itertools - Iterator Building Blocks

Functions creating iterators for efficient looping

The itertools module provides fast, memory-efficient tools for creating iterators. These functions work with iterators to produce complex iterators.

Module Import

import itertools

Infinite Iterators

count() - Infinite Counter

import itertools

# Count from 0
for i in itertools.count():
    if i > 5:
        break
    print(i)  # 0, 1, 2, 3, 4, 5

# Count from 10 by 2
for i in itertools.count(10, 2):
    if i > 20:
        break
    print(i)  # 10, 12, 14, 16, 18, 20

# Practical use: enumerate alternative
for i, item in zip(itertools.count(), ['a', 'b', 'c']):
    print(f"{i}: {item}")

cycle() - Cycle Through Iterable

import itertools

# Cycle through values
for i, value in enumerate(itertools.cycle(['A', 'B', 'C'])):
    if i >= 7:
        break
    print(value)  # A, B, C, A, B, C, A

# Practical use: round-robin assignment
tasks = ['task1', 'task2', 'task3', 'task4']
workers = itertools.cycle(['Alice', 'Bob'])
assignments = list(zip(tasks, workers))
# [('task1', 'Alice'), ('task2', 'Bob'), ('task3', 'Alice'), ('task4', 'Bob')]

repeat() - Repeat Value

import itertools

# Repeat indefinitely
for i, value in enumerate(itertools.repeat('X')):
    if i >= 3:
        break
    print(value)  # X, X, X

# Repeat n times
list(itertools.repeat('X', 5))  # ['X', 'X', 'X', 'X', 'X']

# Practical use: with map
result = list(map(pow, [2, 3, 4], itertools.repeat(2)))
print(result)  # [4, 9, 16] (2^2, 3^2, 4^2)

Terminating Iterators

chain() - Chain Iterables

import itertools

# Combine multiple iterables
result = itertools.chain([1, 2, 3], ['a', 'b', 'c'])
list(result)  # [1, 2, 3, 'a', 'b', 'c']

# Chain from iterable of iterables
result = itertools.chain.from_iterable([[1, 2], [3, 4], [5]])
list(result)  # [1, 2, 3, 4, 5]

# Flatten nested lists
nested = [[1, 2], [3, 4], [5, 6]]
flat = list(itertools.chain.from_iterable(nested))
print(flat)  # [1, 2, 3, 4, 5, 6]

compress() - Filter by Selectors

import itertools

data = ['A', 'B', 'C', 'D', 'E']
selectors = [1, 0, 1, 0, 1]
result = itertools.compress(data, selectors)
list(result)  # ['A', 'C', 'E']

# Filter by boolean conditions
numbers = [1, 2, 3, 4, 5, 6]
result = itertools.compress(numbers, [n % 2 == 0 for n in numbers])
list(result)  # [2, 4, 6]

dropwhile() and takewhile()

import itertools

# Drop while condition is true
data = [1, 3, 5, 2, 4, 6]
result = itertools.dropwhile(lambda x: x < 5, data)
list(result)  # [5, 2, 4, 6]

# Take while condition is true
data = [1, 3, 5, 2, 4, 6]
result = itertools.takewhile(lambda x: x < 5, data)
list(result)  # [1, 3]

filterfalse() - Opposite of filter()

import itertools

numbers = [1, 2, 3, 4, 5, 6]

# Keep items where condition is False
result = itertools.filterfalse(lambda x: x % 2 == 0, numbers)
list(result)  # [1, 3, 5] (odd numbers)

islice() - Slice Iterator

import itertools

# Slice iterator without converting to list
data = range(100)
result = itertools.islice(data, 5)  # First 5
list(result)  # [0, 1, 2, 3, 4]

# With start, stop, step
result = itertools.islice(data, 10, 20, 2)
list(result)  # [10, 12, 14, 16, 18]

# Useful for large files
with open('large_file.txt') as f:
    first_10_lines = list(itertools.islice(f, 10))

Combinatoric Iterators

product() - Cartesian Product

import itertools

# Product of iterables
result = itertools.product([1, 2], ['a', 'b'])
list(result)  # [(1, 'a'), (1, 'b'), (2, 'a'), (2, 'b')]

# Product with itself
result = itertools.product([1, 2, 3], repeat=2)
list(result)  # [(1,1), (1,2), (1,3), (2,1), (2,2), (2,3), (3,1), (3,2), (3,3)]

# All combinations of options
colors = ['red', 'blue']
sizes = ['S', 'M', 'L']
for color, size in itertools.product(colors, sizes):
    print(f"{color}-{size}")

permutations() - All Permutations

import itertools

# All permutations of length r
result = itertools.permutations([1, 2, 3], 2)
list(result)  # [(1,2), (1,3), (2,1), (2,3), (3,1), (3,2)]

# All permutations (full length)
result = itertools.permutations([1, 2, 3])
list(result)  # [(1,2,3), (1,3,2), (2,1,3), (2,3,1), (3,1,2), (3,2,1)]

# Permutations of string
list(itertools.permutations('ABC', 2))
# [('A','B'), ('A','C'), ('B','A'), ('B','C'), ('C','A'), ('C','B')]

combinations() - All Combinations

import itertools

# Combinations without replacement
result = itertools.combinations([1, 2, 3, 4], 2)
list(result)  # [(1,2), (1,3), (1,4), (2,3), (2,4), (3,4)]

# Combinations with replacement
result = itertools.combinations_with_replacement([1, 2, 3], 2)
list(result)  # [(1,1), (1,2), (1,3), (2,2), (2,3), (3,3)]

