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- """Contains custom types and methods to check types."""
- from __future__ import annotations
- import contextlib
- import dataclasses
- import inspect
- import sys
- import types
- from functools import cached_property, lru_cache, wraps
- from typing import (
- Any,
- Callable,
- ClassVar,
- Dict,
- Iterable,
- List,
- Literal,
- Optional,
- Tuple,
- Type,
- Union,
- _GenericAlias, # type: ignore
- get_args,
- get_type_hints,
- )
- from typing import (
- get_origin as get_origin_og,
- )
- import sqlalchemy
- import reflex
- from reflex.components.core.breakpoints import Breakpoints
- try:
- from pydantic.v1.fields import ModelField
- except ModuleNotFoundError:
- from pydantic.fields import ModelField # type: ignore
- from sqlalchemy.ext.associationproxy import AssociationProxyInstance
- from sqlalchemy.ext.hybrid import hybrid_property
- from sqlalchemy.orm import (
- DeclarativeBase,
- Mapped,
- QueryableAttribute,
- Relationship,
- )
- from reflex import constants
- from reflex.base import Base
- from reflex.utils import console
- if sys.version_info >= (3, 12):
- from typing import override as override
- else:
- def override(func: Callable) -> Callable:
- """Fallback for @override decorator.
- Args:
- func: The function to decorate.
- Returns:
- The unmodified function.
- """
- return func
- # Potential GenericAlias types for isinstance checks.
- GenericAliasTypes = [_GenericAlias]
- with contextlib.suppress(ImportError):
- # For newer versions of Python.
- from types import GenericAlias # type: ignore
- GenericAliasTypes.append(GenericAlias)
- with contextlib.suppress(ImportError):
- # For older versions of Python.
- from typing import _SpecialGenericAlias # type: ignore
- GenericAliasTypes.append(_SpecialGenericAlias)
- GenericAliasTypes = tuple(GenericAliasTypes)
- # Potential Union types for isinstance checks (UnionType added in py3.10).
- UnionTypes = (Union, types.UnionType) if hasattr(types, "UnionType") else (Union,)
- # Union of generic types.
- GenericType = Union[Type, _GenericAlias]
- # Valid state var types.
- JSONType = {str, int, float, bool}
- PrimitiveType = Union[int, float, bool, str, list, dict, set, tuple]
- StateVar = Union[PrimitiveType, Base, None]
- StateIterVar = Union[list, set, tuple]
- # ArgsSpec = Callable[[Var], list[Var]]
- ArgsSpec = Callable
- PrimitiveToAnnotation = {
- list: List,
- tuple: Tuple,
- dict: Dict,
- }
- RESERVED_BACKEND_VAR_NAMES = {
- "_abc_impl",
- "_backend_vars",
- "_was_touched",
- }
- if sys.version_info >= (3, 11):
- from typing import Self as Self
- else:
- from typing_extensions import Self as Self
- class Unset:
- """A class to represent an unset value.
- This is used to differentiate between a value that is not set and a value that is set to None.
- """
- def __repr__(self) -> str:
- """Return the string representation of the class.
- Returns:
- The string representation of the class.
- """
- return "Unset"
- def __bool__(self) -> bool:
- """Return False when the class is used in a boolean context.
- Returns:
- False
- """
- return False
- @lru_cache()
- def get_origin(tp):
- """Get the origin of a class.
- Args:
- tp: The class to get the origin of.
- Returns:
- The origin of the class.
- """
- return get_origin_og(tp)
- @lru_cache()
- def is_generic_alias(cls: GenericType) -> bool:
- """Check whether the class is a generic alias.
- Args:
- cls: The class to check.
- Returns:
- Whether the class is a generic alias.
- """
- return isinstance(cls, GenericAliasTypes)
- def is_none(cls: GenericType) -> bool:
- """Check if a class is None.
- Args:
- cls: The class to check.
- Returns:
- Whether the class is None.
- """
- return cls is type(None) or cls is None
- @lru_cache()
- def is_union(cls: GenericType) -> bool:
- """Check if a class is a Union.
- Args:
- cls: The class to check.
- Returns:
- Whether the class is a Union.
