reflex/reflex/utils/types.py
2024-02-08 11:21:46 -08:00

401 lines
12 KiB
Python

"""Contains custom types and methods to check types."""
from __future__ import annotations
import contextlib
import inspect
import types
from functools import wraps
from typing import (
Any,
Callable,
Iterable,
Literal,
Optional,
Type,
Union,
_GenericAlias, # type: ignore
get_args,
get_origin,
get_type_hints,
)
import sqlalchemy
from pydantic.fields import ModelField
from sqlalchemy.ext.hybrid import hybrid_property
from sqlalchemy.orm import DeclarativeBase, Mapped, QueryableAttribute, Relationship
from reflex.base import Base
from reflex.utils import serializers
# 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
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.
"""
# For older versions of Python.
if isinstance(cls, _GenericAlias):
return True
with contextlib.suppress(ImportError):
from typing import _SpecialGenericAlias # type: ignore
if isinstance(cls, _SpecialGenericAlias):
return True
# For newer versions of Python.
try:
from types import GenericAlias # type: ignore
return isinstance(cls, GenericAlias)
except ImportError:
return False
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.
"""
# UnionType added in py3.10
if not hasattr(types, "UnionType"):
return get_origin(cls) is Union
return get_origin(cls) in [Union, types.UnionType]
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
attr = getattr(cls, name, None)
if hint := get_property_hint(attr):
return hint
if hasattr(cls, "__fields__") and name in cls.__fields__:
# 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:
return insp.columns[name].type.python_type
if name not in insp.all_orm_descriptors.keys():
return None
descriptor = insp.all_orm_descriptors[name]
if hint := get_property_hint(descriptor):
return hint
if isinstance(descriptor, QueryableAttribute):
prop = descriptor.property
if not isinstance(prop, Relationship):
return None
return prop.mapper.class_
elif isinstance(cls, type) 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_
return None # Attribute is not accessible.
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 _issubclass(cls: GenericType, cls_check: GenericType) -> bool:
"""Check if a class is a subclass of another class.
Args:
cls: The class to check.
cls_check: The class to check against.
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 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.
"""
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_)
def is_backend_variable(name: str, cls: Type | None = None) -> 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 cls is not None and name.startswith(f"_{cls.__name__}__"):
return False
return name.startswith("_") and not name.startswith("__")
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 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 value not in expected_type.__args__
):
allowed_values = expected_type.__args__
if value not in allowed_values:
value_str = ",".join(
[str(v) if not isinstance(v, str) else f"'{v}'" for v in allowed_values]
)
raise ValueError(
f"prop value for {str(key)} of the `{comp_name}` component should be one of the following: {value_str}. Got '{value}' 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.keys(), 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)