Is there a performance or code maintenance issue with using assert as part of the standard code instead of using it just for debugging purposes? Is assert x >= 0, 'x is less than zero' better or worse than if x < 0: raise Exception('x is less than zero') Also, is there any way to set a business rule like if x < 0 raise error that is always checked without the try/except/finally so, if at anytime throughout the code x is less than 0 an error is raised, like if you set assert x < 0 at the start of a function, anywhere within the function where x becomes less then 0 an exception is raised?


当前回答

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

其他回答

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

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

如前所述,当您的代码should NOT到达某个点(意味着那里存在错误)时,应该使用断言。在我看来,使用断言最有用的原因可能是不变量/前置/后置条件。在循环或函数的每次迭代的开始或结束时,这些必须为真。

例如,一个递归函数(两个独立的函数,一个处理错误的输入,另一个处理错误的代码,因为它很难与递归区分开来)。如果我忘记写if语句,这将很明显地显示出哪里出了问题。

def SumToN(n):
    if n <= 0:
        raise ValueError, "N must be greater than or equal to 0"
    else:
        return RecursiveSum(n)

def RecursiveSum(n):
    #precondition: n >= 0
    assert(n >= 0)
    if n == 0:
        return 0
    return RecursiveSum(n - 1) + n
    #postcondition: returned sum of 1 to n

这些循环不变量通常可以用断言表示。

"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

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。