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