Data Structures16 min read

Set Basics

Learn sets from scratch: uniqueness, fast membership checks, and practical use cases like removing duplicates and comparing groups of data.

David Miller
November 21, 2025
2.9k139

A set stores unique items and is usually unordered.

Why sets matter

Sets are extremely useful when you want:

  • remove duplicates
  • check membership fast
  • compare groups (common vs missing)

Create a set

nums = {1, 2, 3, 3, 3}
print(nums)  # {1,2,3} duplicates removed

Add and remove

s = {"a", "b"}
s.add("c")
s.remove("b")  # error if missing
s.discard("x") # safe if missing

Fast membership

users = {"Tom", "Sarah", "Mike"}
print("Sarah" in users)  # fast

Common set operations (very useful)

a = {"Tom", "Sarah", "Mike"}
b = {"Sarah", "Ahsan"}

print(a & b)  # intersection -> common
print(a | b)  # union -> all
print(a - b)  # difference -> in a not in b

Real example: find new applicants

applied = {"Tom", "Sarah"}
all_users = {"Tom", "Sarah", "Mike", "Ahsan"}
not_applied = all_users - applied
print(not_applied)

Graph: set uniqueness

flowchart LR
  A[Input: a,a,b,c] --> B[Set]
  B --> C[Output: a,b,c]

Remember

  • Sets remove duplicates automatically
  • Use sets for fast membership
  • Set operations solve many real problems
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