从函数的关键字参数生成 TypedDict

foo.py:

kwargs = {"a": 1, "b": "c"}

def consume(*, a: int, b: str) -> None:
    pass

consume(**kwargs)

mypy foo.py:

error: Argument 1 to "consume" has incompatible type "**Dict[str, object]"; expected "int"
error: Argument 1 to "consume" has incompatible type "**Dict[str, object]"; expected "str"

这是因为object是一个超类型int and str，并因此推断。如果我声明：

from typing import TypedDict

class KWArgs(TypedDict):
    a: int
    b: str

然后注释kwargs as KWArgs, the mypy检查通行证。这实现了类型安全，但需要我复制关键字参数名称和类型consume in KWArgs。有没有办法生成这个TypedDict从类型检查时的函数签名，这样我就可以最大限度地减少维护中的重复？

To the best of my knowledge, there is no direct workaround on this ^[1], but there is another elegant way to achieve exactly that:

我们可以利用typings NamedTuple创建一个保存参数的对象：

ConsumeContext = NamedTuple('ConsumeContext', [('a', int), ('b', str)])

现在我们定义consume方法接受它作为参数：

def consume(*, consume_context : ConsumeContext) -> None:
    print(f'a : {consume_context.a} , b : {consume_context.b}')

整个代码是：

from typing import NamedTuple

ConsumeContext = NamedTuple('ConsumeContext', [('a', int), ('b', str)])

def consume(*, consume_context : ConsumeContext) -> None:
    print(f'a : {consume_context.a} , b : {consume_context.b}')

ctx = ConsumeContext(a=1, b='sabich')

consume(consume_context=ctx)

运行 mypy 会产生：

Success: no issues found in 1 source file

它会认识到a and b是参数，并批准这一点。

运行代码将输出：

a : 1 , b : sabich

然而，如果我们改变b如果不是字符串，mypy 会抱怨：

foo.py:9: error: Argument "b" to "ConsumeContext" has incompatible type "int"; expected "str"
Found 1 error in 1 file (checked 1 source file)

通过这种方式，我们通过定义一次方法的参数和类型来实现对方法的类型检查。

^{[1] Because if either defining TypedDict or function signature, based on the other, would require to know the other's __annotations__, which is not known on check-time, and defining a decorator to cast types on run-time misses the point of type checking.}