Python Comprehensions

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• Python Language

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• PROCESS IPy Comprehensions Page 84.
• PROCESS PyOOP "Comprehensions" + "List comprehensions" + "Set and dictionary comprehensions"

Overview

A comprehension is a compact way of creating a data structure from one or more iterators. They are essentially loops with a more compact syntax.

List Comprehensions

A list comprehension produces a list from an iterable type by applying an expression to each of the elements, and optionally a condition.

Simple List Comprehension

[<expression> for <var> in <iterable>]

The list comprehension moves the loop inside square brackets. This example iterates over a list of custom object instances and produces a comma-separated list of their __str__() representations, which printing the list with print() does not do:

class C:
  def __init__(self, i):
    self.i = i 
  def __str__(self):
    return str(self.i)

l = [C(1), C(2), C(3)]

print(l)

displays:

[<__main__.C object at 0x102f06b20>, <__main__.C object at 0x1030159d0>, <__main__.C object at 0x10302c9a0>]

The following list comprehension:

print(', '.join([str(i) for i in l]))

displays:

1, 2, 3

Conditional List Comprehension

[<expression> for <var> in <iterable> if <condition>]

An example of a conditional list comprehension is to generate a list of even numbers from a list of numbers:

l = list(range(10))
print(l)

displays:

[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

To get the even numbers:

l2 = [i for i in l if i % 2 == 0]
print(l2)

displays:

[0, 2, 4, 6, 8]

Nested List Comprehensions

Just as there can be nested loops, there can be more than on set of for ... clauses.

rows = range(1, 4)
cols = range(1, 3)
cells = [(row, col) for row in rows for col in cols]