# coding: utf-8
"""
Amorphic Data Platform
Amorphic Data Platform - API Definition documentation
The version of the OpenAPI document: 1.0
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_update_dataflow_config import DatasourceFlowsUpdateDataflowConfig
from openapi_client.models.datasource_flows_update_dataset_details_inner import DatasourceFlowsUpdateDatasetDetailsInner
from openapi_client.models.datasource_flows_update_item_configs_inner import DatasourceFlowsUpdateItemConfigsInner
from typing import Optional, Set
from typing_extensions import Self
[docs]
class DatasourceFlowsUpdate(BaseModel):
"""
DatasourceFlowsUpdate
""" # noqa: E501
dataflow_name: Optional[StrictStr] = Field(default=None, alias="DataflowName")
process_type: Optional[StrictStr] = Field(default=None, alias="ProcessType")
cdc_tracking_method: Optional[StrictStr] = Field(default=None, alias="CDCTrackingMethod")
target_location: Optional[StrictStr] = Field(default=None, alias="TargetLocation")
dataflow_type: Optional[StrictStr] = Field(default=None, alias="DataflowType")
create_dataset: Optional[StrictBool] = Field(default=None, alias="CreateDataset")
dataset_details: Optional[List[DatasourceFlowsUpdateDatasetDetailsInner]] = Field(default=None, alias="DatasetDetails")
data_format: Optional[StrictStr] = Field(default=None, alias="DataFormat")
item_configs: Optional[List[DatasourceFlowsUpdateItemConfigsInner]] = Field(default=None, description="Configuration for ArcGIS items to be updated", alias="ItemConfigs")
dataflow_config: Optional[DatasourceFlowsUpdateDataflowConfig] = Field(default=None, alias="DataflowConfig")
__properties: ClassVar[List[str]] = ["DataflowName", "ProcessType", "CDCTrackingMethod", "TargetLocation", "DataflowType", "CreateDataset", "DatasetDetails", "DataFormat", "ItemConfigs", "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 DatasourceFlowsUpdate 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 each item in item_configs (list)
_items = []
if self.item_configs:
for _item_item_configs in self.item_configs:
if _item_item_configs:
_items.append(_item_item_configs.to_dict())
_dict['ItemConfigs'] = _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 DatasourceFlowsUpdate from a dict"""
if obj is None:
return None
if not isinstance(obj, dict):
return cls.model_validate(obj)
_obj = cls.model_validate({
"DataflowName": obj.get("DataflowName"),
"ProcessType": obj.get("ProcessType"),
"CDCTrackingMethod": obj.get("CDCTrackingMethod"),
"TargetLocation": obj.get("TargetLocation"),
"DataflowType": obj.get("DataflowType"),
"CreateDataset": obj.get("CreateDataset"),
"DatasetDetails": [DatasourceFlowsUpdateDatasetDetailsInner.from_dict(_item) for _item in obj["DatasetDetails"]] if obj.get("DatasetDetails") is not None else None,
"DataFormat": obj.get("DataFormat"),
"ItemConfigs": [DatasourceFlowsUpdateItemConfigsInner.from_dict(_item) for _item in obj["ItemConfigs"]] if obj.get("ItemConfigs") is not None else None,
"DataflowConfig": DatasourceFlowsUpdateDataflowConfig.from_dict(obj["DataflowConfig"]) if obj.get("DataflowConfig") is not None else None
})
return _obj