无论如何，如果你处理的代码依赖assert来正常工作，那么添加以下代码将确保assert被启用:

try:
    assert False
    raise Exception('Python assertions are not working. This tool relies on Python assertions to do its job. Possible causes are running with the "-O" flag or running a precompiled (".pyo" or ".pyc") module.')
except AssertionError:
    pass

当x在整个函数中小于零时，能够自动抛出错误。您可以使用类描述符。这里有一个例子:

class LessThanZeroException(Exception):
    pass

class variable(object):
    def __init__(self, value=0):
        self.__x = value

    def __set__(self, obj, value):
        if value < 0:
            raise LessThanZeroException('x is less than zero')

        self.__x  = value

    def __get__(self, obj, objType):
        return self.__x

class MyClass(object):
    x = variable()

>>> m = MyClass()
>>> m.x = 10
>>> m.x -= 20
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "my.py", line 7, in __set__
    raise LessThanZeroException('x is less than zero')
LessThanZeroException: x is less than zero

这种方法唯一真正的错误是，很难使用断言语句产生非常描述性的异常。如果你正在寻找更简单的语法，记住你也可以这样做:

class XLessThanZeroException(Exception):
    pass

def CheckX(x):
    if x < 0:
        raise XLessThanZeroException()

def foo(x):
    CheckX(x)
    #do stuff here

另一个问题是，使用assert进行正常的条件检查会使使用-O标志禁用调试断言变得困难。

断言应该用于测试不应该发生的情况。目的是在程序状态损坏的情况下尽早崩溃。

异常应该用于可能发生的错误，并且几乎总是应该创建自己的Exception类。

例如，如果您正在编写一个从配置文件读取到dict的函数，那么文件中的不当格式将引发ConfigurationSyntaxError，而您可以断言您不会返回None。

在您的示例中，如果x是通过用户界面或外部源设置的值，则最好使用异常。

如果x只是在同一个程序中由您自己的代码设置的，则使用断言。

assert的四个目的

假设您与四位同事Alice、Bernd、Carl和Daphne一起处理20万行代码。 他们喊你的代码，你喊他们的代码。

那么assert有四个角色:

Inform Alice, Bernd, Carl, and Daphne what your code expects. Assume you have a method that processes a list of tuples and the program logic can break if those tuples are not immutable: def mymethod(listOfTuples): assert(all(type(tp)==tuple for tp in listOfTuples)) This is more trustworthy than equivalent information in the documentation and much easier to maintain. Inform the computer what your code expects. assert enforces proper behavior from the callers of your code. If your code calls Alices's and Bernd's code calls yours, then without the assert, if the program crashes in Alices code, Bernd might assume it was Alice's fault, Alice investigates and might assume it was your fault, you investigate and tell Bernd it was in fact his. Lots of work lost. With asserts, whoever gets a call wrong, they will quickly be able to see it was their fault, not yours. Alice, Bernd, and you all benefit. Saves immense amounts of time. Inform the readers of your code (including yourself) what your code has achieved at some point. Assume you have a list of entries and each of them can be clean (which is good) or it can be smorsh, trale, gullup, or twinkled (which are all not acceptable). If it's smorsh it must be unsmorshed; if it's trale it must be baludoed; if it's gullup it must be trotted (and then possibly paced, too); if it's twinkled it must be twinkled again except on Thursdays. You get the idea: It's complicated stuff. But the end result is (or ought to be) that all entries are clean. The Right Thing(TM) to do is to summarize the effect of your cleaning loop as assert(all(entry.isClean() for entry in mylist)) This statements saves a headache for everybody trying to understand what exactly it is that the wonderful loop is achieving. And the most frequent of these people will likely be yourself. Inform the computer what your code has achieved at some point. Should you ever forget to pace an entry needing it after trotting, the assert will save your day and avoid that your code breaks dear Daphne's much later.

在我看来，assert的两个文档目的(1和3)和 保障措施(2和4)同样有价值。 告知人民甚至可能比告知计算机更有价值 因为它可以防止assert要捕捉的错误(在情况1中) 无论如何，接下来还有很多错误。

"assert"语句在编译优化时被删除。所以，是的，它们在性能和功能上都有差异。

在编译时请求优化时，当前代码生成器不会为assert语句生成代码。Python 3 Docs

如果您使用assert来实现应用程序功能，然后优化部署到生产环境，那么您将受到“但它在开发中有效”缺陷的困扰。

参见PYTHONOPTIMIZE和-O -OO