If you’re working with loops, sequences, or data processing in Python, the itertools module is your hidden superpower. Built into the standard library, itertools provides fast, memory-efficient tools for working with iterators — making your code cleaner and more performant.
This beginner-friendly guide introduces some of the most useful functions in itertools, with clear examples to help you apply them in real-world tasks like data filtering, grouping, and combinations.
What is itertools?
itertools is a Python module that provides a collection of fast, memory-efficient tools that are ideal for looping and manipulating data streams. Instead of using bulky for loops and nested logic, itertools offers elegant and reusable solutions.
Getting Started
You don’t need to install anything — just import the module:
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import itertools
Commonly Used itertools Functions
1. count()
Creates an infinite iterator that returns evenly spaced values.
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for i in itertools.count(start=10, step=2):
print(i)
if i > 20:
break
2. cycle()
Repeats elements from an iterable indefinitely.
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for i, val in zip(range(5), itertools.cycle([‘A’, ‘B’, ‘C’])):
print(val)
3. repeat()
Repeats a value a specified number of times.
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for item in itertools.repeat(‘Hello’, 3):
print(item)
4. chain()
Combines multiple iterables into one seamless sequence.
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a = [1, 2, 3]
b = [4, 5]
for val in itertools.chain(a, b):
print(val)
5. combinations() and permutations()
Used for generating unique combinations or permutations of elements.
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from itertools import combinations, permutations
items = [‘A’, ‘B’, ‘C’]
print(list(combinations(items, 2))) # [(‘A’, ‘B’), (‘A’, ‘C’), (‘B’, ‘C’)]
print(list(permutations(items, 2))) # [(‘A’, ‘B’), (‘A’, ‘C’), …]
6. groupby()
Groups adjacent elements based on a key function.
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data = [(‘fruit’, ‘apple’), (‘fruit’, ‘banana’), (‘veg’, ‘carrot’), (‘veg’, ‘spinach’)]
for key, group in itertools.groupby(data, lambda x: x[0]):
print(key, list(group))
Why Use itertools?
- Memory Efficient: Works with iterators and streams, not full lists
- Elegant Code: Reduces the need for manual loops and conditionals
- Highly Composable: Many functions can be combined for powerful logic
Practice Challenge
Try this:
Use chain() to merge two lists, then apply filter() to extract even numbers. This will help reinforce the power of combining iterable tools for practical tasks.
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