验证类型注释是一项不平凡的任务。 Python 不会自动执行此操作，并且编写自己的验证器很困难，因为typing 模块没有提供太多有用的接口。 （事实上，typing 模块的内部结构自从它在 python 3.5 中引入以来已经发生了很大的变化，以至于它真的是一场噩梦。）
这是一个类型验证器函数，取自我的一个个人项目（代码警告墙）：
import inspect
import typing
__all__ = ['is_instance', 'is_subtype', 'python_type', 'is_generic', 'is_base_generic', 'is_qualified_generic']
if hasattr(typing, '_GenericAlias'):
# python 3.7
def _is_generic(cls):
if isinstance(cls, typing._GenericAlias):
return True
if isinstance(cls, typing._SpecialForm):
return cls not in {typing.Any}
return False
def _is_base_generic(cls):
if isinstance(cls, typing._GenericAlias):
if cls.__origin__ in {typing.Generic, typing._Protocol}:
return False
if isinstance(cls, typing._VariadicGenericAlias):
return True
return len(cls.__parameters__) > 0
if isinstance(cls, typing._SpecialForm):
return cls._name in {'ClassVar', 'Union', 'Optional'}
return False
def _get_base_generic(cls):
# subclasses of Generic will have their _name set to None, but
# their __origin__ will point to the base generic
if cls._name is None:
return cls.__origin__
else:
return getattr(typing, cls._name)
def _get_python_type(cls):
"""
Like `python_type`, but only works with `typing` classes.
"""
return cls.__origin__
def _get_name(cls):
return cls._name
else:
# python <3.7
if hasattr(typing, '_Union'):
# python 3.6
def _is_generic(cls):
if isinstance(cls, (typing.GenericMeta, typing._Union, typing._Optional, typing._ClassVar)):
return True
return False
def _is_base_generic(cls):
if isinstance(cls, (typing.GenericMeta, typing._Union)):
return cls.__args__ in {None, ()}
if isinstance(cls, typing._Optional):
return True
return False
else:
# python 3.5
def _is_generic(cls):
if isinstance(cls, (typing.GenericMeta, typing.UnionMeta, typing.OptionalMeta, typing.CallableMeta, typing.TupleMeta)):
return True
return False
def _is_base_generic(cls):
if isinstance(cls, typing.GenericMeta):
return all(isinstance(arg, typing.TypeVar) for arg in cls.__parameters__)
if isinstance(cls, typing.UnionMeta):
return cls.__union_params__ is None
if isinstance(cls, typing.TupleMeta):
return cls.__tuple_params__ is None
if isinstance(cls, typing.CallableMeta):
return cls.__args__ is None
if isinstance(cls, typing.OptionalMeta):
return True
return False
def _get_base_generic(cls):
try:
return cls.__origin__
except AttributeError:
pass
name = type(cls).__name__
if not name.endswith('Meta'):
raise NotImplementedError("Cannot determine base of {}".format(cls))
name = name[:-4]
return getattr(typing, name)
def _get_python_type(cls):
"""
Like `python_type`, but only works with `typing` classes.
"""
