# 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_dataflow_config import DatasourceFlowsDetailsDataflowConfig
from openapi_client.models.datasource_flows_details_dataset_details_inner import DatasourceFlowsDetailsDatasetDetailsInner
from typing import Optional, Set
from typing_extensions import Self
[docs]
class DatasourceFlowsDetails(BaseModel):
"""
DatasourceFlowsDetails
""" # noqa: E501
dataflow_type: Optional[StrictStr] = Field(default=None, alias="DataflowType")
dataflow_name: Optional[StrictStr] = Field(default=None, alias="DataflowName")
datasource_id: Optional[StrictStr] = Field(default=None, alias="DatasourceId")
dataflow_status: Optional[StrictStr] = Field(default=None, alias="DataflowStatus")
process_type: Optional[StrictStr] = Field(default=None, alias="ProcessType")
target_location: Optional[StrictStr] = Field(default=None, alias="TargetLocation")
create_dataset: Optional[StrictBool] = Field(default=None, alias="CreateDataset")
dataset_details: Optional[List[DatasourceFlowsDetailsDatasetDetailsInner]] = Field(default=None, alias="DatasetDetails")
message: Optional[StrictStr] = Field(default=None, alias="Message")
data_format: Optional[StrictStr] = Field(default=None, alias="DataFormat")
creation_time: Optional[StrictStr] = Field(default=None, alias="CreationTime")
created_by: Optional[StrictStr] = Field(default=None, alias="CreatedBy")
last_modified_by: Optional[StrictStr] = Field(default=None, alias="LastModifiedBy")
last_modified_time: Optional[StrictStr] = Field(default=None, alias="LastModifiedTime")
dataflow_config: Optional[DatasourceFlowsDetailsDataflowConfig] = Field(default=None, alias="DataflowConfig")
__properties: ClassVar[List[str]] = ["DataflowType", "DataflowName", "DatasourceId", "DataflowStatus", "ProcessType", "TargetLocation", "CreateDataset", "DatasetDetails", "Message", "DataFormat", "CreationTime", "CreatedBy", "LastModifiedBy", "LastModifiedTime", "DataflowConfig"]
model_config = ConfigDict(
populate_by_name=True,
validate_assignment=True,
protected_namespaces=(),
)
[docs]
def to_str(self) -> str:
"""Returns the string representation of the model using alias"""
return pprint.pformat(self.model_dump(by_alias=True))
[docs]
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())
[docs]
@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
"""Create an instance of DatasourceFlowsDetails from a JSON string"""
return cls.from_dict(json.loads(json_str))
[docs]
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
[docs]
@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
"""Create an instance of DatasourceFlowsDetails 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"),
"DataflowName": obj.get("DataflowName"),
"DatasourceId": obj.get("DatasourceId"),
"DataflowStatus": obj.get("DataflowStatus"),
"ProcessType": obj.get("ProcessType"),
"TargetLocation": obj.get("TargetLocation"),
"CreateDataset": obj.get("CreateDataset"),
"DatasetDetails": [DatasourceFlowsDetailsDatasetDetailsInner.from_dict(_item) for _item in obj["DatasetDetails"]] if obj.get("DatasetDetails") is not None else None,
"Message": obj.get("Message"),
"DataFormat": obj.get("DataFormat"),
"CreationTime": obj.get("CreationTime"),
"CreatedBy": obj.get("CreatedBy"),
"LastModifiedBy": obj.get("LastModifiedBy"),
"LastModifiedTime": obj.get("LastModifiedTime"),
"DataflowConfig": DatasourceFlowsDetailsDataflowConfig.from_dict(obj["DataflowConfig"]) if obj.get("DataflowConfig") is not None else None
})
return _obj