If n is None, consume entirely." # Use functions that consume iterators at C speed. " return imap ( function, count ( start )) def consume ( iterator, n = None ): "Advance the iterator n-steps ahead. Roughly equivalent to:ĭef take ( n, iterable ): "Return first n items of the iterable as a list" return list ( islice ( iterable, n )) def tabulate ( function, start = 0 ): "Return function(0), function(1). Multi-line report may list a name field on every third line). Can be used to extract relatedįields from data where the internal structure has been flattened (for example, a Negative values for start, stop, or step. Unlike regular slicing, islice() does not support If stop is None, then iterationĬontinues until the iterator is exhausted, if at all otherwise, it stops at the One which results in items being skipped. Non-zero, then elements from the iterable are skipped until start is reached.Īfterward, elements are returned consecutively unless step is set higher than Make an iterator that returns selected elements from the iterable. Is needed later, it should be stored as a list:ĭef imap ( function, * iterables ): # imap(pow, (2,3,10), (5,2,3)) -> 32 9 1000 iterables = map ( iter, iterables ) while True : args = if function is None : yield tuple ( args ) else : yield function ( * args ) itertools. Object is advanced, the previous group is no longer visible. Because the source is shared, when the groupby() The returned group is itself an iterator that shares the underlying iterable That behavior differs from SQL’s GROUP BY which aggregates commonĮlements regardless of their input order. (which is why it is usually necessary to have sorted the data using the same keyįunction). Generates a break or new group every time the value of the key function changes The operation of groupby() is similar to the uniq filter in Unix. Generally, the iterable needs to already be sorted on Specified or is None, key defaults to an identity function and returns The key is a function computing a key value for each element. Make an iterator that returns consecutive keys and groups from the iterable. R-length tuples, in sorted order, with repeated elementsĪA AB AC AD BA BB BC BD CA CB CC CD DA DB DC DDĭef dropwhile ( predicate, iterable ): # dropwhile(lambda x: x 6 4 1 iterable = iter ( iterable ) for x in iterable : if not predicate ( x ): yield x break for x in iterable : yield x itertools. R-length tuples, in sorted order, no repeated elements R-length tuples, all possible orderings, no repeated elements Izip_longest('ABCD', 'xy', fillvalue='-') -> Ax By C- D-Ĭartesian product, equivalent to a nested for-loop It1, it2, … itn splits one iterator into n Ifilter(lambda x: x%2, range(10)) -> 1 3 5 7 9Įlements of seq where pred(elem) is false ![]() Sub-iterators grouped by value of keyfunc(v) Iterators terminating on the shortest input sequence:Ĭompress('ABCDEF', ) -> A C E F Sum(imap(operator.mul, vector1, vector2)).Įlem, elem, elem, … endlessly or up to n times Operator can be mapped across two vectors to form an efficient dot-product: These tools and their built-in counterparts also work well with the high-speedįunctions in the operator module. The same effect can be achieved in Pythonīy combining imap() and count() to form imap(f, count()). Together, they form an “iteratorĪlgebra” making it possible to construct specialized tools succinctly andįor instance, SML provides a tabulation tool: tabulate(f) which produces a The module standardizes a core set of fast, memory efficient tools that are The version history can be found in documentation.This module implements a number of iterator building blocks inspiredīy constructs from APL, Haskell, and SML. If you have a problem or suggestion, please file a bug or pull request in this More-itertools is maintained by with help from many others. ![]() Several new recipes are available as well: > from more_itertools import chunked > iterable = > list ( chunked ( iterable, 3 )), , ] > from more_itertools import spy > iterable = ( x * x for x in range ( 1, 6 )) > head, iterable = spy ( iterable, n = 3 ) > list ( head ) > list ( iterable ) įor the full listing of functions, see the API documentation. To get started, install the library with pip: pip install more-itertoolsĪre included in the top-level package: > from more_itertools import flatten > iterable = > list ( flatten ( iterable )) We collect additional building blocks, recipes, and routines for working with Python’s itertools library is a gem - you can compose elegant solutionsįor a variety of problems with the functions it provides.
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