# Many classes actually reference their corresponding abstract base class from the abc module
# instead of their builtin variant (i.e. typing.List references MutableSequence instead of list).
# We're interested in the builtin class (if any), so we'll traverse the MRO and look for it there.
for typ in cls.mro():
if typ.__module__ == 'builtins' and typ is not object:
return typ
try:
return cls.__extra__
except AttributeError:
pass
if is_qualified_generic(cls):
cls = get_base_generic(cls)
if cls is typing.Tuple:
return tuple
raise NotImplementedError("Cannot determine python type of {}".format(cls))
def _get_name(cls):
try:
return cls.__name__
except AttributeError:
return type(cls).__name__[1:]
if hasattr(typing.List, '__args__'):
# python 3.6+
def _get_subtypes(cls):
subtypes = cls.__args__
if get_base_generic(cls) is typing.Callable:
if len(subtypes) != 2 or subtypes[0] is not ...:
subtypes = (subtypes[:-1], subtypes[-1])
return subtypes
else:
# python 3.5
def _get_subtypes(cls):
if isinstance(cls, typing.CallableMeta):
if cls.__args__ is None:
return ()
return cls.__args__, cls.__result__
for name in ['__parameters__', '__union_params__', '__tuple_params__']:
try:
subtypes = getattr(cls, name)
break
except AttributeError:
pass
else:
raise NotImplementedError("Cannot extract subtypes from {}".format(cls))
subtypes = [typ for typ in subtypes if not isinstance(typ, typing.TypeVar)]
return subtypes
def is_generic(cls):
"""
Detects any kind of generic, for example `List` or `List[int]`. This includes "special" types like
Union and Tuple - anything that's subscriptable, basically.
"""
return _is_generic(cls)
def is_base_generic(cls):
"""
Detects generic base classes, for example `List` (but not `List[int]`)
"""
return _is_base_generic(cls)
def is_qualified_generic(cls):
"""
Detects generics with arguments, for example `List[int]` (but not `List`)
"""
return is_generic(cls) and not is_base_generic(cls)
def get_base_generic(cls):
if not is_qualified_generic(cls):
raise TypeError('{} is not a qualified Generic and thus has no base'.format(cls))
return _get_base_generic(cls)
def get_subtypes(cls):
return _get_subtypes(cls)
def _instancecheck_iterable(iterable, type_args):
if len(type_args) != 1:
raise TypeError("Generic iterables must have exactly 1 type argument; found {}".format(type_args))
type_ = type_args[0]
return all(is_instance(val, type_) for val in iterable)
def _instancecheck_mapping(mapping, type_args):
return _instancecheck_itemsview(mapping.items(), type_args)
def _instancecheck_itemsview(itemsview, type_args):
if len(type_args) != 2:
raise TypeError("Generic mappings must have exactly 2 type arguments; found {}".format(type_args))
key_type, value_type = type_args
return all(is_instance(key, key_type) and is_instance(val, value_type) for key, val in itemsview)
def _instancecheck_tuple(tup, type_args):
if len(tup) != len(type_args):
return False
return all(is_instance(val, type_) for val, type_ in zip(tup, type_args))
_ORIGIN_TYPE_CHECKERS = {}
for class_path, check_func in {
# iterables
'typing.Container': _instancecheck_iterable,
'typing.Collection': _instancecheck_iterable,
'typing.AbstractSet': _instancecheck_iterable,
'typing.MutableSet': _instancecheck_iterable,
'typing.Sequence': _instancecheck_iterable,
'typing.MutableSequence': _instancecheck_iterable,
'typing.ByteString': _instancecheck_iterable,
'typing.Deque': _instancecheck_iterable,
'typing.List': _instancecheck_iterable,
'typing.Set': _instancecheck_iterable,
'typing.FrozenSet': _instancecheck_iterable,
'typing.KeysView': _instancecheck_iterable,
'typing.ValuesView': _instancecheck_iterable,
'typing.AsyncIterable': _instancecheck_iterable,
# mappings
'typing.Mapping': _instancecheck_mapping,
'typing.MutableMapping': _instancecheck_mapping,
'typing.MappingView': _instancecheck_mapping,
'typing.ItemsView': _instancecheck_itemsview,
'typing.Dict': _instancecheck_mapping,
'typing.DefaultDict': _instancecheck_mapping,
'typing.Counter': _instancecheck_mapping,
'typing.ChainMap': _instancecheck_mapping,
# other
'typing.Tuple': _instancecheck_tuple,
}.items():
try:
cls = eval(class_path)
except AttributeError:
continue
_ORIGIN_TYPE_CHECKERS[cls] = check_func
def _instancecheck_callable(value, type_):
if not callable(value):
return False
if is_base_generic(type_):
return True
param_types, ret_type = get_subtypes(type_)
sig = inspect.signature(value)
missing_annotations = []
if param_types is not ...:
if len(param_types) != len(sig.parameters):
