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More routines for operating on iterables, beyond itertools

Project description

https://readthedocs.org/projects/more-itertools/badge/?version=latest

Python’s itertools library is a gem - you can compose elegant solutions for a variety of problems with the functions it provides. In more-itertools we collect additional building blocks, recipes, and routines for working with Python iterables.

Grouping

chunked, ichunked, chunked_even, sliced, distribute, divide, split_at, split_before, split_after, split_into, split_when, bucket, unzip, grouper, partition

Lookahead and lookback

spy, peekable, seekable

Windowing

windowed, substrings, substrings_indexes, stagger, windowed_complete, pairwise, triplewise, sliding_window subslices,

Augmenting

count_cycle, intersperse, padded, repeat_each, mark_ends, repeat_last, adjacent, groupby_transform, pad_none, ncycles

Combining

collapse, sort_together, interleave, interleave_longest, interleave_evenly, zip_offset, zip_equal, zip_broadcast, dotproduct, convolve, flatten, roundrobin, prepend, value_chain

Summarizing

ilen, unique_to_each, sample, consecutive_groups, run_length, map_reduce, exactly_n, is_sorted, all_equal, all_unique, minmax, first_true, quantify iequals

Selecting

islice_extended, first, last, one, only, strictly_n, strip, lstrip, rstrip, filter_except, map_except, nth_or_last, unique_in_window, before_and_after, nth, take, tail, unique_everseen, unique_justseen, duplicates_everseen, duplicates_justseen longest_common_prefix

Combinatorics

distinct_permutations, distinct_combinations, circular_shifts, partitions, set_partitions, product_index, combination_index, permutation_index, powerset, random_product, random_permutation, random_combination, random_combination_with_replacement, nth_product, nth_permutation, nth_combination

Wrapping

always_iterable, always_reversible, countable, consumer, with_iter, iter_except

Others

locate, rlocate, replace, numeric_range, side_effect, iterate, difference, make_decorator, SequenceView, time_limited, map_if, consume, tabulate, repeatfunc

Getting started

To get started, install the library with pip:

pip install more-itertools

The recipes from the itertools docs are included in the top-level package:

>>> from more_itertools import flatten
>>> iterable = [(0, 1), (2, 3)]
>>> list(flatten(iterable))
[0, 1, 2, 3]

Several new recipes are available as well:

>>> from more_itertools import chunked
>>> iterable = [0, 1, 2, 3, 4, 5, 6, 7, 8]
>>> list(chunked(iterable, 3))
[[0, 1, 2], [3, 4, 5], [6, 7, 8]]

>>> from more_itertools import spy
>>> iterable = (x * x for x in range(1, 6))
>>> head, iterable = spy(iterable, n=3)
>>> list(head)
[1, 4, 9]
>>> list(iterable)
[1, 4, 9, 16, 25]

For the full listing of functions, see the API documentation.

Development

more-itertools is maintained by @erikrose and @bbayles, with help from many others. If you have a problem or suggestion, please file a bug or pull request in this repository. Thanks for contributing!

Version History

The version history can be found in documentation.

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