Python Comprehensions: Difference between revisions
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Revision as of 01:45, 9 July 2022
Internal
TODO
- 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 "<" + 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:
...
Conditional List Comprehension
[<expression> for <var> in <iterable> if <condition>]