vcell / data /python-restclient /vcell_client /models /annotated_function_dto.py
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# 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