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Python Comprehensions: List, Dict and Set Comprehensions Explained

Learn Python comprehensions: build lists in one line, filter with if, transform with if-else, dictionary and set comprehensions, nested comprehensions and flattening, generator expressions with sum/any/all, and when a loop is clearer.

Intermediate6 min readUpdated
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A comprehension builds a new list, dictionary or set from an existing iterable in a single, readable line. It replaces the common pattern of "create an empty list, loop, append".

From loop to comprehension#

Python
result = []
for n in range(1, 6):
    if n % 2:
        result.append(n * 10)

print(result, [n * 10 for n in range(1, 6) if n % 2])
Output
[10, 30, 50] [10, 30, 50]

Both produce the same list. Read the comprehension as: "n * 10 for each n in range(1, 6), if n is odd".

List comprehensions#

The general form is:

Python
[expression for item in iterable if condition]
Python
squares = [n * n for n in range(1, 6)]
print(squares)
Output
[1, 4, 9, 16, 25]

Filtering with if#

An if at the end keeps only some items:

Python
nums = [4, -2, 7, 0, -5, 9]
print([n for n in nums if n > 0])
Output
[4, 7, 9]

Transforming with if-else#

A conditional expression at the start changes each item but keeps them all:

Python
print([n if n > 0 else 0 for n in nums])
Output
[4, 0, 7, 0, 0, 9]
WhereSyntaxEffect
at the end[x for x in items if cond]filters: fewer items
at the start[a if cond else b for x in items]transforms: same number of items

Methods work as usual inside the expression:

Python
words = ["Python", "SQL", "Go", "JavaScript"]
print([w.lower() for w in words if len(w) > 2])
Output
['python', 'sql', 'javascript']

Dictionary comprehensions#

Use key: value inside curly braces:

Python
prices = {"tea": 20, "coffee": 35, "juice": 50}

with_tax = {item: round(p * 1.18, 2) for item, p in prices.items()}
print(with_tax)

cheap = {k: v for k, v in prices.items() if v < 40}
print(cheap)

inverted = {v: k for k, v in prices.items()}
print(inverted)
Output
{'tea': 23.6, 'coffee': 41.3, 'juice': 59.0}
{'tea': 20, 'coffee': 35}
{20: 'tea', 35: 'coffee', 50: 'juice'}

Set comprehensions#

Curly braces without a colon build a set, so duplicates disappear:

Python
words = ["apple", "avocado", "banana", "blueberry", "cherry"]
print(sorted({w[0] for w in words}))
print(sorted({len(w) for w in words}))
Output
['a', 'b', 'c']
[5, 6, 7, 9]

(Sets have no order, so they are sorted here for display.)

Nested comprehensions#

Several for clauses read left to right, like nested loops. Flattening a list of lists:

Python
matrix = [[1, 2, 3], [4, 5, 6]]

print([n for row in matrix for n in row])
print([[row[i] for row in matrix] for i in range(3)])   # transpose
print([(x, y) for x in "ab" for y in (1, 2)])
Output
[1, 2, 3, 4, 5, 6]
[[1, 4], [2, 5], [3, 6]]
[('a', 1), ('a', 2), ('b', 1), ('b', 2)]

[n for row in matrix for n in row] is the same as:

Python
for row in matrix:
    for n in row:
        ...

Generator expressions with sum, any and all#

Parentheses instead of brackets give a lazy generator expression. They pair perfectly with functions that consume values:

Python
total = sum(n * n for n in range(1, 11))
print(total, any(n > 90 for n in [40, 95]), all(n > 0 for n in [3, 0]))
Output
385 True False

When to use a loop instead#

Comprehensions are for building a collection. Prefer a normal loop when:

  • the logic needs several statements, try/except, or prints;
  • there are more than two for clauses or complex conditions;
  • you are not building a collection at all (for example, only printing or saving).

A comprehension that needs a minute to understand has lost its advantage.

Common mistakes#

Practice#

Practice exercise

Given this list of students, build (1) a list of the names of those who passed (score ≥ 40) and (2) a dictionary mapping every name to a grade: "A" for 90+, "B" for 50+, otherwise "F".

Python
students = [{"name": "Asha", "score": 92}, {"name": "Ravi", "score": 58},
            {"name": "Meera", "score": 97}, {"name": "John", "score": 34}]
Show hint

The list needs a filter at the end. The dictionary needs a chained conditional expression in the value: "A" if ... else "B" if ... else "F".

Show solution
Python
passed = [s["name"] for s in students if s["score"] >= 40]

grades = {s["name"]: ("A" if s["score"] >= 90 else "B" if s["score"] >= 50 else "F")
          for s in students}

print(passed)
print(grades)
Output
['Asha', 'Ravi', 'Meera']
{'Asha': 'A', 'Ravi': 'B', 'Meera': 'A', 'John': 'F'}

Key takeaway#

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