Master Python List Comprehensions: 3 Techniques, Examples, and Exercises

1. Introduction

List comprehensions are a built‑in, simple yet powerful way to create lists in Python.

2. Case Study

Three Methods

To generate the list [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] you can use list(range(1, 11)):

print(list(range(1, 11)))

How to generate [1×1, 2×2, …, 10×10]?

1. Method One – Loop

L = []
for x in range(1, 11):
    L.append(x * x)
print(L)

Loops are verbose; a list comprehension can replace the loop in one line:

print([x * x for x in range(1, 11)])

In a list comprehension the expression appears first, followed by the for clause.

You can also add an if clause to filter, e.g., squares of even numbers:

print([x * x for x in range(1, 11) if x % 2 == 0])

2. Two‑level loop – Cartesian product

L = []
for x in range(1, 11):
    L.append(x * x)
print([m + n for m in 'ABC' for n in 'XYZ'])

Three‑level (or deeper) loops are rarely needed.

3. Concise code with list comprehensions

Example: list all files and directories in the current folder:

import os
print([d for d in os.listdir('.')])

For dictionaries you can iterate over key and value simultaneously:

d = {'x': 'A', 'y': 'B', 'z': 'C'}
for k, v in d.items():
    print(k, '=', v)

Using two variables in a comprehension:

print([k + '=' + v for k, v in d.items()])

Convert all strings in a list to lowercase:

L = ['Hello', 'World', 'IBM', 'Apple']
print([s.lower() for s in L])

If the list contains non‑string items, calling lower() raises an error. Use isinstance to filter strings:

L = ['Hello', 'World', 18, 'Apple', None]
print([s.lower() for s in L])

x = 'abc'
y = 123
print(isinstance(x, str))
print(isinstance(y, str))

3. Exercise

Modify the list comprehension to include an if clause so that only string elements are converted to lowercase.

# -*- coding: utf-8 -*-
L1 = ['Hello', 'World', 18, 'Apple', None]
L2 = ???
# Expected output: ['hello', 'world', 'apple']
print(L2)

Reference solution:

L2 = [s.lower() for s in L1 if isinstance(s, str)]

4. Conclusion

This article introduced Python list comprehensions, demonstrated three approaches, discussed common pitfalls, and provided an exercise to deepen understanding.