而不是检查类型是否相等,应使用isinstance
。但是您不能使用参数化的泛型类型(typing.List[int]
),而必须使用“泛型”版本(typing.List
)。因此,您将能够检查容器类型,而不是所包含的类型。参数化的泛型类型定义了__origin__
可用于该属性的属性。
与Python 3.6相反,在Python 3.7中,大多数类型提示都具有有用的__origin__
属性。比较:
# Python 3.6
>>> import typing
>>> typing.List.__origin__
>>> typing.List[int].__origin__
typing.List
和
# Python 3.7
>>> import typing
>>> typing.List.__origin__
<class 'list'>
>>> typing.List[int].__origin__
<class 'list'>
Python 3.8通过typing.get_origin()
自省功能引入了更好的支持:
# Python 3.8
>>> import typing
>>> typing.get_origin(typing.List)
<class 'list'>
>>> typing.get_origin(typing.List[int])
<class 'list'>
值得注意的例外是typing.Any
,typing.Union
和typing.ClassVar
…嗯,任何一个typing._SpecialForm
没有定义__origin__
。幸好:
>>> isinstance(typing.Union, typing._SpecialForm)
True
>>> isinstance(typing.Union[int, str], typing._SpecialForm)
False
>>> typing.get_origin(typing.Union[int, str])
typing.Union
但是参数化类型定义了一个__args__
属性,该属性将其参数存储为元组。Python 3.8引入了typing.get_args()
检索它们的功能:
# Python 3.7
>>> typing.Union[int, str].__args__
(<class 'int'>, <class 'str'>)
# Python 3.8
>>> typing.get_args(typing.Union[int, str])
(<class 'int'>, <class 'str'>)
因此,我们可以改进类型检查:
for field_name, field_def in self.__dataclass_fields__.items():
if isinstance(field_def.type, typing._SpecialForm):
# No check for typing.Any, typing.Union, typing.ClassVar (without parameters)
continue
try:
actual_type = field_def.type.__origin__
except AttributeError:
# In case of non-typing types (such as <class 'int'>, for instance)
actual_type = field_def.type
# In Python 3.8 one would replace the try/except with
# actual_type = typing.get_origin(field_def.type) or field_def.type
if isinstance(actual_type, typing._SpecialForm):
# case of typing.Union[…] or typing.ClassVar[…]
actual_type = field_def.type.__args__
actual_value = getattr(self, field_name)
if not isinstance(actual_value, actual_type):
print(f"\t{field_name}: '{type(actual_value)}' instead of '{field_def.type}'")
ret = False
这不是完美的,因为它不会考虑typing.ClassVar[typing.Union[int, str]]
或typing.Optional[typing.List[int]]
为实例,但是它应该上手的东西。
接下来是应用此检查的方法。
除了使用之外__post_init__
,我还可以使用装饰器路线:这可以用于具有类型提示的任何东西,不仅限于dataclasses
:
import inspect
import typing
from contextlib import suppress
from functools import wraps
def enforce_types(callable):
spec = inspect.getfullargspec(callable)
def check_types(*args, **kwargs):
parameters = dict(zip(spec.args, args))
parameters.update(kwargs)
for name, value in parameters.items():
with suppress(KeyError): # Assume un-annotated parameters can be any type
type_hint = spec.annotations[name]
if isinstance(type_hint, typing._SpecialForm):
# No check for typing.Any, typing.Union, typing.ClassVar (without parameters)
continue
try:
actual_type = type_hint.__origin__
except AttributeError:
# In case of non-typing types (such as <class 'int'>, for instance)
actual_type = type_hint
# In Python 3.8 one would replace the try/except with
# actual_type = typing.get_origin(type_hint) or type_hint
if isinstance(actual_type, typing._SpecialForm):
# case of typing.Union[…] or typing.ClassVar[…]
actual_type = type_hint.__args__
if not isinstance(value, actual_type):
raise TypeError('Unexpected type for \'{}\' (expected {} but found {})'.format(name, type_hint, type(value)))
def decorate(func):
@wraps(func)
def wrapper(*args, **kwargs):
check_types(*args, **kwargs)
return func(*args, **kwargs)
return wrapper
if inspect.isclass(callable):
callable.__init__ = decorate(callable.__init__)
return callable
return decorate(callable)
用法是:
@enforce_types
@dataclasses.dataclass
class Point:
x: float
y: float
@enforce_types
def foo(bar: typing.Union[int, str]):
pass
Appart通过验证上一节中建议的某些类型提示,此方法仍存在一些缺点:
不验证不是适当类型的默认值:
@enforce_type
def foo(bar: int = None): pass
foo()
没有筹集任何款项TypeError
。如果您想对此加以考虑inspect.Signature.bind
,inspect.BoundArguments.apply_defaults
则可能需要结合使用(并因此迫使您定义def foo(bar: typing.Optional[int] = None)
);