Understanding List, Set, and Dictionary Comprehension in Python

List comprehensions in python is a powerful tool that allows you to create lists, sets, and dictionaries with a single line of code. When using list comprehensions to create your lists, you can utilize conditional logic, expressions, and callbacks functions to control the output of the elements pushed into the new list.

There are many ways of creating lists in python. We will specifically discuss for loops, list comprehensions and how the two are similar.

To create a list using a for loop, you must

• Instantiate an empty list
• Loop over an iterable (such as a list, tuple, range, or dictionary object)
• Append each element to the end of the list

Using a for loop, let's create a list that contains the double of values 0 - 10:

double = []
for i in range(11):  
    result = i * 2
    double.append(result)
double
# >>> [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20]

Using list comprehension, we can simplify this into one line of code

double = [ i * 2 for i in range(11) ]
double
# >>> [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20]

To filter which value gets doubled, we can add a conditional if statement. We only want even numbers to be doubled and stored in the list.

double = []
for i in range(11):
    if i % 2 == 0:
        result = i * 2
        double.append(result)
double
# >>> [0, 4, 8, 12, 16, 20]

With list comprehension:

double = [ i * 2 for i in range(11) if i % 2 == 0]
double
# >>> [0, 4, 8, 12, 16, 20]

We can also add an else clause and make it an if expression; if the value is even, double it, else return another thing (let’s use the word "hi" ). Note, the structure of the list comprehension will be different:

double = [ i * 2 if i % 2 == 0 else "hi" for i in range (11)]
# >>> [0, 'hi', 4, 'hi', 8, 'hi', 12, 'hi', 16, 'hi', 20]

The reason for this is due to the syntax of a list comprehension:

new_list = [ expression for item in iterable optional_if_condition ]

List comprehension are structured using three important components as well as an optional fourth:

• an expression
• the item
• the iterable
• optional if statement

The expression can be the item itself, a call to a function, or any expression that returns a value. For instance, you can have a list with 10 "hi": greetings = ["hi" for i in range(11)]

The item is the element in the iterable.

The iterable can be a list, set, dictionary, range, or any object that can return its elements one at a time.

The optional if statement acts as a filter. If the conditional evaluates to True, the expression component evaluates and the return value gets pushed into the list, otherwise the expression does not run for that round of the iteration. Using the above example, you can have a list with 10 "hi" if your conditional is "if True" or a blank list if your conditional is "if False". For complex filters, a function can be used to do your analysis.

The benefits of using list comprehension are that you can use a single tool in many situations to create lists. In JavaScript, you can create new lists utilizing the .map() and .filter() methods. However, there isn't a method that combines the two. Python also has .map() and .filter() methods as well. But fortunately in python, with list comprehension, you have 1 tool that can utilize both methods at your disposal.

Python contains other list data structures and you can apply comprehension to them as well. I will specifically cover set and dictionary comprehension.

Set and dictionary comprehension are similar to each other. Both set and dictionary use curly brackets and outputs unique elements into an unordered list but with dictionaries, you must also include values that corresponds to the key.

The syntax:

new_set = { expression for item in iterable optional_if_condition }
new_dict = { key_expression : value_expression for item in iterable optional_if_condition }

Let's create a set list where it contains the letters of a sentence

sentence = "Today, we are learning list, set, and dictionary comprehension"
set_sentence = { item for item in sentence}
set_sentence
# >>> {',', 'l', 'm', 'T', 'r', 'a', 'e', 'n', 'i', 't', 'c', ' ', 's', 'p', 'd', 'o', 'y', 'w', 'h', 'g'}

Now let's create a dictionary where the key is the letter and the value is the count of each character in the sentence.

set_sentence = { item : sentence.count(item) for item in sentence}
set_sentence
# >>> {'T': 1, 'o': 4, 'd': 3, 'a': 5, 'y': 2, ',': 3, ' ': 8, 'w': 1, 'e': 6, 'r': 4, 'l': 2, 'n': 6, 'i': 5, 'g': 1, 's': 3, 't': 3, 'c': 2, 'm': 1, 'p': 1, 'h': 1}

Additionally for dictionary comprehension, you can use 2 items if the iterable returns two values. For instance, we can create a dictionary enumerating a list or using .items() method on an existing dictionary.

fruits = ["apples", "bananas", "grapes", "oranges", "pineapples"]
fruit_dict = { key : value for key, value in enumerate(fruits)}
fruit_dict
# >>> {0: 'apples', 1: 'bananas', 2: 'grapes', 3: 'oranges', 4: 'pineapples'}

phone_book = {"John" : 3334445555, "Rose" : 5555555555, "Alan" : 1234567890}
phone_book_edit = { key.upper() : value for key, value in phone_book.items()}
# >>> {'JOHN': 3334445555, 'ROSE': 5555555555, 'ALAN': 1234567890}

I hope my guide helped you on your programming journey. Please feel free to comment, ask questions, or provide feedback.

Lastly, happy coding!