Why do Numpy.all() and any() give wrong results if you use generator expressions?

Question

Working with somebody else\'s code I stumbled across this gotcha. So what is the explanation for numpy\'s behavior?

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Answer 1

np.any and np.all don't work on generators. They need sequences. When given a non-sequence, they treat this as any other object and call bool on it (or do something equivalent), which will return True:

>>> false = [False]
>>> np.array(x for x in false)
array(<generator object <genexpr> at 0x31193c0>, dtype=object)
>>> bool(x for x in false)
True

List comprehensions work, though:

>>> np.all([x for x in false])
False
>>> np.any([x for x in false])
False

I advise using Python's built-in any and all when generators are expected, since they are typically faster than using NumPy and list comprehensions (because of a double conversion, first to list, then to array).