more-itertools
Extends Python's itertools with 60+ additional iterator building blocks — provides windowed, chunked, batched, flatten, one, peekable, side_effect, distribute, roundrobin, and many more. more-itertools features: windowed/sliding window over iterables, chunked/batched for fixed-size groups, peekable for look-ahead, one/first/last/only for safe single-item extraction, side_effect for debugging iterators, flatten/collapse for nested iterables, zip_offset for shifted zipping, intersperse for separators, ilen for iterator length, partition for predicate splitting, spy for non-consuming peek, and 40+ more. All return lazy iterators.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Pure Python iterator library with no network calls and minimal dependencies. No security concerns. side_effect() executes arbitrary function per item — validate side effect functions in agent code.
⚡ Reliability
Best When
Complex iterator manipulation and lazy data pipeline construction — more-itertools fills the gap between itertools and needing custom iterator code for windowing, batching, and safe extraction.
Avoid When
NumPy array operations, async iterables, or when itertools + list comprehensions already solve the problem.
Use Cases
- • Agent batch processing — from more_itertools import chunked; data = range(10000); for batch in chunked(data, 100): process_batch(list(batch)) — fixed-size batches; agent processes large datasets in chunks without loading all into memory; chunked returns iterator of lists; last chunk may be smaller than chunk_size
- • Agent sliding window — from more_itertools import windowed; prices = [100, 102, 98, 105, 103]; for window in windowed(prices, n=3): moving_avg = sum(w for w in window if w) / 3 — sliding window; agent computes rolling statistics over time series; windowed(seq, n) yields n-tuples with None padding at end
- • Agent safe single extraction — from more_itertools import one, first, last; result = one(filtered_items) — raises ValueError if not exactly one; first_match = first(items, default=None) — safe single extraction; agent validates exactly one match or safely gets first/last; one() raises if 0 or >1 items
- • Agent peekable iterator — from more_itertools import peekable; it = peekable(stream); if it.peek(None) is not None: process(next(it)) — look-ahead; agent inspects next item without consuming; peekable.peek(default) returns next without advancing; useful for parsers and state machines
- • Agent interleaving streams — from more_itertools import roundrobin; a = [1, 3, 5]; b = [2, 4, 6]; interleaved = list(roundrobin(a, b)) — [1, 2, 3, 4, 5, 6]; agent merges multiple ordered streams; roundrobin distributes equally from each iterable in turn
Not For
- • NumPy array operations — more-itertools works with Python iterables not arrays; for array windowing use numpy.lib.stride_tricks
- • Async iterables — more-itertools is synchronous; for async itertools use aioitertools or asyncio-specific utilities
- • Parallel processing — more-itertools is sequential; for parallel iteration use concurrent.futures with chunks
Interface
Authentication
No auth — pure Python iterator library.
Pricing
more-itertools is MIT licensed. Free for all use.
Agent Metadata
Known Gotchas
- ⚠ Iterators are consumed once — more_itertools functions return lazy iterators; calling list() twice on same iterator returns empty list second time; agent code: materialize with list() if multiple passes needed; chunked(data, 100) — each call to chunked creates new iterator; but underlying data= must be re-iterable
- ⚠ windowed() pads end with None by default — windowed([1,2,3], 4) yields (1,2,3,None); filter None: windowed(seq, n, fillvalue=None); agent code summing windows must handle None: sum(x for x in window if x is not None); or use windowed_complete() for only complete windows
- ⚠ one() error message is informative — one(iter([1,2])) raises ValueError: 'Expected exactly one item in iterable, but got two or more'; one(iter([])) raises ValueError: 'Expected exactly one item... but got zero'; agent code using one() for validation: catch ValueError for graceful handling; error messages distinguish 0 vs 2+ items
- ⚠ chunked() last chunk may be smaller — chunked([1,2,3,4,5], 2) yields [1,2], [3,4], [5]; last chunk [5] has 1 item not 2; agent code expecting uniform chunk size: use chunked_even() or pad last chunk; or filter: (chunk for chunk in chunked(data, n) if len(chunk) == n)
- ⚠ import more_itertools not more-itertools — pip install more-itertools; import more_itertools (underscore not hyphen); from more_itertools import chunked, windowed; agent requirements.txt: more-itertools>=10.0; import uses underscore
- ⚠ peekable consumes from source — peekable wraps an iterator; once created, the original iterator should not be used directly; agent code: it = peekable(original); do not also iterate original separately; peekable.prepend(item) inserts item to be yielded next — useful for parser lookahead that needs to 'unget'
Alternatives
Full Evaluation Report
Detailed scoring breakdown, competitive positioning, security analysis, and improvement recommendations for more-itertools.
Scores are editorial opinions as of 2026-03-06.