At the end of the itertools page there is a section called Itertools Recipes: a collection of useful functions built by combining the module’s building blocks. Flattening a list of lists, finding the first element that passes a test, walking a sequence in windows: a lot of what you would write by hand is already solved there. The recipes do not come ready to use in itertools, the idea is to copy them into your code. We have already used one of them here, consume, in the article about consuming iterables without allocating memory. I picked three others that are worth knowing.
flatten flattens one level of nested lists:
from itertools import chain
def flatten(list_of_lists):
return chain.from_iterable(list_of_lists)
list(flatten([[1, 2], [3, 4], [5]])) # [1, 2, 3, 4, 5]
first_true returns the first element that satisfies a condition, without scanning the rest:
def first_true(iterable, default=False, predicate=None):
return next(filter(predicate, iterable), default)
first_true([2, 4, 7, 8], predicate=lambda x: x % 2) # 7
sliding_window walks the sequence in sliding windows:
from collections import deque
from itertools import islice
def sliding_window(iterable, n):
iterator = iter(iterable)
window = deque(islice(iterator, n - 1), maxlen=n)
for x in iterator:
window.append(x)
yield tuple(window)
list(sliding_window("ABCDE", 3)) # [('A','B','C'), ('B','C','D'), ('C','D','E')]
Some recipes were such a hit that they became part of the module, like pairwise and batched. And if you prefer everything ready and tested, the more-itertools package brings these and many others.
That’s it, folks!
See you next time!
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