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是检查- 1. 有效条件， 2. 有效的表述， 3.真正的逻辑; 源代码。它不会让整个项目失败，而是会发出警报，提示源文件中有些地方不合适。

在例1中，因为变量'str'不是空的。因此不会引发任何断言或异常。

示例1:

#!/usr/bin/python

str = 'hello Python!'
strNull = 'string is Null'

if __debug__:
    if not str: raise AssertionError(strNull)
print str

if __debug__:
    print 'FileName '.ljust(30,'.'),(__name__)
    print 'FilePath '.ljust(30,'.'),(__file__)


------------------------------------------------------

Output:
hello Python!
FileName ..................... hello
FilePath ..................... C:/Python\hello.py

在例2中，var 'str'为空。因此，我们可以通过assert语句来避免用户走在错误程序前面。

示例2:

#!/usr/bin/python

str = ''
strNull = 'NULL String'

if __debug__:
    if not str: raise AssertionError(strNull)
print str

if __debug__:
    print 'FileName '.ljust(30,'.'),(__name__)
    print 'FilePath '.ljust(30,'.'),(__file__)


------------------------------------------------------

Output:
AssertionError: NULL String

当我们不想调试并意识到源代码中的断言问题时。禁用优化标志

python -O assertStatement.py 没有东西会被打印出来

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。

我补充说，我经常使用断言来指定属性，比如循环不变量或我的代码应该具有的逻辑属性，就像我在正式验证的软件中指定它们一样。

它们有两个目的，告诉读者，帮助我推理，并检查我在推理中没有犯错误。例如 :

k = 0
for i in range(n):
    assert k == i * (i + 1) // 2
    k += i 
    #do some things      

或者在更复杂的情况下:

def sorted(l):
   return all(l1 <= l2 for l1, l2 in zip(l, l[1:]))
 
def mergesort(l):
   if len(l) < 2: #python 3.10 will have match - case for this instead of checking length
      return l
   k = len(l // 2)
   l1 = mergesort(l[:k])
   l2 = mergesort(l[k:])
   assert sorted(l1) # here the asserts allow me to explicit what properties my code should have
   assert sorted(l2) # I expect them to be disabled in a production build
   return merge(l1, l2)

因为当python在优化模式下运行时，断言是禁用的，所以不要犹豫在它们中编写代价高昂的条件，特别是当它使您的代码更清晰，更不容易出现错误时

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.