"""Define the base Reflex class.""" from __future__ import annotations import os from typing import TYPE_CHECKING, Any, List, Type try: import pydantic.v1.main as pydantic_main from pydantic.v1 import BaseModel from pydantic.v1.fields import ModelField except ModuleNotFoundError: if not TYPE_CHECKING: import pydantic.main as pydantic_main from pydantic import BaseModel from pydantic.fields import ModelField # type: ignore def validate_field_name(bases: List[Type["BaseModel"]], field_name: str) -> None: """Ensure that the field's name does not shadow an existing attribute of the model. Args: bases: List of base models to check for shadowed attrs. field_name: name of attribute Raises: VarNameError: If state var field shadows another in its parent state """ from reflex.utils.exceptions import VarNameError # can't use reflex.config.environment here cause of circular import reload = os.getenv("__RELOAD_CONFIG", "").lower() == "true" base = None try: for base in bases: if not reload and getattr(base, field_name, None): pass except TypeError as te: raise VarNameError( f'State var "{field_name}" in {base} has been shadowed by a substate var; ' f'use a different field name instead".' ) from te # monkeypatch pydantic validate_field_name method to skip validating # shadowed state vars when reloading app via utils.prerequisites.get_app(reload=True) pydantic_main.validate_field_name = validate_field_name # type: ignore if TYPE_CHECKING: from reflex.vars import Var class Base(BaseModel): # pyright: ignore [reportUnboundVariable] """The base class subclassed by all Reflex classes. This class wraps Pydantic and provides common methods such as serialization and setting fields. Any data structure that needs to be transferred between the frontend and backend should subclass this class. """ class Config: """Pydantic config.""" arbitrary_types_allowed = True use_enum_values = True extra = "allow" def json(self) -> str: """Convert the object to a json string. Returns: The object as a json string. """ from reflex.utils.serializers import serialize return self.__config__.json_dumps( # type: ignore self.dict(), default=serialize, ) def set(self, **kwargs): """Set multiple fields and return the object. Args: **kwargs: The fields and values to set. Returns: The object with the fields set. """ for key, value in kwargs.items(): setattr(self, key, value) return self @classmethod def get_fields(cls) -> dict[str, ModelField]: """Get the fields of the object. Returns: The fields of the object. """ return cls.__fields__ @classmethod def add_field(cls, var: Var, default_value: Any): """Add a pydantic field after class definition. Used by State.add_var() to correctly handle the new variable. Args: var: The variable to add a pydantic field for. default_value: The default value of the field """ var_name = var._var_field_name new_field = ModelField.infer( name=var_name, value=default_value, annotation=var._var_type, class_validators=None, config=cls.__config__, # type: ignore ) cls.__fields__.update({var_name: new_field}) def get_value(self, key: str) -> Any: """Get the value of a field. Args: key: The key of the field. Returns: The value of the field. """ if isinstance(key, str): # Seems like this function signature was wrong all along? # If the user wants a field that we know of, get it and pass it off to _get_value return getattr(self, key, key) return key