Sets in Python are an incredibly useful data type for handling collections of unique items. Whether you're checking for membership, removing duplicates, or performing mathematical set operations like union or intersection, Python sets are designed to be efficient and easy to use.

In this detailed guide, you’ll learn what sets are, how to create and modify them, and how to apply common set operations with practical examples.

1. What is a Set?

A set is an unordered, mutable collection of unique elements. It is defined using curly braces {} or the set() constructor.

# Example 1: Creating a set
fruits = {"apple", "banana", "cherry"}
print(fruits)  # Output may vary due to unordered nature

# Example 2: Creating a set with duplicates
numbers = {1, 2, 2, 3, 4}
print(numbers)  # Output: {1, 2, 3, 4}

# Example 3: Using set() to convert from list
colors = set(["red", "green", "blue", "green"])
print(colors)

2. Accessing Elements

Sets do not support indexing or slicing since they are unordered. You can loop through a set using a for loop.

# Example 4: Looping through a set
for fruit in fruits:
    print(fruit)

3. Adding Elements

Use add() to add a single element and update() to add multiple items.

# Example 5: Adding elements
fruits.add("orange")
print(fruits)

# Example 6: Adding multiple elements
fruits.update(["kiwi", "grape"])
print(fruits)

4. Removing Elements

Python provides several methods to remove elements:

• remove() – raises an error if the element is not found
• discard() – does not raise an error if the element is not found
• pop() – removes and returns an arbitrary element
• clear() – removes all elements from the set

# Example 7: remove vs discard
fruits.remove("apple")
fruits.discard("banana")
# fruits.remove("mango")  # This would raise a KeyError
fruits.discard("mango")  # No error

# Example 8: pop and clear
value = fruits.pop()
print(value)       # Random item
fruits.clear()
print(fruits)      # Output: set()

5. Set Operations

Sets support mathematical operations like union, intersection, difference, and symmetric difference.

# Example 9: Set operations
A = {1, 2, 3, 4}
B = {3, 4, 5, 6}

print(A | B)   # Union: {1, 2, 3, 4, 5, 6}
print(A & B)   # Intersection: {3, 4}
print(A - B)   # Difference: {1, 2}
print(A ^ B)   # Symmetric Difference: {1, 2, 5, 6}

6. Membership Testing

Sets are very efficient for checking if an element exists.

# Example 10: Checking membership
if "apple" in fruits:
    print("Apple is in the set")
else:
    print("Apple is not in the set")

7. Immutable Sets (frozenset)

If you need a set that cannot be modified, use frozenset.

# Example 11: Creating a frozenset
fs = frozenset([1, 2, 3])
# fs.add(4)  # ❌ Raises AttributeError because frozenset is immutable

8. Set Methods Overview

• add() – Add a single element
• update() – Add multiple elements
• remove() – Remove specified element (raises error if not found)
• discard() – Remove specified element (no error if not found)
• pop() – Remove and return arbitrary element
• clear() – Remove all elements
• union(), intersection(), difference(), symmetric_difference() – Set operations

When to Use Sets

• To remove duplicates from a list or other iterable
• When you need fast membership testing (e.g., checking if a value exists)
• To perform mathematical set operations

Summary

• Sets are unordered collections of unique, mutable elements
• They are ideal for membership testing and removing duplicates
• They support a wide range of built-in operations and methods

Final Thoughts

Python sets are a versatile and efficient data structure that every Python programmer should be familiar with. Whether you're working with clean data, eliminating duplicates, or comparing datasets, sets offer a clean and performant solution.