Source code for flatland.integrations.interactiveai.context_api.models.context_in

# coding: utf-8

"""
    APIFlask

    No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator)

    The version of the OpenAPI document: 0.1.0
    Generated by OpenAPI Generator (https://openapi-generator.tech)

    Do not edit the class manually.
"""  # noqa: E501

from __future__ import annotations

import json
import pprint
import re  # noqa: F401
from datetime import datetime
from typing import Any, ClassVar, Dict, List
from typing import Optional, Set

from pydantic import BaseModel, ConfigDict, Field, StrictStr, field_validator
from typing_extensions import Self

from flatland.integrations.interactiveai.context_api.models.metadata_schema_railway import MetadataSchemaRailway




class ContextIn(BaseModel):
    """
    ContextIn
    """  # noqa: E501
    data: Optional[MetadataSchemaRailway] = None
    var_date: Optional[datetime] = Field(default=None, alias="date")
    use_case: StrictStr
    __properties: ClassVar[List[str]] = ["data", "date", "use_case"]



    @field_validator('use_case')
    def use_case_validate_enum(cls, value):
        """Validates the enum"""
        if value not in set(['PowerGrid', 'Railway', 'ATM']):
            raise ValueError("must be one of enum values ('PowerGrid', 'Railway', 'ATM')")
        return value


    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 ContextIn 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 data
        if self.data:
            _dict['data'] = self.data.to_dict()
        return _dict




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

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

        _obj = cls.model_validate({
            "data": MetadataSchemaRailway.from_dict(obj["data"]) if obj.get("data") is not None else None,
            "date": obj.get("date"),
            "use_case": obj.get("use_case")
        })
        return _obj