philiprehberger-list-chunk 0.3.0

Split iterables into evenly sized chunks.

philiprehberger-list-chunk

Split iterables into evenly sized chunks.

Installation

pip install philiprehberger-list-chunk

Usage

from philiprehberger_list_chunk import chunk, chunk_by, sliding_window, interleave, flatten

chunk([1, 2, 3, 4, 5], size=2)
# [[1, 2], [3, 4], [5]]

chunk([1, 2, 3], size=2, pad=0)
# [[1, 2], [3, 0]]

chunk_by([1, 1, 2, 2, 3], key=lambda x: x)
# [[1, 1], [2, 2], [3]]

sliding_window([1, 2, 3, 4, 5], size=3)
# [[1, 2, 3], [2, 3, 4], [3, 4, 5]]

interleave([1, 2, 3], ["a", "b", "c"])
# [1, "a", 2, "b", 3, "c"]

flatten([[1, 2], [3, 4]])
# [1, 2, 3, 4]

Transpose and pairwise

transpose(matrix) swaps rows and columns and truncates to the shortest row, so jagged input stays rectangular. pairwise(items) returns consecutive overlapping pairs.

from philiprehberger_list_chunk import transpose, pairwise

transpose([[1, 2, 3], [4, 5, 6]])
# [[1, 4], [2, 5], [3, 6]]

pairwise([1, 2, 3, 4])
# [(1, 2), (2, 3), (3, 4)]

Partition

Split an iterable into (truthy, falsy) lists in one pass.

from philiprehberger_list_chunk import partition

evens, odds = partition(range(6), lambda n: n % 2 == 0)
# evens == [0, 2, 4], odds == [1, 3, 5]

API

Function / Class	Description
chunk(items, size, pad=None)	Fixed-size chunks
chunk_by(items, key)	Group consecutive elements by key
sliding_window(items, size, step=1)	Sliding window views
interleave(*iterables)	Round-robin interleave
flatten(nested)	Flatten one level of nesting
partition(items, predicate)	Split into (truthy, falsy) lists in one pass
transpose(matrix)	Transpose a 2D iterable; jagged input is truncated to the shortest row
pairwise(items)	Return consecutive overlapping (a, b) tuples

Development

pip install -e .
python -m pytest tests/ -v

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License

MIT