# Python list comprehensions

In this tutorial, we will learn to use Python list comprehensions.

A list comprehension is a syntactic construct which creates a list based on existing list. List comprehensions provide a concise way to create lists. It is a common requirement to make new lists where each element is the result of some operations applied to each member of another sequence or iterable, or to create a subsequence of those elements that satisfy a certain condition.

A list comprehension can be used to:

- transform a list
- filter a list

The syntax of a list comprehension was influenced by mathematical notation of sets. The Python syntax was inspired by the Haskell programming language.

S = {x² : x in {0 ... 16}}

This is a mathematical notation for creating a set of integer values.

L = [expression for variable in sequence [if condition]]

The above pseudo code shows the syntax of a list comprehension. It consists of three parts: a for loop, an optional condition, and an expression. A for loop goes through the sequence. For each loop an expression is evaluated if the condition is met. If the value is computed it is appended to the new list. There can be multiple for loops and if conditions.

## Transforming a list

The following example transforms a list into another list with the help of the list comprehension.

#!/usr/bin/python3 a = [1, 2, 3, 4, 5, 6] b = [e * 2 for e in a] print(b)

In the first example, we create a new list from an existing list by multiplying each element by 2.

b = [e * 2 for e in a]

Each of the elements of the `a`

list is multiplied by 2 and
the result is added to the new `b`

list.

$ ./multiply_elements.py [2, 4, 6, 8, 10, 12]

Each of the elements was multiplied by two.

## Calculating Fahrenheit temperatures from Celsius

We have a list of temperatures in Celsius. We want to create a new list of temperatures expressed in Fahrenheit temperature.

#!/usr/bin/python3 celsius = [22, 28, 33, 42, 52] fahr = [e * 9/5 + 32 for e in celsius] print(fahr)

The example creates a new list of Fahrenheit temperatures calculated from a list of Celsius temperatures.

fahr = [e * 9/5 + 32 for e in celsius]

The calculation is done in the third, expression part of the Python list comprehension.

$ ./fahrenheit_celsius.py [71.6, 82.4, 91.4, 107.6, 125.6]

This is the output of the example.

## Filtering a list

In the following example, we are going to filter a list with a list comprehension.

#!/usr/bin/python3 a = [-4, 2, 0, -1, 12, -3] b = [e for e in a if e > 0] print(b)

We have a list of integers. We create a new list where we only include positive integers.

b = [e for e in a if e > 0]

To include only positive numbers, we use an `if`

condition,
which is applied on each of the elements; the elements are included
into the new list only if they satisfy the condition.

$ ./filter_positive.py [2, 12]

This is the output of the example.

The next example filters elements by their type.

#!/usr/bin/python3 a = ['a', 2, 'c', 12, 3, 'd'] b = [e for e in a if type(e) == int] c = [e for e in a if type(e) == str] print(b) print(c)

We have a list of elements, which are integers and strings. We create two new lists; one having only integers and one only strings.

b = [e for e in a if type(e) == int]

Here we create a list `b`

, which will contain only integer
values. The `type()`

function is used to determine the type
of the element.

$ ./filter_by_type.py [2, 12, 3] ['a', 'c', 'd']

This is the output of the example.

## Multiple if conditions

It is possible to use multiple if conditions in the Python list comprehensions.

#!/usr/bin/python3 a = [9, 2, 18, 14, 22, 11, 7, 19, 23] b = [e for e in a if e > 10 if e < 20] print(b)

We create a new list of integers from list `a`

, which are
greater than 10 and lower than 20.

b = [e for e in a if e > 10 if e < 20]

In this list comprehension, we use two if conditions.

$ ./multiple_conditions.py [18, 14, 11, 19]

This is the output of the example.

## Multiple for loops

It is possible to have multiple for loops in a Python list comprehension.

#!/usr/bin/python3 a = [1, 2, 3] b = ['A', 'B', 'C'] c = [ str(i) + j for i in a for j in b] print(c)

The example creates a cartesian product of two lists.

c = [ str(i) + j for i in a for j in b]

Two for loops are used to create a cartesian product.

$ ./multiple_for_loops.py ['1A', '1B', '1C', '2A', '2B', '2C', '3A', '3B', '3C']

This is the output of the example.

The next example shows how to flatten a Python list.

#!/usr/bin/python3 nums = [[1, 2, 3], [3, 4, 5], [6, 7, 8]] c = [ e for num in nums for e in num] print(c)

The `nums`

list is a list of nested lists. We flatten
the list with a list comprehension.

c = [ e for num in nums for e in num]

The first loop goes through the outer list; the second for loop goes through the nested lists.

$ ./flatten_list.py [1, 2, 3, 3, 4, 5, 6, 7, 8]

This is the output of the example.

## Nested list comprehensions

The initial expression in a Python list comprehension can be another list comprehension.

#!/usr/bin/python3 M1 = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] M1_tr = [[row[i] for row in M1] for i in range(3)] print(M1_tr)

The example defines a matrix and a list comprehension creates a transposed matrix from the original matrix.

$ ./nested_list_comprehension.py [[1, 4, 7], [2, 5, 8], [3, 6, 9]]

This is the output of the example.

## Sieve of Eratosthenes

Sieve of Eratosthenes is an ancient algorithm to compute prime numbers. The algorithm iteratively marks as composite (i.e., not prime) the multiples of each prime, starting with the multiples of 2.

#!/usr/bin/python3 no_primes = [j for i in range(2, 8) for j in range(i*2, 100, i)] primes = [e for e in range(2, 100) if e not in no_primes] print (primes)

The example computes prime numbers up to 100.

no_primes = [j for i in range(2, 8) for j in range(i*2, 100, i)]

First, we create a list of numbers that are not primes.

primes = [e for e in range(2, 100) if e not in no_primes]

Prime numbers are simply these numbers that are not included
in the `no_primes`

list.

$ ./sieve_of_eratosthenes.py [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97]

This is the output.

In this tutorial, we have presented the Python list comprehensions.

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