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An Introduction to Python Sets


One of the most unique built-in methods to store collections in Python are sets. Other kinds of collections in Python include the well known lists as well as dictionaries and tuples. In this article, we will be focusing on sets, their properties, and how to use them in your programs.


What are sets?

In mathematics, a set is simply a collection of elements. The elements could be any number or object. In programming languages, more specifically in Python, sets are most commonly used to store elements while ensuring that no element gets repeated more than once. This means that a set is a list where we are sure that every single element is unique.


Why use sets?

Sets provide us with two main advantages: there are no duplicate items in sets; and accessing elements in them is fast. This is due to the fact that sets utilize a technique called Hashing which allows us to insert, delete, and traverse a collection or an iterable in O(1) on average.


Sets properties

  • No duplicates

  • Unordered

  • Immutable

  • Different data types

No Duplicates

This is one of the key differences between sets and other collections. For example, in the following set, "apples" has been input twice. However, it shows up only once in the set when you try to print the set. More on how to create sets later.

fruit_basket = {'apples', 'bananas', 'apples','oranges'}

Unordered

This means that elements do not have an index that can be used to refer to them, and thus they have no hierarchy: no element comes before the other. So how can we access items in a set? Using a loop:

for fruit in fruit_basket:
    print(fruit)

Immutable

You cannot change an element that has been added to a set, you can only add to the set or delete from it. In fact, there is no way to change the element: it is not indexed so you cannot access it individually unless by value.


Different Data Types

A set can contain elements having different data types. For example:

new_set = {1, 'two', 3.0, True}


Creating a Set

To create a new set, you can use curly braces as in the previous examples (not to be confused with dictionaries' curly braces). You can also use the set() constructor.

another_set = set(('Hello', 'this', 'is', 'a', 'set'))

Note the double brackets in the previous example.


However, to create an empty set, you cannot use empty curly braces {}, as this will denote an empty dictionary. Instead, use the set constructor.

empty_set = set()


Adding Items to Sets

To add new items to a preexisting set, use add() method.

fruit_basket.add('mangoes')

To add an entire set to a new set, use update() method.

new_fruits = {'strawberries', 'passion fruit'}
fruit_basket.update(new_fruits)

Note: the update method can be used to add any sort of collections to a set, not just other sets.

fruit_list = ['kiwis', 'cherries']
fruit_basket.update(fruit_list)


Remove Items from Sets

To remove an item from a set, you have to refer to it by value and use either the method remove() or discard(). The difference between them is that remove() will raise an error if you attempt to remove an item that does not exist in the set, whereas discard() will not raise an error.

if ('bananas' in fruit_basket):
    fruit_basket.remove('bananas')

Note the use of in keyword to check if an item exists in a set or not.


You can also use pop() method, which would typically remove the last item in a list and return it. However, since sets are unordered, you would not know what that last item is.

random_fruit = fruit_basket.pop()

Two additional methods are clear() which would empty the set, and del() which would delete the set from the memory completely so you cannot use its reference name again unless it is reinitialized.


Other Interesting Methods

Python offers more set methods that relate more directly to its mathematical definition such as union() and intersection().


This has been a brief overview to help you start using sets in Python. For a full list of methods check out this resource.


To view this article as a Jupyter Notebook, click here.

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