python - 有没有办法在 python 中为带有类型提示的函数参数指定一系列有效值？

Question

我非常喜欢 python 中的类型提示，但是我很好奇是否有一种方法可以使用类型提示为给定参数指定一个有效的值范围。

我的想法是这样的

from typing import *

def function(
        number: Union[float, int],
        fraction: Float[0.0, 1.0] = 0.5 # give a hint that this should be between 0 and 1,
):
    return fraction * number

我可以想象可以通过断言来强制执行此操作，或者可以指定文档字符串中的有效值范围，但感觉像 Float[0.0, 1.0] 这样的东西看起来更优雅。

Answer 1

Python 3.9 引入 typing.Annotated :

In [75]: from typing import *

In [76]: from dataclasses import dataclass

In [77]: @dataclass
    ...: class ValueRange:
    ...:     min: float
    ...:     max: float
    ...:

In [78]: def function(
    ...:         number: Union[float, int],
    ...:         fraction: Annotated[float, ValueRange(0.0, 1.0)] = 0.5
    ...: ):
    ...:     return fraction * number
    ...:

与任何其他类型提示一样，它不执行任何运行时检查:

In [79]: function(1, 2)
Out[79]: 2

但是，您可以实现自己的运行时检查。下面的代码只是一个示例，它并没有涵盖所有情况，并且可能对您的简单功能来说有点矫枉过正:

In [88]: import inspect

In [89]: @dataclass
    ...: class ValueRange:
    ...:     min: float
    ...:     max: float
    ...:
    ...:     def validate_value(self, x):
    ...:         if not (self.min <= x <= self.max):
    ...:             raise ValueError(f'{x} must be in range [{self.min}, {self.max}]')
    ...:

In [90]: def check_annotated(func):
    ...:     hints = get_type_hints(func, include_extras=True)
    ...:     spec = inspect.getfullargspec(func)
    ...:
    ...:     def wrapper(*args, **kwargs):
    ...:         for idx, arg_name in enumerate(spec[0]):
    ...:             hint = hints.get(arg_name)
    ...:             validators = getattr(hint, '__metadata__', None)
    ...:             if not validators:
    ...:                 continue
    ...:             for validator in validators:
    ...:                 validator.validate_value(args[idx])
    ...:
    ...:         return func(*args, **kwargs)
    ...:     return wrapper
    ...:
    ...:

In [91]: @check_annotated
    ...: def function_2(
    ...:         number: Union[float, int],
    ...:         fraction: Annotated[float, ValueRange(0.0, 1.0)] = 0.5
    ...: ):
    ...:     return fraction * number
    ...:
    ...:

In [92]: function_2(1, 2)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-92-c9345023c025> in <module>
----> 1 function_2(1, 2)

<ipython-input-90-01115cb628ba> in wrapper(*args, **kwargs)
     10                 continue
     11             for validator in validators:
---> 12                 validator.validate_value(args[idx])
     13
     14         return func(*args, **kwargs)

<ipython-input-87-7f4ac07379f9> in validate_value(self, x)
      6     def validate_value(self, x):
      7         if not (self.min <= x <= self.max):
----> 8             raise ValueError(f'{x} must be in range [{self.min}, {self.max}]')
      9

ValueError: 2 must be in range [0.0, 1.0]

In [93]: function_2(1, 1)
Out[93]: 1