Sets in Python

Overview

A Set is an unordered collection of unique elements enclosed in curly braces {}. Sets automatically eliminate duplicates and offer lightning-fast $O(1)$ lookup speeds.

Learning Objectives

• Create sets and add/remove elements.
• Use sets to remove duplicate items from lists.
• Perform set operations: Union (|), Intersection (&), Difference (-), and Symmetric Difference (^).

Concept Explanation

In simple words:

• Unordered: Items have no fixed position or index (you cannot access s[0]).
• Unique: Duplicate elements are automatically ignored.
• Fast Lookups: Checking if an item exists (item in my_set) runs in constant time $O(1)$.

Code Examples

Example 1 — Creating Sets & Removing Duplicates

# Creating a set with duplicate entries
raw_user_ids = [101, 102, 101, 103, 102]

# Deduplicate by converting to a set
unique_ids = set(raw_user_ids)
print("Unique IDs:", unique_ids) # {101, 102, 103}

# Adding and removing elements
unique_ids.add(104)
unique_ids.remove(101)
print("Updated Set:", unique_ids)

Example 2 — Set Mathematics

set_a = {"python", "sql", "spark"}
set_b = {"python", "java", "scala"}

# Union (all items from both)
print("Union:", set_a | set_b)

# Intersection (common items)
print("Intersection:", set_a & set_b) # {'python'}

# Difference (in A but not B)
print("Difference:", set_a - set_b) # {'sql', 'spark'}

Common Mistakes

• Creating empty sets with {}: {} creates an empty dictionary, not a set. Use set() for empty sets.
• Trying to store mutable objects in sets: Sets can only store immutable (hashable) items like numbers, strings, or tuples. Storing a list in a set raises a TypeError.

Best Practices

• Use sets whenever you need to filter duplicates or test membership across large datasets.