Grouping and Accumulating

groupby() - Group Consecutive Elements

import itertools

# Group by key function
data = [('A', 1), ('A', 2), ('B', 3), ('B', 4), ('C', 5)]
for key, group in itertools.groupby(data, lambda x: x[0]):
    print(f"{key}: {list(group)}")
# A: [('A', 1), ('A', 2)]
# B: [('B', 3), ('B', 4)]
# C: [('C', 5)]

# Group consecutive duplicates
data = [1, 1, 2, 2, 2, 3, 1, 1]
for key, group in itertools.groupby(data):
    print(f"{key}: {len(list(group))}")
# 1: 2
# 2: 3
# 3: 1
# 1: 2

accumulate() - Running Totals

import itertools
import operator

# Cumulative sum (default)
data = [1, 2, 3, 4, 5]
result = itertools.accumulate(data)
list(result)  # [1, 3, 6, 10, 15]

# Cumulative product
result = itertools.accumulate(data, operator.mul)
list(result)  # [1, 2, 6, 24, 120]

# Cumulative maximum
data = [5, 2, 8, 1, 9, 3]
result = itertools.accumulate(data, max)
list(result)  # [5, 5, 8, 8, 9, 9]

Practical Examples

Pagination

import itertools

def paginate(iterable, page_size):
    """Split iterable into pages"""
    iterator = iter(iterable)
    while True:
        page = list(itertools.islice(iterator, page_size))
        if not page:
            break
        yield page

# Usage
items = range(25)
for page_num, page in enumerate(paginate(items, 10), 1):
    print(f"Page {page_num}: {page}")

Round Robin

import itertools

def roundrobin(*iterables):
    """Round-robin across iterables"""
    iterators = [iter(it) for it in iterables]
    while iterators:
        result = []
        for it in iterators:
            try:
                result.append(next(it))
            except StopIteration:
                iterators.remove(it)
        if result:
            yield from result

# Usage
list(roundrobin('ABC', 'D', 'EF'))
# ['A', 'D', 'E', 'B', 'F', 'C']

Sliding Window

import itertools

def sliding_window(iterable, n):
    """Return sliding window of size n"""
    it = iter(iterable)
    window = list(itertools.islice(it, n))
    if len(window) == n:
        yield tuple(window)
    for item in it:
        window = window[1:] + [item]
        yield tuple(window)

# Usage
for window in sliding_window([1, 2, 3, 4, 5], 3):
    print(window)
# (1, 2, 3)
# (2, 3, 4)
# (3, 4, 5)

Flatten Nested Structure

import itertools

def flatten(nested):
    """Flatten nested iterable"""
    for item in nested:
        if isinstance(item, (list, tuple)):
            yield from flatten(item)
        else:
            yield item

# Usage
nested = [1, [2, 3, [4, 5]], 6, [7, [8, 9]]]
list(flatten(nested))  # [1, 2, 3, 4, 5, 6, 7, 8, 9]

Generate All Subsets

import itertools

def powerset(iterable):
    """Generate all subsets (power set)"""
    items = list(iterable)
    return itertools.chain.from_iterable(
        itertools.combinations(items, r)
        for r in range(len(items) + 1)
    )

# Usage
list(powerset([1, 2, 3]))
# [(), (1,), (2,), (3,), (1,2), (1,3), (2,3), (1,2,3)]

Pairwise Iteration

import itertools

def pairwise(iterable):
    """Return successive overlapping pairs"""
    a, b = itertools.tee(iterable)
    next(b, None)
    return zip(a, b)

# Usage
list(pairwise([1, 2, 3, 4, 5]))
# [(1, 2), (2, 3), (3, 4), (4, 5)]

Best Practices

itertools is memory efficient: Iterators don’t create intermediate lists, saving memory.

# Memory efficient
for item in itertools.chain(list1, list2, list3):
    process(item)

# Memory intensive
for item in list1 + list2 + list3:
    process(item)

Use itertools for complex iterations:

# Clean and readable
for a, b, c in itertools.product(range(3), repeat=3):
    print(a, b, c)

# Instead of nested loops
for a in range(3):
    for b in range(3):
        for c in range(3):
            print(a, b, c)

Complete Function List

Infinite Iterators

• count(start=0, step=1) - Count infinitely
• cycle(iterable) - Cycle through iterable
• repeat(object, times=None) - Repeat object

Terminating Iterators

• accumulate(iterable, func=operator.add) - Running totals
• chain(*iterables) - Chain iterables
• chain.from_iterable(iterable) - Chain from iterable
• compress(data, selectors) - Filter by selectors
• dropwhile(predicate, iterable) - Drop while true
• filterfalse(predicate, iterable) - Filter false values
• groupby(iterable, key=None) - Group consecutive
• islice(iterable, stop) - Slice iterator
• pairwise(iterable) - Successive pairs (Python 3.10+)
• starmap(function, iterable) - Map with unpacking
• takewhile(predicate, iterable) - Take while true
• tee(iterable, n=2) - Split iterator
• zip_longest(*iterables, fillvalue=None) - Zip with padding

Combinatoric Iterators

• product(*iterables, repeat=1) - Cartesian product
• permutations(iterable, r=None) - Permutations
• combinations(iterable, r) - Combinations
• combinations_with_replacement(iterable, r) - Combinations with replacement

Related Modules

functools

Higher-order functions

collections

Specialized containers

operator

Function equivalents of operators