- """
- return get_origin(cls) in UnionTypes
- @lru_cache()
- def is_literal(cls: GenericType) -> bool:
- """Check if a class is a Literal.
- Args:
- cls: The class to check.
- Returns:
- Whether the class is a literal.
- """
- return get_origin(cls) is Literal
- def is_optional(cls: GenericType) -> bool:
- """Check if a class is an Optional.
- Args:
- cls: The class to check.
- Returns:
- Whether the class is an Optional.
- """
- return is_union(cls) and type(None) in get_args(cls)
- def get_property_hint(attr: Any | None) -> GenericType | None:
- """Check if an attribute is a property and return its type hint.
- Args:
- attr: The descriptor to check.
- Returns:
- The type hint of the property, if it is a property, else None.
- """
- if not isinstance(attr, (property, hybrid_property)):
- return None
- hints = get_type_hints(attr.fget)
- return hints.get("return", None)
- def get_attribute_access_type(cls: GenericType, name: str) -> GenericType | None:
- """Check if an attribute can be accessed on the cls and return its type.
- Supports pydantic models, unions, and annotated attributes on rx.Model.
- Args:
- cls: The class to check.
- name: The name of the attribute to check.
- Returns:
- The type of the attribute, if accessible, or None
- """
- from reflex.model import Model
- try:
- attr = getattr(cls, name, None)
- except NotImplementedError:
- attr = None
- if hint := get_property_hint(attr):
- return hint
- if (
- hasattr(cls, "__fields__")
- and name in cls.__fields__
- and hasattr(cls.__fields__[name], "outer_type_")
- ):
- # pydantic models
- field = cls.__fields__[name]
- type_ = field.outer_type_
- if isinstance(type_, ModelField):
- type_ = type_.type_
- if not field.required and field.default is None:
- # Ensure frontend uses null coalescing when accessing.
- type_ = Optional[type_]
- return type_
- elif isinstance(cls, type) and issubclass(cls, DeclarativeBase):
- insp = sqlalchemy.inspect(cls)
- if name in insp.columns:
- # check for list types
- column = insp.columns[name]
- column_type = column.type
- try:
- type_ = insp.columns[name].type.python_type
- except NotImplementedError:
- type_ = None
- if type_ is not None:
- if hasattr(column_type, "item_type"):
- try:
- item_type = column_type.item_type.python_type # type: ignore
- except NotImplementedError:
- item_type = None
- if item_type is not None:
- if type_ in PrimitiveToAnnotation:
- type_ = PrimitiveToAnnotation[type_] # type: ignore
- type_ = type_[item_type] # type: ignore
- if column.nullable:
- type_ = Optional[type_]
- return type_
- if name in insp.all_orm_descriptors:
- descriptor = insp.all_orm_descriptors[name]
- if hint := get_property_hint(descriptor):
- return hint
- if isinstance(descriptor, QueryableAttribute):
- prop = descriptor.property
- if isinstance(prop, Relationship):
- type_ = prop.mapper.class_
- # TODO: check for nullable?
- type_ = List[type_] if prop.uselist else Optional[type_]
- return type_
- if isinstance(attr, AssociationProxyInstance):
- return List[
- get_attribute_access_type(
- attr.target_class,
- attr.remote_attr.key, # type: ignore[attr-defined]
- )
- ]
- elif isinstance(cls, type) and not is_generic_alias(cls) and issubclass(cls, Model):
- # Check in the annotations directly (for sqlmodel.Relationship)
- hints = get_type_hints(cls)
- if name in hints:
- type_ = hints[name]
- type_origin = get_origin(type_)
- if isinstance(type_origin, type) and issubclass(type_origin, Mapped):
- return get_args(type_)[0] # SQLAlchemy v2
- if isinstance(type_, ModelField):
- return type_.type_ # SQLAlchemy v1.4
- return type_
- elif is_union(cls):
- # Check in each arg of the annotation.
- for arg in get_args(cls):
- type_ = get_attribute_access_type(arg, name)
- if type_ is not None:
- # Return the first attribute type that is accessible.
