I am a fairly new developer in Python and was getting accustomed to the idea of "Duck Typing".

我是一个相当新手的开发人员，我已经习惯了“鸭子打字”的想法。

I have a class I used in another module to do particular things with it, for example, access it's name and version. This module obviously cannot handle arbitrary values and needs the name to be a string and version to be an integer.

我在另一个模块中使用了一个类来对它执行特定的操作，例如，访问它的名称和版本。该模块显然不能处理任意值，需要名称为字符串，版本为整数。

Currently, I am enforcing the type of input to my class properties using isinstance():

目前，我正在使用isInstance()将输入类型强制输入到我的类属性：

class ExampleObject(object):
    def __init__(self):
        self._name = None
        self._version = None

    @property
    def name(self):
        return self._name

    @name.setter
    def name(self, name):
        if not isinstance(name, str) and name is not None:
            raise ValueError("Expected string, got {0}".format(type(name)))
        
        self._name = name

    @property
    def version(self):
        return self._name

    @version.setter
    def version(self, version_number):
        if not isinstance(version_number, int) and version_number is not None:
            raise ValueError("Expected int, got {0}".format(type(version_number)))

        self._version = version_number
        

If I go with the idea of Duck typing, I should not be enforcing a particular type to my properties. If I drop my type checking and some other developer starts using these properties for other data types, it can lead to the module I wrote breaking. Basically, the module expecting an integer and it gets something else. What's the correct approach to this?

如果我采用Duck类型的想法，我不应该强制我的属性使用特定的类型。如果我放弃类型检查，而其他开发人员开始将这些属性用于其他数据类型，可能会导致我编写的模块崩溃。基本上，该模块需要一个整数，但它得到的是其他值。解决这个问题的正确方法是什么？

I checked several related questions regarding this but none of them covers what would happen if we skip the type checking and how to enforce that other developers don't break things because they were not aware of another module using these properties to perform type specific things.

我检查了几个与此相关的问题，但没有一个涉及到如果我们跳过类型检查会发生什么，以及如何强制其他开发人员不破坏东西，因为他们不知道另一个模块使用这些属性来执行特定于类型的事情。

Python's duck typing puts the onus on you to enforce it. If the parameter will be passed by the user, it can be a good idea to perform casting and/or type validation. For example, you can try casting version_number to an int using the built-in int() method. If this fails (ie. version_number cannot be converted to a string), the int() method raises a ValueError for you, which you can check for as follows:

Python的鸭子类型将强制执行它的责任推给了您。如果参数将由用户传递，那么执行强制转换和/或类型验证可能是个好主意。例如，您可以尝试使用内置的int()方法将VERSION_NUMBER转换为int。如果此操作失败(即VERSION_NUMBER无法转换为字符串)，int()方法将为您引发ValueError，您可以按如下方式进行检查：

@version.setter
def version(self, version_number):
    try:
        version_number = int(version_number)
    except ValueError: #when casting to int fails, Python raises a ValueError
        # handle error here
    #otherwise, version_number is now a valid int, so continue

If you're the only one that will be using your code, you can forgo this validation at your own risk. Regardless of which you choose, it's also a good idea to use type hints. Type hints don't do anything at runtime (so they won't perform any casting/validation for you), but can help assist your IDE in reminding you what type is expected for a parameter or return. Type hints for your function might look as follows:

如果您是唯一将使用您的代码的人，您可以放弃此验证，风险自负。无论您选择哪种类型，使用类型提示都是一个好主意。类型提示在运行时不做任何事情(因此它们不会为您执行任何强制转换/验证)，但可以帮助您的IDE提醒您参数或返回应该使用什么类型。为您的函数键入提示可能如下所示：

@version.setter
def version(self, version_number: int) -> None:

No type hint is required on the self parameter, as your IDE can tell self will be an ExampleObject. The type hint int on the parameter version_number indicates that this parameter should be an int. Finally, the return type hint of None indicates this function doesn't return anything.

在self参数上不需要类型提示，因为您的IDE可以告诉您self将是一个ExampleObject。参数VERSION_NUMBER上的类型提示指示此参数应为int。最后，返回类型提示NONE表示该函数不返回任何内容。

Source: https://mypy.readthedocs.io/en/stable/cheat_sheet_py3.html

消息来源：https://mypy.readthedocs.io/en/stable/cheat_sheet_py3.html