Does Python's `all` function use short circuit evaluation?

Question:

I wish to use the Python all() function to help me compute something, but this something could take substantially longer if the all() does not evaluate as soon as it hits a False. I’m thinking it probably is short-circuit evaluated, but I just wanted to make sure. Also, is there a way to tell in Python how the function gets evaluated?


Because any and all are functions, their arguments must be evaluated before they are called. That often creates the impression of no short-circuiting – but they do still short-circuit. To work around the problem, pass a generator expression, or other lazily evaluated expression, rather than a sequence. See Python: Lazy Function Evaluation in any() / all() for details.

Asked By: Sylvester V Lowell

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Answers:

Yes, it short-circuits:

>>> def test():
...     yield True
...     print('one')
...     yield False
...     print('two')
...     yield True
...     print('three')
...
>>> all(test())
one
False

From the docs:

Return True if all elements of the iterable are true (or if the iterable is empty). Equivalent to:

def all(iterable):
    for element in iterable:
        if not element:
            return False
    return True

So when it returns False, then the function immediately breaks.

Answered By: TerryA

Yes, all does use short-circuit evaluation. For example:

all(1.0/x < 0.5  for x in [4, 8, 1, 0])
=> False

The above stops when x reaches 1 in the list, when the condition becomes false. If all weren’t short-circuiting, we’d get a division by zero when x reached 0.

Answered By: Óscar López

In answer to your question of whether you can tell all to be either short-circuit evaluated or not, it is short-circuit by default, but if you wanted it not to be, you could do this:

result = all(list(iterable))

Though that has the possibly undesirable property that the whole list will be loaded into memory. I can’t think how you would avoid that other than using a different function than all. For example

result = reduce(lambda x,y: x and y, iterable)
result = min(iterable) # surprisingly similar to all; YMMV if iterable contains non-booleans
Answered By: morningstar

Make sure you don’t do as I did initially which was to try to use short-circuiting to test for the existence of a method before calling it:

>>> class MyClass(object):
...    pass
...
>>> a=MyClass()
>>> all([hasattr(a,'b'), a.b()])

Traceback (most recent call last):
File "<interactive input>", line 1, in <module>
AttributeError: 'MyClass' object has no attribute 'b'

but

>>> a=MyClass()                   
>>> hasattr(a,'b') and a.b()   #doesn't evaluate a.b() as hasattr(a,'b') is false

False

In the first code snippet, Python evaluates the list before passing it to all() so it still throws the exception. This is basically the same as using list() to force all() not to use short-circuit evaluation as in morningstar’s answer

Answered By: Danny