Python comprehensions

The purpose of this article is to follow up on my previous article, Understanding map, filter, and zip in Python, and show you a more concise way of similar functionality.

List Comprehensions

In the previous article, I covered map and filter, so now I can show you how we can emulate the same functionality with list comprehensions.

Have a look at the structure of a comprehension here. Its comprised of 3 main parts.

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

def square(number):
    return number*number

Using a loop to square

...
squared_numbers = []
for number in numbers:
    squared = square(number)
    squared_numbers.append(squared

Using map()

...
squared_numbers = map(square, numbers)

Using a list comprehension

squared_numbers = [x*x  for x in numbers]

Note: I use x*x here for readability, however, you can more appropriately use the power of operator ** for this. [x**2].

Lets now re-use our even or odd filter example from the last article to show how comprehensions can use a condition as well. We'll get the squared number of ONLY even numbers in our list.

Using filter() and map()

...
def even(number):
    if (number % 2) == 0:
        return True
    return False

even_numbers = filter(even, numbers)
even_numbers_squared = map(square, even_numbers)

Using comprehensions

...
even_numbers_squared = [x**2 for x in numbers if (x % 2) == 0]

Conclusion

So with this you should have a basic grasp on how comprehensions work, how they're structured, and how they can help you write more concise code!