是否存在性能问题?

Please remember to "make it work first before you make it work fast". Very few percent of any program are usually relevant for its speed. You can always kick out or simplify an assert if it ever proves to be a performance problem -- and most of them never will. Be pragmatic: Assume you have a method that processes a non-empty list of tuples and the program logic will break if those tuples are not immutable. You should write: def mymethod(listOfTuples): assert(all(type(tp)==tuple for tp in listOfTuples)) This is probably fine if your lists tend to be ten entries long, but it can become a problem if they have a million entries. But rather than discarding this valuable check entirely you could simply downgrade it to def mymethod(listOfTuples): assert(type(listOfTuples[0])==tuple) # in fact _all_ must be tuples! which is cheap but will likely catch most of the actual program errors anyway.

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的使用和异常的引发都与通信有关。

Assertions are statements about the correctness of code addressed at developers: An assertion in the code informs readers of the code about conditions that have to be fulfilled for the code being correct. An assertion that fails at run-time informs developers that there is a defect in the code that needs fixing. Exceptions are indications about non-typical situations that can occur at run-time but can not be resolved by the code at hand, addressed at the calling code to be handled there. The occurence of an exception does not indicate that there is a bug in the code.

最佳实践

因此，如果您将运行时发生的特定情况视为您想要通知开发人员的错误(“嗨，开发人员，这种情况表明某处存在错误，请修复代码。”)，那么请使用断言。如果断言检查代码的输入参数，当输入参数违反条件时，您通常应该在文档中添加代码具有“未定义行为”。

相反，如果这种情况的出现并不是您眼中的错误，而是您认为应该由客户端代码处理的(可能很少，但可能)情况，则引发异常。引发哪种异常的情况应该是相应代码文档的一部分。

有没有演出[…]使用assert时的问题

断言的计算需要一些时间。但是，它们可以在编译时被删除。然而，这有一些后果，见下文。

有[…]使用assert的代码维护问题

Normally assertions improve the maintainability of the code, since they improve readability by making assumptions explicit and during run-time regularly verifying these assumptions. This will also help catching regressions. There is one issue, however, that needs to be kept in mind: Expressions used in assertions should have no side-effects. As mentioned above, assertions can be eliminated at compile time - which means that also the potential side-effects would disappear. This can - unintendedly - change the behaviour of the code.

除了其他答案之外，断言本身也会抛出异常，但仅抛出AssertionErrors。从实用主义的角度来看，当您需要对捕获的异常进行精细控制时，断言并不适合。

"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

是否存在性能问题?

Please remember to "make it work first before you make it work fast". Very few percent of any program are usually relevant for its speed. You can always kick out or simplify an assert if it ever proves to be a performance problem -- and most of them never will. Be pragmatic: Assume you have a method that processes a non-empty list of tuples and the program logic will break if those tuples are not immutable. You should write: def mymethod(listOfTuples): assert(all(type(tp)==tuple for tp in listOfTuples)) This is probably fine if your lists tend to be ten entries long, but it can become a problem if they have a million entries. But rather than discarding this valuable check entirely you could simply downgrade it to def mymethod(listOfTuples): assert(type(listOfTuples[0])==tuple) # in fact _all_ must be tuples! which is cheap but will likely catch most of the actual program errors anyway.