Source code for openapi_client.models.datalab_create_input

# 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, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from openapi_client.models.datalab_create_input_additional_metadata import DatalabCreateInputAdditionalMetadata
from openapi_client.models.datalab_create_input_compute_metadata import DatalabCreateInputComputeMetadata
from openapi_client.models.datalab_create_input_resource_access_metadata import DatalabCreateInputResourceAccessMetadata
from typing import Optional, Set
from typing_extensions import Self



class DatalabCreateInput(BaseModel):
    """
    DatalabCreateInput
    """ # noqa: E501
    datalab_name: Optional[StrictStr] = Field(default=None, alias="DatalabName")
    datalab_type: Optional[StrictStr] = Field(default=None, alias="DatalabType")
    description: Optional[StrictStr] = Field(default=None, alias="Description")
    compute_metadata: Optional[DatalabCreateInputComputeMetadata] = Field(default=None, alias="ComputeMetadata")
    resource_access_metadata: Optional[DatalabCreateInputResourceAccessMetadata] = Field(default=None, alias="ResourceAccessMetadata")
    additional_metadata: Optional[DatalabCreateInputAdditionalMetadata] = Field(default=None, alias="AdditionalMetadata")
    __properties: ClassVar[List[str]] = ["DatalabName", "DatalabType", "Description", "ComputeMetadata", "ResourceAccessMetadata", "AdditionalMetadata"]

    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 DatalabCreateInput 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 compute_metadata
        if self.compute_metadata:
            _dict['ComputeMetadata'] = self.compute_metadata.to_dict()
        # override the default output from pydantic by calling `to_dict()` of resource_access_metadata
        if self.resource_access_metadata:
            _dict['ResourceAccessMetadata'] = self.resource_access_metadata.to_dict()
        # override the default output from pydantic by calling `to_dict()` of additional_metadata
        if self.additional_metadata:
            _dict['AdditionalMetadata'] = self.additional_metadata.to_dict()
        return _dict




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

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

        _obj = cls.model_validate({
            "DatalabName": obj.get("DatalabName"),
            "DatalabType": obj.get("DatalabType"),
            "Description": obj.get("Description"),
            "ComputeMetadata": DatalabCreateInputComputeMetadata.from_dict(obj["ComputeMetadata"]) if obj.get("ComputeMetadata") is not None else None,
            "ResourceAccessMetadata": DatalabCreateInputResourceAccessMetadata.from_dict(obj["ResourceAccessMetadata"]) if obj.get("ResourceAccessMetadata") is not None else None,
            "AdditionalMetadata": DatalabCreateInputAdditionalMetadata.from_dict(obj["AdditionalMetadata"]) if obj.get("AdditionalMetadata") is not None else None
        })
        return _obj