Sets and Set Operations in Python

In Python, a set is a built-in data structure that stores unordered, unique elements. Sets are incredibly useful when you need to eliminate duplicates, perform mathematical set operations, or check for membership efficiently.

Let’s explore how sets work and how you can use them in your Python programs.

What is a Set?

A set is defined using curly braces {} or the set() constructor.

# Using curly braces

fruits = {"apple", "banana", "cherry"}

# Using set() constructor

numbers = set([1, 2, 3, 4])

⚠️ Note: You cannot create an empty set using {} — that creates an empty dictionary. Use set() instead.

Key Properties of Sets

• Unordered: The elements have no fixed position.

• Unique: Duplicate elements are automatically removed.

• Mutable: You can add or remove elements.

• Iterable: You can loop through a set.

data = {1, 2, 2, 3, 4}

print(data)  # Output: {1, 2, 3, 4}

Common Set Methods

Here are some useful methods to manipulate sets:

• add(elem) - Adds an element

• remove(elem) - Removes an element (raises error if not found)

• discard(elem) - Removes an element (no error if not found)

• pop() - Removes and returns a random element

• clear() - Removes all elements

• len(set) - Returns the number of elements

colors = {"red", "green"}

colors.add("blue")

colors.discard("green")

print(colors)  # Output: {'red', 'blue'}

Set Operations

Python supports standard set theory operations:

1. Union (| or .union())

Combines elements from both sets.

a = {1, 2, 3}

b = {3, 4, 5}

print(a | b)           # {1, 2, 3, 4, 5}

print(a.union(b))      # {1, 2, 3, 4, 5}

2. Intersection (& or .intersection())

Returns common elements.

print(a & b)           # {3}

print(a.intersection(b))  # {3}

3. Difference (- or .difference())

Returns elements in a but not in b.

print(a - b)           # {1, 2}

print(a.difference(b)) # {1, 2}

4. Symmetric Difference (^ or .symmetric_difference())

Returns elements in either set, but not both.

print(a ^ b)           # {1, 2, 4, 5}

Membership Testing

Sets are optimized for fast membership checks.

print(2 in a)   # True

print(5 not in a)  # True

When to Use Sets?

• Removing duplicates from a list

• Fast membership testing

• Performing mathematical set operations

• Representing unique items (e.g., tags, categories)

Practice Challenge

Try this:

# Remove duplicates from a list

names = ["Ali", "Sara", "Ali", "Zara", "Sara"]

unique_names = set(names)

print(unique_names)

Summary

Sets are a powerful and efficient way to handle collections of unique items in Python. Whether you're cleaning data or performing mathematical operations, sets make your code cleaner and faster.

Next Up: Dictionaries and key-value access