Does all(list) use short circuit evaluation?

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?

Answers:

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Method 1

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.

Method 2

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.

Method 3

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

Method 4

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

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0