tessl/pypi-more-itertools
Additional building blocks, recipes, and routines for working with Python iterables beyond itertools.
—
Pending
windowing.mddocs/
Windowing Operations
Functions for creating sliding windows and overlapping views of data.
Capabilities
Basic Windowing
Create sliding windows over iterables.
def windowed(iterable, n, fillvalue=None, step=1):
"""
Create sliding window of size n over iterable.
Args:
iterable: Input iterable to window
n: Window size
fillvalue: Value to use for padding incomplete windows
step: Step size between windows
Returns:
Iterator of n-tuples representing windows
"""
def windowed_complete(iterable, n):
"""
Create sliding windows, yielding only complete windows.
Args:
iterable: Input iterable to window
n: Window size
Returns:
Iterator of n-tuples (no incomplete windows)
"""
def sliding_window(iterable, n):
"""
Create sliding window of size n.
Args:
iterable: Input iterable to window
n: Window size
Returns:
Iterator of n-tuples representing sliding windows
"""Usage Examples:
from more_itertools import windowed, sliding_window
# Basic sliding window
data = [1, 2, 3, 4, 5]
windows = list(windowed(data, 3))
# Result: [(1, 2, 3), (2, 3, 4), (3, 4, 5)]
# With fillvalue for incomplete windows
windows = list(windowed(data, 3, fillvalue='X'))
# Result: [(1, 2, 3), (2, 3, 4), (3, 4, 5), (4, 5, 'X'), (5, 'X', 'X')]
# Step size greater than 1
windows = list(windowed(data, 3, step=2))
# Result: [(1, 2, 3), (3, 4, 5)]Pairwise and N-wise Operations
Generate adjacent pairs, triples, and n-tuples.
def pairwise(iterable):
"""
Return successive overlapping pairs from iterable.
Args:
iterable: Input iterable
Returns:
Iterator of 2-tuples (adjacent pairs)
"""
def triplewise(iterable):
"""
Return successive overlapping triples from iterable.
Args:
iterable: Input iterable
Returns:
Iterator of 3-tuples (adjacent triples)
"""Usage Examples:
from more_itertools import pairwise, triplewise
# Adjacent pairs
pairs = list(pairwise([1, 2, 3, 4, 5]))
# Result: [(1, 2), (2, 3), (3, 4), (4, 5)]
# Adjacent triples
triples = list(triplewise([1, 2, 3, 4, 5]))
# Result: [(1, 2, 3), (2, 3, 4), (3, 4, 5)]Staggered Views
Create lagged or offset views of data.
def stagger(iterable, offsets=(0, 1), longest=False, fillvalue=None):
"""
Create multiple offset iterators from single iterable.
Args:
iterable: Input iterable to stagger
offsets: Sequence of offset values
longest: If True, iterate until longest iterator exhausted
fillvalue: Value for padding when longest=True
Returns:
Iterator of tuples with staggered values
"""Usage Examples:
from more_itertools import stagger
# Basic staggering
data = [0, 1, 2, 3, 4, 5]
staggered = list(stagger(data, offsets=(0, 2)))
# Result: [(0, 2), (1, 3), (2, 4), (3, 5)]
# Multiple offsets
staggered = list(stagger(data, offsets=(0, 1, 2)))
# Result: [(0, 1, 2), (1, 2, 3), (2, 3, 4), (3, 4, 5)]
# With longest=True
staggered = list(stagger(data, offsets=(0, 2), longest=True, fillvalue=None))
# Result: [(0, 2), (1, 3), (2, 4), (3, 5), (4, None), (5, None)]Substring Operations
Generate substrings and substring-like operations.
def substrings(iterable):
"""
Generate all non-empty contiguous subsequences.
Args:
iterable: Input iterable
Returns:
Iterator of all contiguous subsequences
"""
def substrings_indexes(seq, reverse=False):
"""
Generate all substrings with their start and end indexes.
Args:
seq: Input sequence
reverse: If True, generate in reverse order
Returns:
Iterator of (substring, start_index, end_index) tuples
"""
def subslices(iterable):
"""
Generate all contiguous subslices as lists.
Args:
iterable: Input iterable
Returns:
Iterator of lists (all contiguous subslices)
"""Usage Examples:
from more_itertools import substrings, substrings_indexes
# All substrings
subs = list(substrings("abc"))
# Result: [('a',), ('a', 'b'), ('a', 'b', 'c'), ('b',), ('b', 'c'), ('c',)]
# With indexes
subs_idx = list(substrings_indexes("abc"))
# Result: [('a', 0, 1), ('ab', 0, 2), ('abc', 0, 3), ('b', 1, 2), ('bc', 1, 3), ('c', 2, 3)]Install with Tessl CLI
npx tessl i tessl/pypi-more-itertools