Python List Comprehensions

A list comprehension is a way to compress a list building for loop into a shorter line of code.

Example list building for loop

L = []
for n in range(12):
    L.append(n ** 2)

The equivalent list comprehension

L = [n ** 2 for n in range(12)]

Basic syntax:
[expression for variable in iterable ]

A list can be built from multiple values

[(i,j) for i in range(2) for j in range(3)]

This is equivalent to nested for loops; the interior index varies the fastest.

A conditional can be added to the end of the expression

>>> [val for val in range(20) if val % 3 > 0]
[1, 2, 4, 5, 7, 8, 10, 11, 13, 14, 16, 17, 19]

This is equivalent to the following loop:

L = []
for val in range(20):
    if val % 3 > 0:
        L.append(val)

Python has a conditional expression (note, not statement)

>>> val = -10
>>> val if val >= 0 else -val
10

This is often used within list comprehensions and lambda functions

>>> [v if v % 2 else -v for v in range(10)]
[1, -2, 3, -4, 5, -6, 7, -8, 9]

set comprehensions

>>> {n ** 2 for n in range(10)}
{0, 1, 4, 9, 16, 25, 36, 49, 64, 81}

dict comprehensions

>>> {n:n ** 2 for n in range(6)}
{0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

generator expression

>>> (n**2 for n in range(12))
<generator object <genexpr> at 0x1027a5a50>

A list is a collection of values

A generator produces values as they are needed

A generator exposes the iterator interface

for val in (n ** 2 for n in range(10)):
    print(val, end=' ')

A generator can only be iterated through once

A generator function makes use of the yield statement

The generator expression

G1 = (n ** 2 for n in range(10))

is equivalent to

def gen():
    for n in range(10):
        yield n ** 2

G2 = gen()