- return type_
- elif isinstance(cls, type):
- # Bare class
- if sys.version_info >= (3, 10):
- exceptions = NameError
- else:
- exceptions = (NameError, TypeError)
- try:
- hints = get_type_hints(cls)
- if name in hints:
- return hints[name]
- except exceptions as e:
- console.warn(f"Failed to resolve ForwardRefs for {cls}.{name} due to {e}")
- pass
- return None # Attribute is not accessible.
- @lru_cache()
- def get_base_class(cls: GenericType) -> Type:
- """Get the base class of a class.
- Args:
- cls: The class.
- Returns:
- The base class of the class.
- Raises:
- TypeError: If a literal has multiple types.
- """
- if is_literal(cls):
- # only literals of the same type are supported.
- arg_type = type(get_args(cls)[0])
- if not all(type(arg) == arg_type for arg in get_args(cls)):
- raise TypeError("only literals of the same type are supported")
- return type(get_args(cls)[0])
- if is_union(cls):
- return tuple(get_base_class(arg) for arg in get_args(cls))
- return get_base_class(cls.__origin__) if is_generic_alias(cls) else cls
- def _breakpoints_satisfies_typing(cls_check: GenericType, instance: Any) -> bool:
- """Check if the breakpoints instance satisfies the typing.
- Args:
- cls_check: The class to check against.
- instance: The instance to check.
- Returns:
- Whether the breakpoints instance satisfies the typing.
- """
- cls_check_base = get_base_class(cls_check)
- if cls_check_base == Breakpoints:
- _, expected_type = get_args(cls_check)
- if is_literal(expected_type):
- for value in instance.values():
- if not isinstance(value, str) or value not in get_args(expected_type):
- return False
- return True
- elif isinstance(cls_check_base, tuple):
- # union type, so check all types
- return any(
- _breakpoints_satisfies_typing(type_to_check, instance)
- for type_to_check in get_args(cls_check)
- )
- elif cls_check_base == reflex.vars.Var and "__args__" in cls_check.__dict__:
- return _breakpoints_satisfies_typing(get_args(cls_check)[0], instance)
- return False
- def _issubclass(cls: GenericType, cls_check: GenericType, instance: Any = None) -> bool:
- """Check if a class is a subclass of another class.
- Args:
- cls: The class to check.
- cls_check: The class to check against.
- instance: An instance of cls to aid in checking generics.
- Returns:
- Whether the class is a subclass of the other class.
- Raises:
- TypeError: If the base class is not valid for issubclass.
- """
- # Special check for Any.
- if cls_check == Any:
- return True
- if cls in [Any, Callable, None]:
- return False
- # Get the base classes.
- cls_base = get_base_class(cls)
- cls_check_base = get_base_class(cls_check)
- # The class we're checking should not be a union.
- if isinstance(cls_base, tuple):
- return False
- # Check that fields of breakpoints match the expected values.
- if isinstance(instance, Breakpoints):
- return _breakpoints_satisfies_typing(cls_check, instance)
- # Check if the types match.
- try:
- return cls_check_base == Any or issubclass(cls_base, cls_check_base)
- except TypeError as te:
- # These errors typically arise from bad annotations and are hard to
- # debug without knowing the type that we tried to compare.
- raise TypeError(f"Invalid type for issubclass: {cls_base}") from te
- def _isinstance(obj: Any, cls: GenericType) -> bool:
- """Check if an object is an instance of a class.
- Args:
- obj: The object to check.
- cls: The class to check against.
- Returns:
- Whether the object is an instance of the class.
- """
- return isinstance(obj, get_base_class(cls))
- def is_dataframe(value: Type) -> bool:
- """Check if the given value is a dataframe.
- Args:
- value: The value to check.
- Returns:
- Whether the value is a dataframe.
- """
- if is_generic_alias(value) or value == Any:
- return False
- return value.__name__ == "DataFrame"
- def is_valid_var_type(type_: Type) -> bool:
- """Check if the given type is a valid prop type.
- Args:
- type_: The type to check.
- Returns:
- Whether the type is a valid prop type.
- """
- from reflex.utils import serializers
- if is_union(type_):
- return all((is_valid_var_type(arg) for arg in get_args(type_)))
- return (
- _issubclass(type_, StateVar)
- or serializers.has_serializer(type_)
- or dataclasses.is_dataclass(type_)
- )
- def is_backend_base_variable(name: str, cls: Type) -> bool:
- """Check if this variable name correspond to a backend variable.
