Comprehensions: Building Collections in One Line

Why this matters

A very common loop builds a new list from an old one: double every price, keep only the big ones. A comprehension says the same thing in a single readable line. You will see them everywhere in real Python code.

The idea

The loop you already know:

squares = []
for n in [1, 2, 3, 4]:
    squares.append(n * n)

The comprehension that does the same:

squares = [n * n for n in [1, 2, 3, 4]]   # [1, 4, 9, 16]

Read it as: “n * n for each n in the list”. Add an if to filter:

big = [n for n in [1, 5, 8, 2] if n > 4]  # [5, 8]

The same shape builds other collections:

lengths = {w: len(w) for w in ["hi", "hello"]}  # {'hi': 2, 'hello': 5}
unique = {n % 3 for n in range(10)}             # {0, 1, 2}

Use a comprehension when it fits on one line and stays easy to read. If it gets complicated, a normal loop is kinder to the next reader (that includes you).

Try it

Write a comprehension that makes upper-case versions of ["a", "b", "c"]. Then one that keeps only the words longer than 3 letters from ["tree", "sun", "forest"].

Your turn

The starter reads some numbers and some words. Using comprehensions, print two lines. For numbers 1 2 3 4 and words cat horse:

Even squares: [4, 16]
Lengths: {'cat': 3, 'horse': 5}

“Even squares” is the square of each even number, in the original order. “Lengths” maps each word to its length (words in the order given).

Recap

• [expression for item in items if condition] builds a new list in one line.
• Curly braces with key: value make a dict; without it they make a set.
• Prefer a plain loop when the comprehension stops being easy to read.

Common mistakes

• Putting the if in the wrong place. A filter goes at the end: [n for n in nums if n > 0].
• Side effects inside a comprehension, such as printing. Build the collection, then use it.
• Over-clever one-liners. Clear beats short.