self



class DatasourceFlowsUpdate(BaseModel):
    """
    DatasourceFlowsUpdate
    """ # noqa: E501
    dataflow_type: Optional[StrictStr] = Field(default=None, alias="DataflowType")
    create_dataset: Optional[StrictBool] = Field(default=None, alias="CreateDataset")
    dataset_details: Optional[List[DatasourceFlowsDetailsDatasetDetailsInner]] = Field(default=None, alias="DatasetDetails")
    data_format: Optional[StrictStr] = Field(default=None, alias="DataFormat")
    dataflow_config: Optional[DatasourceFlowsUpdateDataflowConfig] = Field(default=None, alias="DataflowConfig")
    __properties: ClassVar[List[str]] = ["DataflowType", "CreateDataset", "DatasetDetails", "DataFormat", "DataflowConfig"]

    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 DatasourceFlowsUpdate 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 each item in dataset_details (list)
        _items = []
        if self.dataset_details:
            for _item_dataset_details in self.dataset_details:
                if _item_dataset_details:
                    _items.append(_item_dataset_details.to_dict())
            _dict['DatasetDetails'] = _items
        # override the default output from pydantic by calling `to_dict()` of dataflow_config
        if self.dataflow_config:
            _dict['DataflowConfig'] = self.dataflow_config.to_dict()
        return _dict




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

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

        _obj = cls.model_validate({
            "DataflowType": obj.get("DataflowType"),
            "CreateDataset": obj.get("CreateDataset"),
            "DatasetDetails": [DatasourceFlowsDetailsDatasetDetailsInner.from_dict(_item) for _item in obj["DatasetDetails"]] if obj.get("DatasetDetails") is not None else None,
            "DataFormat": obj.get("DataFormat"),
            "DataflowConfig": DatasourceFlowsUpdateDataflowConfig.from_dict(obj["DataflowConfig"]) if obj.get("DataflowConfig") is not None else None
        })
        return _obj