- Args:
- name: The name of the variable to check
- cls: The class of the variable to check
- Returns:
- bool: The result of the check
- """
- if name in RESERVED_BACKEND_VAR_NAMES:
- return False
- if not name.startswith("_"):
- return False
- if name.startswith("__"):
- return False
- if name.startswith(f"_{cls.__name__}__"):
- return False
- hints = get_type_hints(cls)
- if name in hints:
- hint = get_origin(hints[name])
- if hint == ClassVar:
- return False
- if name in cls.inherited_backend_vars:
- return False
- from reflex.vars.base import is_computed_var
- if name in cls.__dict__:
- value = cls.__dict__[name]
- if type(value) == classmethod:
- return False
- if callable(value):
- return False
- if isinstance(
- value,
- (
- types.FunctionType,
- property,
- cached_property,
- ),
- ) or is_computed_var(value):
- return False
- return True
- def check_type_in_allowed_types(value_type: Type, allowed_types: Iterable) -> bool:
- """Check that a value type is found in a list of allowed types.
- Args:
- value_type: Type of value.
- allowed_types: Iterable of allowed types.
- Returns:
- If the type is found in the allowed types.
- """
- return get_base_class(value_type) in allowed_types
- def check_prop_in_allowed_types(prop: Any, allowed_types: Iterable) -> bool:
- """Check that a prop value is in a list of allowed types.
- Does the check in a way that works regardless if it's a raw value or a state Var.
- Args:
- prop: The prop to check.
- allowed_types: The list of allowed types.
- Returns:
- If the prop type match one of the allowed_types.
- """
- from reflex.vars import Var
- type_ = prop._var_type if _isinstance(prop, Var) else type(prop)
- return type_ in allowed_types
- def is_encoded_fstring(value) -> bool:
- """Check if a value is an encoded Var f-string.
- Args:
- value: The value string to check.
- Returns:
- Whether the value is an f-string
- """
- return isinstance(value, str) and constants.REFLEX_VAR_OPENING_TAG in value
- def validate_literal(key: str, value: Any, expected_type: Type, comp_name: str):
- """Check that a value is a valid literal.
- Args:
- key: The prop name.
- value: The prop value to validate.
- expected_type: The expected type(literal type).
- comp_name: Name of the component.
- Raises:
- ValueError: When the value is not a valid literal.
- """
- from reflex.vars import Var
- if (
- is_literal(expected_type)
- and not isinstance(value, Var) # validating vars is not supported yet.
- and not is_encoded_fstring(value) # f-strings are not supported.
- and value not in expected_type.__args__
- ):
- allowed_values = expected_type.__args__
- if value not in allowed_values:
- allowed_value_str = ",".join(
- [str(v) if not isinstance(v, str) else f"'{v}'" for v in allowed_values]
- )
- value_str = f"'{value}'" if isinstance(value, str) else value
- raise ValueError(
- f"prop value for {str(key)} of the `{comp_name}` component should be one of the following: {allowed_value_str}. Got {value_str} instead"
- )
- def validate_parameter_literals(func):
- """Decorator to check that the arguments passed to a function
- correspond to the correct function parameter if it (the parameter)
- is a literal type.
- Args:
- func: The function to validate.
- Returns:
- The wrapper function.
- """
- @wraps(func)
- def wrapper(*args, **kwargs):
- func_params = list(inspect.signature(func).parameters.items())
- annotations = {param[0]: param[1].annotation for param in func_params}
- # validate args
- for param, arg in zip(annotations, args):
- if annotations[param] is inspect.Parameter.empty:
- continue
- validate_literal(param, arg, annotations[param], func.__name__)
- # validate kwargs.
- for key, value in kwargs.items():
- annotation = annotations.get(key)
- if not annotation or annotation is inspect.Parameter.empty:
- continue
- validate_literal(key, value, annotation, func.__name__)
- return func(*args, **kwargs)
- return wrapper
- # Store this here for performance.
- StateBases = get_base_class(StateVar)
- StateIterBases = get_base_class(StateIterVar)
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