set

The built-in set data type represents an unordered collection of unique elements. Sets allow for efficient membership testing and set operations like union, intersection, and difference:

Python 
>>> fruits = {"apple", "banana", "cherry"}
>>> "banana" in fruits
True

set Constructor

Python Syntax 
set(iterable)

Arguments

Argument Description
iterable An iterable with elements to be included in the set

Return Value

  • Returns a Python set object

set Examples

Creating an empty instance of a set:

Python 
>>> empty_set = set()
>>> empty_set
set()

Creating instances using a literal:

Python 
>>> colors = {"red", "green", "blue"}
>>> colors
{'red', 'blue', 'green'}

Creating an instance using the class constructor with a list as an argument:

Python 
>>> numbers = set([1, 2, 3, 4, 5])
>>> numbers
{1, 2, 3, 4, 5}

Checking whether a value is in a set:

Python 
>>> "red" in colors
True

Adding or removing elements from a set:

Python 
>>> colors.add("yellow")
>>> colors
{'red', 'green', 'blue', 'yellow'}

>>> colors.remove("green")
>>> colors
{'red', 'blue', 'yellow'}

set Methods

Method Description
.add(elem) Adds an element to the set.
.remove(elem) Removes an element from the set; raises KeyError if not found.
.discard(elem) Removes an element from the set if present.
.pop() Removes and returns an arbitrary element; raises KeyError if empty.
.clear() Removes all elements from the set.
.update(iterable) Updates the set with elements from the iterable.
.intersection_update(iterable) Updates the set with the intersection of itself and another.
.difference_update(iterable) Removes all elements of another set from this set.
.symmetric_difference_update(iterable) Updates the set with the symmetric difference.
.union(*others) Returns a new set with elements from the set and all others.
.intersection(*others) Returns a new set with elements common to the set and all others.
.difference(*others) Returns a new set with elements in the set that are not in the others.
.symmetric_difference(other) Returns a new set with elements in either the set or other but not both.
.issubset(other) Returns True if the set is a subset of other.
.issuperset(other) Returns True if the set is a superset of other.
.isdisjoint(other) Returns True if the set has no elements in common with other.

set Common Use Cases

The most common use cases for the set include:

  • Removing duplicates from a sequence
  • Efficient membership testing
  • Performing mathematical set operations, such as union, intersection, and difference
  • Storing unique items without any particular order

set Real-World Example

Consider an example of using a set to find unique visitors to a website:

Python 
>>> visitors = ["Alice", "Bob", "Alice", "Charlie", "Bob", "David"]
>>> unique_visitors = set(visitors)
>>> unique_visitors
{'Charlie', 'Bob', 'Alice', 'David'}

This example demonstrates how you can use a set to eliminate duplicate entries, efficiently identifying unique elements.

Sets in Python

Tutorial

Sets in Python

In this tutorial you'll learn how to work effectively with Python's set data type. You'll see how to define set objects in Python and discover the operations that they support and by the end of the tutorial you'll have a good feel for when a set is an appropriate choice in your own programs.

basics python

For additional information on related topics, take a look at the following resources:

By Leodanis Pozo Ramos • Updated Dec. 6, 2024 • Reviewed by Dan Bader
Python’s Built-in Data Types Share Feedback