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

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

其他回答

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

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。

英语单词assert在这里的意思是发誓、肯定、宣称。它的意思不是“检查”或“应该是”。这意味着你作为一个程序员要在这里做一个宣誓声明:

# I solemnly swear that here I will tell the truth, the whole truth, 
# and nothing but the truth, under pains and penalties of perjury, so help me FSM
assert answer == 42

如果代码是正确的,除了单事件中断、硬件故障等,任何断言都不会失败。这就是为什么程序对终端用户的行为不能受到影响。特别是,断言即使在异常的编程条件下也不能失败。这种事从来没有发生过。如果发生这种情况,程序员应该为此受到惩罚。

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。