Comprehensions

Python · Reference cheat sheet

📋 Overview

Comprehensions build lists, sets, dicts, and generator expressions concisely. Prefer them over manual loops for simple map/filter transforms. Keep them readable — nest sparingly.

🔧 Core concepts

Scope: iteration variables leak in list/set/dict comps in 3.x? Actually in Python 3, comprehension iteration variables are isolated in their own scope (unlike 2.x).

💡 Examples

List / set / dict:

nums = range(8)
squares = [n * n for n in nums if n % 2 == 0]
unique_lens = {len(w) for w in ["a", "bb", "ccc", "bb"]}
index = {c: i for i, c in enumerate("abc")}

Nested:

matrix = [[1, 2], [3, 4]]
flat = [x for row in matrix for x in row]
pairs = [(i, j) for i in range(3) for j in range(3) if i != j]

Generator expression:

total = sum(n * n for n in range(1_000_000))  # no giant list
lines = (line.strip() for line in open("f.txt", encoding="utf-8"))
# prefer pathlib + context manager in real code

Walrus in comprehension:

def normalize(s: str) -> str:
    return s.strip().lower()

names = [" Ada ", "Bob", "  "]
clean = [n for name in names if (n := normalize(name))]
# ["ada", "bob"]

⚠️ Pitfalls

• Over-nested comps are worse than a plain loop.
• Dict comps: later keys overwrite earlier ones silently.
• Side effects inside comps hurt readability — avoid prints/mutations.
• Generator expressions are single-pass — materialize with list() if reused.
• Huge list comps can exhaust memory; use generators.

🔗 Related

• Lists
• Dictionaries
• Sets
• Generators
• Loops
• Walrus