Source code for openapi_client.models.batch_update_dataset_metadata_inner
# 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 typing import Optional, Set
from typing_extensions import Self
[docs]
class BatchUpdateDatasetMetadataInner(BaseModel):
"""
BatchUpdateDatasetMetadataInner
""" # noqa: E501
dataset_description: Optional[StrictStr] = Field(default=None, alias="DatasetDescription")
dataset_id: StrictStr = Field(alias="DatasetId")
dataset_name: Optional[StrictStr] = Field(default=None, alias="DatasetName")
domain: Optional[StrictStr] = Field(default=None, alias="Domain")
file_type: Optional[StrictStr] = Field(default=None, alias="FileType")
is_active: Optional[StrictStr] = Field(default=None, alias="IsActive")
access_type: Optional[StrictStr] = Field(default=None, alias="AccessType")
registration_status: Optional[StrictStr] = Field(default=None, alias="RegistrationStatus")
table_update: Optional[StrictStr] = Field(default=None, alias="TableUpdate")
target_location: Optional[StrictStr] = Field(default=None, alias="TargetLocation")
checked: Optional[StrictBool] = None
data_classification: Optional[List[StrictStr]] = Field(default=None, alias="DataClassification")
datasource_type: Optional[StrictStr] = Field(default=None, alias="DatasourceType")
keywords: Optional[List[StrictStr]] = Field(default=None, alias="Keywords")
__properties: ClassVar[List[str]] = ["DatasetDescription", "DatasetId", "DatasetName", "Domain", "FileType", "IsActive", "AccessType", "RegistrationStatus", "TableUpdate", "TargetLocation", "checked", "DataClassification", "DatasourceType", "Keywords"]
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 BatchUpdateDatasetMetadataInner 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,
)
return _dict
[docs]
@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
"""Create an instance of BatchUpdateDatasetMetadataInner from a dict"""
if obj is None:
return None
if not isinstance(obj, dict):
return cls.model_validate(obj)
_obj = cls.model_validate({
"DatasetDescription": obj.get("DatasetDescription"),
"DatasetId": obj.get("DatasetId"),
"DatasetName": obj.get("DatasetName"),
"Domain": obj.get("Domain"),
"FileType": obj.get("FileType"),
"IsActive": obj.get("IsActive"),
"AccessType": obj.get("AccessType"),
"RegistrationStatus": obj.get("RegistrationStatus"),
"TableUpdate": obj.get("TableUpdate"),
"TargetLocation": obj.get("TargetLocation"),
"checked": obj.get("checked"),
"DataClassification": obj.get("DataClassification"),
"DatasourceType": obj.get("DatasourceType"),
"Keywords": obj.get("Keywords")
})
return _obj