Comprehensions

The long way first

A very common task is building a new list from an old one — for example, the squares of some numbers. The plain way is a loop with .append():

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

This works fine: we start with an empty list squares, loop over each number n, and append n * n each time. After the loop, squares holds the four squared values. But it took four lines to express one simple idea.

A comprehension does it in one line

A list comprehension is a compact way to write that exact loop inside the square brackets. It reads almost like English: “give me n * n for each n in numbers.”

numbers = [1, 2, 3, 4]
squares = [n * n for n in numbers]
print(squares)

Read the part inside the brackets left to right: n * n is what to collect, and for n in numbers is where the values come from. Python runs the loop for you, squares each number, and gathers the results into a brand-new list. Same output as the four-line version — just clearer and shorter.

Add a filter with if

You can keep only some items by adding an if at the end — it acts as a filter, letting through only the values that pass the test.

numbers = [1, 2, 3, 4, 5, 6]
evens = [n for n in numbers if n % 2 == 0]
print(evens)

The new part is if n % 2 == 0 on the end. Remember % gives the remainder and an even number divided by 2 leaves remainder 0, so this keeps only the even numbers. Python checks each n, lets the evens through, and collects them — giving [2, 4, 6]. Odd numbers are silently skipped.

A realistic example

Comprehensions shine on real data. Say you have a list of prices and want a new list with 10% tax added, but only for items over 100:

prices = [50, 120, 200, 80]
taxed = [round(p * 1.1, 2) for p in prices if p > 100]
print(taxed)

Here if p > 100 keeps only 120 and 200. For each of those, p * 1.1 adds 10% and round(..., 2) rounds to two decimal places. The result is a clean new list of taxed prices for the expensive items only — a transform and a filter together in one readable line.

Set and dict comprehensions

The same idea works with curly braces to build a set (unique values) or a dictionary (key–value pairs). For a dict you supply both a key and a value with a colon.

words = ["apple", "mango", "apple"]
lengths = {w: len(w) for w in words}
print(lengths)

unique_lengths = {len(w) for w in words}
print(unique_lengths)

The first comprehension uses w: len(w) — for each word it stores the word as the key and its length as the value, building a dictionary. Because dictionaries cannot have duplicate keys, the repeated apple simply appears once. The second uses curly braces with a single value, len(w), so it builds a set of the distinct lengths.