Comprehensions Intro

Comprehensions Intro

What it means

A comprehension is a compact syntax for building a new list, dict, or set by transforming and optionally filtering an existing iterable — in one expression instead of a multi-line for loop. They exist for lists ([...]), sets ({...}), and dicts ({k: v for ...}).

Examples

# List comprehension
squares = [n * n for n in range(6)]                 # [0, 1, 4, 9, 16, 25]

# With a filter condition
evens = [n for n in range(10) if n % 2 == 0]         # [0, 2, 4, 6, 8]

# Dict comprehension
lengths = {word: len(word) for word in ["hi", "hello", "hey"]}
# {'hi': 2, 'hello': 5, 'hey': 3}

# Set comprehension
unique_lengths = {len(word) for word in ["hi", "hey", "yo"]}   # {2, 3}

Common mistake

Writing a comprehension so dense with nested loops or conditions that it becomes harder to read than the plain for loop it replaced — comprehensions are for simple transform/filter operations, not everything.

# Hard to read -- nested loop, unclear intent
result = [x*y for x in range(5) for y in range(5) if x != y if (x+y) % 2 == 0]

# Clearer as a regular loop
result = []
for x in range(5):
    for y in range(5):
        if x != y and (x + y) % 2 == 0:
            result.append(x * y)

Quick practice

1. What’s the difference between [x for x in items] and {x for x in items}?

   Answer

   The first builds a list (ordered, duplicates allowed); the second builds a set (unordered, duplicates automatically removed).

2. How do you filter items inside a comprehension?

   Answer

   Add an if condition at the end: [x for x in items if condition].

3. When should you prefer a regular for loop over a comprehension?

   Answer

   When the logic involves multiple nested conditions/loops or side effects (like printing or writing to a file) — comprehensions should stay simple and side-effect-free.