英文:
Python arbritary keys in TypedDict
问题
你能否创建一个具有一组已知键和任意键类型的 TypedDict 吗？例如，在 TypeScript 中，我可以这样做：
from typing import TypedDict, Mapping, List, Union
class Sample(TypedDict):
x: bool
y: int
labels: Mapping[str, str]
aliases: Mapping[str, List[str]]
# For arbitrary keys with type SomeCustomClass
__annotations__: Mapping[str, Union[str, List[str], SomeCustomClass]]
编辑：我的问题是，我创建了一个库，其中一个函数的参数期望类型为 Mapping[str, SomeCustomClass]。我想更改类型，使其包含特殊键，类型如下：
labels: Mapping[str, str]aliases: Mapping[str, List[str]]
但我仍希望它仍然是一个任意映射，如果键不在上述两种特殊情况中，则其类型应为 SomeCustomClass。有什么好的方法可以做到这一点吗？如果有替代方案而不会造成向后不兼容的更改，我对此不感兴趣。
英文:
Is it possible to make a TypedDict with a set of known keys and then a type for an arbitrary key? For example, in TypeScript, I could do this:
interface Sample {
x: boolean;
y: number;
[name: string]: string;
}
What is the equivalent in Python?
Edit: My problem is that I make a library where a function's argument expects a type of Mapping[str, SomeCustomClass]. I want to change the type so that there are now special keys, where the types are like this:
labels: Mapping[str, str]aliases: Mapping[str, List[str]]
But I want it to still be an arbitrary mapping where if a key is not in the two special cases above, it should be of type SomeCustomClass. What is a good way to do this? I am not interested in making a backwards-incompatible change if there is an alternative.
答案1
得分: 1
这是可能的，使用 Union 类型操作符，但不幸的是，通过这种解决方案，您失去了对必需字段的检查：
from typing import TypedDict, Union, Dict
class SampleRequiredType(TypedDict, total=True):
x: bool
y: int
SampleType = Union[SampleRequiredType, Dict]
# 现在所有这些字典都是有效的：
dict1: SampleType = {
'x': True,
'y': 123
}
dict2: SampleType = {
'x': True,
'y': 123,
'z': 'my string'
}
dict3: SampleType = {
'z': 'my string'
}
英文:
That is possible with Union type operator, but unfortunately with this solution, you lose checking the required fields:
from typing import TypedDict, Union, Dict
class SampleRequiredType(TypedDict, total=True):
x: bool
y: int
SampleType = Union[SampleRequiredType, Dict]
# Now all these dictionaries will be valid:
dict1: SampleType = {
'x': True,
'y': 123
}
dict2: SampleType = {
'x': True,
'y': 123
'z': 'my string'
}
dict3: SampleType = {
'z': 'my string'
}
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