Solved: List Comprehension

Sound sophisticated? That’s Python list comprehension for you. This highly efficient feature condenses the creation of lists into a single line of code. It’s a simplified approach that streamlines both speed and performance.

List comprehension involves comprehending components of a list and generating a new list from the original one. It combines elements of mapping and filtering to create a new list based on an existing list, with an added condition. Its main components are Output Expression, Input Sequence, and Optional Predicate.

new_list = [expression for member in iterable]

Before we dive deeper into the workings of list comprehension, let’s clear up some terms:

Output Expression:

This is like the operative part of list comprehension. It decides what items will be part of the new list. It can be anything from mathematical operations (like squaring numbers) to string formatting and more.

Input Sequence:

The input sequence allows us to define the list or range over which we want to iterate.

Optional Predicate:

This part lets us apply a condition to the input sequence – like a filter. The condition can filter out items based on certain criteria.

Consider an example where we want to square each number in a list. Without list comprehension, we’d have to use a for loop:

numbers = [1, 2, 3, 4, 5]
squared = []

for num in numbers:
    squared.append(num ** 2)


But with list comprehension, we can easily write this:

numbers = [1, 2, 3, 4, 5]
squared = [num ** 2 for num in numbers]


Now, consider an example where we only want to square the numbers that are greater than 2:

numbers = [1, 2, 3, 4, 5]
squared = [num ** 2 for num in numbers if num > 2]


Wrapping it up

Python list comprehension provides an elegantly concise solution for creating lists. It is faster and more readable (once you’re familiar with it) than traditional loops. With an output expression, an input sequence, and an optional predicate, you can perform powerful and effective operations in a single line of code. Python list comprehension is proof that, in coding, seldom do succinctness and efficiency not go hand in hand.

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