Comprehensions

Comprehensions are a Python language construct for concisely creating data in lists, dictionaries and sets. List comprehensions are included in Python 2 while dictionary and set comprehensions were introduced to the language in Python 3.

Why are comprehensions important?

Comprehensions are a more clear syntax for populating conditional data in the core Python data structures. Creating data without comprehensions often involves nested loops with conditionals that can be difficult for code readers to properly evaluate.

Example code

List comprehension:

>>> double_digit_evens = [e*2 for e in range(5, 50)]
>>> double_digit_evens
[10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50, 52, 54, 56, 58, 60, 62, 64, 66, 68, 70, 72, 74, 76, 78, 80, 82, 84, 86, 88, 90, 92, 94, 96, 98]

Set comprehension:

>>> double_digit_odds = {e*2+1 for e in range(5, 50)}
{11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99}

Dictionary comprehension:

>>> {e: e*10 for e in range(1, 11)}
{1: 10, 2: 20, 3: 30, 4: 40, 5: 50, 6: 60, 7: 70, 8: 80, 9: 90, 10: 100}

Comprehension resources

• Intermediate Python's Python Comprehensions post gives a well written overview of comprehensions for the three core Python data structures.

• The Python 3 Patterns and Idioms site has an overview of comprehensions including code examples and diagrams to explain how they work.

• Learning Python by example: list comprehensions gives an example of an incorrect list comprehension then shows how to correct its issues.

• List comprehensions in Python covers what the code for list comprehensions looks like and gives some example code to show how they work.

• An Introduction to Python Lists is a solid overview of Python lists in general and tangentially covers list comprehensions.

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