10 Python itertools Tricks I Wish I Knew Sooner! 🚀

Boost your Python skills with itertools magic!

10 Python itertools Tricks I Wish I Knew Sooner! 🚀

If you’ve ever worked with large datasets, nested loops, or complex iterations in Python, you’ve probably faced situations where regular loops feel too slow or clunky. This is where itertools comes to the rescue!

Python’s itertools module provides powerful functions that make working with iterators faster, memory-efficient, and more readable.

In this article, I'll share 10 essential itertools tricks that I wish I had learned earlier—saving countless hours of coding!

1. itertools.count() – Infinite Counting Made Easy

If you need an infinite counter that keeps going? count() generates numbers indefinitely.

from itertools import count 
 
for num in count(start=1, step=2): 
    print(num, end=" ") 
    if num > 10: 
        break  # Stop the infinite loop 
 
# output - 1 3 5 7 9 11

Unlike range(), which requires predefined limits, count() is infinite and lazy, making it ideal for iterating over infinite sequences.

2. itertools.cycle() – Loop Over an Iterable Infinitely

When you need to cycle through a list indefinitely.

from itertools import cycle 
 
colors = ["red", "green", "blue"] 
color_cycle = cycle(colors) 
 
for _ in range(6):  # Print 6 colors 
    print(next(color_cycle))

# output 
red 
green 
blue 
red 
green 
blue

This is perfect for round-robin scheduling, alternating elements, or endless UI animations.

3. itertools.repeat() – Repeat a Value Efficiently

Instead of creating a list of repeated values, use repeat() to save memory.

from itertools import repeat 
 
for msg in repeat("Hello", 3): 
    print(msg)

# output 
Hello 
Hello 
Hello

It is more efficient than [value] * n since it doesn’t create an actual list in memory.

4. itertools.accumulate() – Running Totals in One Line

If you need a cumulative sum (or product) of numbers? accumulate() do it for you easily.

from itertools import accumulate 
 
nums = [1, 2, 3, 4, 5] 
print(list(accumulate(nums)))   
 
# output - [1, 3, 6, 10, 15]

You can also use accumulate() for multiplication:

import operator 
 
print(list(accumulate(nums, operator.mul)))   
 
# output - [1, 2, 6, 24, 120]

It is very helpful to makes rolling calculations like cumulative sales, moving averages, or running totals effortless!

5. itertools.chain() – Flatten Nested Iterables

If you want to combine multiple lists into a single list ? chain() do it for you easily.

from itertools import chain 
 
list1 = [1, 2, 3] 
list2 = [4, 5, 6] 
combined = list(chain(list1, list2)) 
 
print(combined)   
 
# output - [1, 2, 3, 4, 5, 6]

It can works with any iterable (tuples, sets, generators), avoiding the overhead of creating a new list manually.

6. itertools.product() – Cartesian Product (All Pair Combinations)

If you want to generate all possible pairs between two lists. product() function generate it for you.

from itertools import product 
 
sizes = ["S", "M", "L"] 
colors = ["Red", "Blue"] 
 
print(list(product(sizes, colors)))

# output 
[('S', 'Red'), ('S', 'Blue'), ('M', 'Red'), ('M', 'Blue'), ('L', 'Red'), ('L', 'Blue')]

7. itertools.permutations() – All Possible Orderings

If you need all orderings of elements in a sequence? permutations() function is perfect for this.

from itertools import permutations 
 
items = ["A", "B", "C"] 
print(list(permutations(items)))

# output 
[('A', 'B', 'C'), ('A', 'C', 'B'), ('B', 'A', 'C'), ('B', 'C', 'A'), ('C', 'A', 'B'), ('C', 'B', 'A')]

It is perfect for solving puzzles, generating passwords, or testing order-dependent operations.

8. itertools.combinations() – Unique Groups of Items

If you want generate all unique combinations of elements without repetition.

from itertools import combinations 
 
letters = ["A", "B", "C"] 
print(list(combinations(letters, 2)))  # Pick 2 elements at a time

# output 
[('A', 'B'), ('A', 'C'), ('B', 'C')]

It is essential for lottery simulations, choosing teams, or forming unique pairs.

9. itertools.groupby() – Group Elements Together

If you want to group consecutive similar items together.

from itertools import groupby 
 
data = "aaabbccccdaa" 
grouped = [(key, list(group)) for key, group in groupby(data)] 
 
print(grouped)

# output 
[('a', ['a', 'a', 'a']), ('b', ['b', 'b']), ('c', ['c', 'c', 'c', 'c']), ('d', ['d']), ('a', ['a', 'a'])]

10. itertools.tee() – Duplicate an Iterator

If you need to iterate over the same generator twice without consuming it? you can do it easily with tee() .

from itertools import tee 
 
data = iter([1, 2, 3, 4]) 
iter1, iter2 = tee(data, 2) 
 
print(list(iter1))  # output - [1, 2, 3, 4] 
print(list(iter2))  # output - [1, 2, 3, 4]

Normally, generators get exhausted after one iteration, but tee() lets you reuse them.

Wrapping Up: Why itertools is a Game-Changer!

Python’s itertools module is a hidden powerhouse for efficient iteration.

If you haven’t explored itertools yet, now is the perfect time! 🚀

Which itertools trick did you find the most useful? Drop a comment below! 👇