Python Comprehensions: Difference between revisions
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Revision as of 01:55, 9 July 2022
Internal
TODO
- 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]