# coding: utf-8

"""
    VCell API

    VCell API

    The version of the OpenAPI document: 1.0.1
    Contact: vcell_support@uchc.com
    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 typing import Any, ClassVar, Dict, List, Optional
from pydantic import BaseModel, StrictStr
from pydantic import Field
from vcell_client.models.domain import Domain
from vcell_client.models.function_category import FunctionCategory
from vcell_client.models.variable_type import VariableType
try:
    from typing import Self
except ImportError:
    from typing_extensions import Self

class AnnotatedFunctionDTO(BaseModel):
    """
    AnnotatedFunctionDTO
    """ # noqa: E501
    function_name: Optional[StrictStr] = Field(default=None, alias="functionName")
    function_expression: Optional[StrictStr] = Field(default=None, alias="functionExpression")
    error: Optional[StrictStr] = None
    domain: Optional[Domain] = None
    function_type: Optional[VariableType] = Field(default=None, alias="functionType")
    category: Optional[FunctionCategory] = None
    __properties: ClassVar[List[str]] = ["functionName", "functionExpression", "error", "domain", "functionType", "category"]

    model_config = {
        "populate_by_name": True,
        "validate_assignment": True
    }


    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) -> Self:
        """Create an instance of AnnotatedFunctionDTO 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.
        """
        _dict = self.model_dump(
            by_alias=True,
            exclude={
            },
            exclude_none=True,
        )
        # override the default output from pydantic by calling `to_dict()` of domain
        if self.domain:
            _dict['domain'] = self.domain.to_dict()
        # override the default output from pydantic by calling `to_dict()` of function_type
        if self.function_type:
            _dict['functionType'] = self.function_type.to_dict()
        return _dict

    @classmethod
    def from_dict(cls, obj: Dict) -> Self:
        """Create an instance of AnnotatedFunctionDTO from a dict"""
        if obj is None:
            return None

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

        # raise errors for additional fields in the input
        for _key in obj.keys():
            if _key not in cls.__properties:
                raise ValueError("Error due to additional fields (not defined in AnnotatedFunctionDTO) in the input: " + _key)

        _obj = cls.model_validate({
            "functionName": obj.get("functionName"),
            "functionExpression": obj.get("functionExpression"),
            "error": obj.get("error"),
            "domain": Domain.from_dict(obj.get("domain")) if obj.get("domain") is not None else None,
            "functionType": VariableType.from_dict(obj.get("functionType")) if obj.get("functionType") is not None else None,
            "category": obj.get("category")
        })
        return _obj