Sets in Python

Creating a Set

A set is written using curly braces {} with comma-separated values.

colors = {"red", "green", "blue"}
print(colors)
print(type(colors))   # <class 'set'>

Unordered and Unique

A set does not keep track of insertion order or position, so items cannot be accessed by index. More importantly, a set automatically removes duplicates. Adding a value that already exists in the set has no effect at all.

numbers = {1, 2, 3, 2, 1}
print(numbers)    # {1, 2, 3} - duplicates were dropped automatically

colors = {"red", "green", "blue"}
colors.add("red")     # "red" is already in the set
print(colors)     # still {'red', 'green', 'blue'} - no effect, no error
print(len(colors))  # 3

Common Set Methods

Sets provide methods for adding, removing, and combining values.

Method	Description
.add(value)	Adds a single item to the set.
.remove(value)	Removes an item; raises KeyError if it is not present.
.discard(value)	Removes an item if present; does nothing if it is not present (no error).
.union(other)	Returns a new set with all items from both sets.
.intersection(other)	Returns a new set with only the items common to both sets.
.difference(other)	Returns a new set with items in the first set that are not in the second.

a = {1, 2, 3}
b = {3, 4, 5}

a.add(10)
print(a)                    # {1, 2, 3, 10}

a.discard(10)
print(a)                    # {1, 2, 3}

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

Set Operators

The same union, intersection, and difference operations can also be written with operators, which many developers find more readable.

Operator	Meaning
|	Union - items in either set
&	Intersection - items in both sets
-	Difference - items in the first set but not the second

a = {1, 2, 3}
b = {3, 4, 5}

print(a | b)   # {1, 2, 3, 4, 5}  same as a.union(b)
print(a & b)   # {3}              same as a.intersection(b)
print(a - b)   # {1, 2}           same as a.difference(b)

Why Sets Are Useful

Two practical, everyday uses for sets:

• Fast membership testing: checking value in my_set is much faster than checking value in my_list for large collections.
• Removing duplicates from a list: converting a list to a set and back is a common one-line trick to deduplicate values.

names = ["Amit", "Neha", "Amit", "Ravi", "Neha"]

unique_names = list(set(names))
print(unique_names)   # order not guaranteed, e.g. ['Amit', 'Neha', 'Ravi']

# fast membership test
allowed_users = {"admin", "editor", "viewer"}
if "editor" in allowed_users:
    print("Access granted")

The Empty Set Gotcha

Writing {} does not create an empty set — it creates an empty dictionary. To create an empty set, you must use the set() constructor instead.

not_a_set = {}
print(type(not_a_set))   # <class 'dict'>

empty_set = set()
print(type(empty_set))   # <class 'set'>