Python 定义 types.Dict 和 dict 之间的区别？
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Difference between defining typing.Dict and dict?
提问by Sarit
I am practicing using type hints in Python 3.5. One of my colleague uses typing.Dict:
我正在练习在 Python 3.5 中使用类型提示。我的一位同事使用typing.Dict：
import typing
def change_bandwidths(new_bandwidths: typing.Dict,
user_id: int,
user_name: str) -> bool:
print(new_bandwidths, user_id, user_name)
return False
def my_change_bandwidths(new_bandwidths: dict,
user_id: int,
user_name: str) ->bool:
print(new_bandwidths, user_id, user_name)
return True
def main():
my_id, my_name = 23, "Tiras"
simple_dict = {"Hello": "Moon"}
change_bandwidths(simple_dict, my_id, my_name)
new_dict = {"new": "energy source"}
my_change_bandwidths(new_dict, my_id, my_name)
if __name__ == "__main__":
main()
Both of them work just fine, there doesn't appear to be a difference.
两者都工作得很好，似乎没有区别。
I have read the typingmodule documentation.
我已阅读typing模块文档。
Between typing.Dictor dictwhich one should I use in the program?
我应该在程序中使用两者之间typing.Dict或dict哪一个？
回答by Martijn Pieters
There is no real difference between using a plain typing.Dictand dict, no.
使用普通typing.Dict和没有真正的区别dict，没有。
However, typing.Dictis a Generic typethat lets you specify the type of the keys and values too, making it more flexible:
然而，typing.Dict是一个泛型类型，让你指定键和值的类型太多，使之更加灵活：
def change_bandwidths(new_bandwidths: typing.Dict[str, str],
user_id: int,
user_name: str) -> bool:
As such, it could well be that at some point in your project lifetime you want to define the dictionary argument a little more precisely, at which point expanding typing.Dictto typing.Dict[key_type, value_type]is a 'smaller' change than replacing dict.
因此，很可能在您的项目生命周期中的某个时刻，您希望更精确地定义字典参数，此时扩展typing.Dict为typing.Dict[key_type, value_type]比替换更“较小”的更改dict。
You can make this even more generic by using Mappingor MutableMappingtypes here; since your function doesn't need to alterthe mapping, I'd stick with Mapping. A dictis one mapping, but you could create other objects that also satisfy the mapping interface, and your function might well still work with those:
您可以通过在此处使用Mapping或MutableMapping类型使其更加通用；由于您的函数不需要更改映射，因此我会坚持使用Mapping. Adict是一种映射，但是您可以创建其他也满足映射接口的对象，并且您的函数可能仍然可以使用这些对象：
def change_bandwidths(new_bandwidths: typing.Mapping[str, str],
user_id: int,
user_name: str) -> bool:
Now you are clearly telling other users of this function that your code won't actually alterthe new_bandwidthsmapping passed in.
现在你清楚地告诉这个函数的其他用户你的代码实际上不会改变new_bandwidths传入的映射。
Your actual implementation is merely expecting an object that is printable. That may be a test implementation, but as it stands your code would continue to work if you used new_bandwidths: typing.Any, because any object in Python is printable.
您的实际实现只是期望一个可打印的对象。这可能是一个测试实现，但就目前而言，如果您使用new_bandwidths: typing.Any，您的代码将继续工作，因为 Python 中的任何对象都是可打印的。
回答by AKS
typing.Dictis a generic version of dict:
typing.Dict是一个通用版本dict：
class typing.Dict(dict, MutableMapping[KT, VT])A generic version of dict. The usage of this type is as follows:
def get_position_in_index(word_list: Dict[str, int], word: str) -> int: return word_list[word]
class typing.Dict(dict, MutableMapping[KT, VT])dict 的通用版本。该类型的用法如下：
def get_position_in_index(word_list: Dict[str, int], word: str) -> int: return word_list[word]
Here you can specify the type of key and values in the dict: Dict[str, int]
在这里，您可以在字典中指定键和值的类型： Dict[str, int]
