Python Dictionary Comprehension

Basic Syntax

The general form is {key_expr: value_expr for item in iterable}. Python evaluates both expressions for every item and builds the resulting dictionary.

squares = {n: n * n for n in range(1, 6)}
print(squares)  # {1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

Filtering Entries

Add an if condition at the end to include only the entries that pass a test — useful for pulling a subset out of a larger dictionary.

scores = {"Aarav": 82, "Riya": 45, "Kabir": 91}
passed = {name: s for name, s in scores.items() if s >= 50}
print(passed)  # {'Aarav': 82, 'Kabir': 91}

Transforming Values

You are not limited to copying values as-is — apply any expression to build a new dictionary derived from an existing one.

marks = {"Aarav": 82, "Riya": 45}
percent = {name: mark / 100 * 100 for name, mark in marks.items()}
print(percent)

Swapping Keys and Values

A classic one-liner: loop over items() and flip the position of the key and value expressions. This only works cleanly when the original values are unique and immutable (hashable).

capitals = {"India": "Delhi", "Japan": "Tokyo"}
reversed_dict = {city: country for country, city in capitals.items()}
print(reversed_dict)  # {'Delhi': 'India', 'Tokyo': 'Japan'}

Comprehension vs a for Loop

A dict comprehension replaces a for loop that builds a new dictionary key by key. Use it when the logic is a single simple expression; fall back to a full loop for anything more complex.

nums = [1, 2, 3]

# for loop
squares = {}
for n in nums:
    squares[n] = n * n

# dict comprehension
squares = {n: n * n for n in nums}