return False
# FIXME: add support for TypeVars
# if any of the existing annotations don't match the type, we'll return False.
# Then, if any annotations are missing, we'll throw an exception.
for param, expected_type in zip(sig.parameters.values(), param_types):
param_type = param.annotation
if param_type is inspect.Parameter.empty:
missing_annotations.append(param)
continue
if not is_subtype(param_type, expected_type):
return False
if sig.return_annotation is inspect.Signature.empty:
missing_annotations.append('return')
else:
if not is_subtype(sig.return_annotation, ret_type):
return False
if missing_annotations:
raise ValueError("Missing annotations: {}".format(missing_annotations))
return True
def _instancecheck_union(value, type_):
types = get_subtypes(type_)
return any(is_instance(value, typ) for typ in types)
def _instancecheck_type(value, type_):
# if it's not a class, return False
if not isinstance(value, type):
return False
if is_base_generic(type_):
return True
type_args = get_subtypes(type_)
if len(type_args) != 1:
raise TypeError("Type must have exactly 1 type argument; found {}".format(type_args))
return is_subtype(value, type_args[0])
_SPECIAL_INSTANCE_CHECKERS = {
'Union': _instancecheck_union,
'Callable': _instancecheck_callable,
'Type': _instancecheck_type,
'Any': lambda v, t: True,
}
def is_instance(obj, type_):
if type_.__module__ == 'typing':
if is_qualified_generic(type_):
base_generic = get_base_generic(type_)
else:
base_generic = type_
name = _get_name(base_generic)
try:
validator = _SPECIAL_INSTANCE_CHECKERS[name]
except KeyError:
pass
else:
return validator(obj, type_)
if is_base_generic(type_):
python_type = _get_python_type(type_)
return isinstance(obj, python_type)
if is_qualified_generic(type_):
python_type = _get_python_type(type_)
if not isinstance(obj, python_type):
return False
base = get_base_generic(type_)
try:
validator = _ORIGIN_TYPE_CHECKERS[base]
except KeyError:
raise NotImplementedError("Cannot perform isinstance check for type {}".format(type_))
type_args = get_subtypes(type_)
return validator(obj, type_args)
return isinstance(obj, type_)
def is_subtype(sub_type, super_type):
if not is_generic(sub_type):
python_super = python_type(super_type)
return issubclass(sub_type, python_super)
# at this point we know `sub_type` is a generic
python_sub = python_type(sub_type)
python_super = python_type(super_type)
if not issubclass(python_sub, python_super):
return False
# at this point we know that `sub_type`'s base type is a subtype of `super_type`'s base type.
# If `super_type` isn't qualified, then there's nothing more to do.
if not is_generic(super_type) or is_base_generic(super_type):
return True
# at this point we know that `super_type` is a qualified generic... so if `sub_type` isn't
# qualified, it can't be a subtype.
if is_base_generic(sub_type):
return False
# at this point we know that both types are qualified generics, so we just have to
# compare their sub-types.
sub_args = get_subtypes(sub_type)
super_args = get_subtypes(super_type)
return all(is_subtype(sub_arg, super_arg) for sub_arg, super_arg in zip(sub_args, super_args))
def python_type(annotation):
"""
Given a type annotation or a class as input, returns the corresponding python class.
Examples:
::
>>> python_type(typing.Dict)
<class 'dict'>
>>> python_type(typing.List[int])
<class 'list'>
>>> python_type(int)
<class 'int'>
"""
try:
mro = annotation.mro()
except AttributeError:
# if it doesn't have an mro method, it must be a weird typing object
return _get_python_type(annotation)
if Type in mro:
return annotation.python_type
elif annotation.__module__ == 'typing':
return _get_python_type(annotation)
else:
return annotation
演示：
>>> is_instance([{'x': 3}], List[Dict[str, int]])
True
>>> is_instance([{'x': 3}, {'y': 7.5}], List[Dict[str, int]])
False
（据我所知，这支持所有 python 版本，即使是 typing module backport 的版本。）