set()

set([iterable])

The set() function creates a new set object from an iterable. A set is an unordered collection of unique elements — duplicates are automatically removed. If no argument is provided, set() returns an empty set.

Syntax

set()
set(iterable)

Parameters

Parameter	Type	Default	Description
iterable	iterable	—	Optional. An iterable (list, tuple, string, dict, etc.) to convert to a set. If omitted, returns an empty set.

Examples

Creating an empty set

# This is NOT an empty dictionary — it's an empty set
empty = set()
print(empty)
# set()

# Common mistake: don't use {} for empty sets
# {} creates an empty dict, not a set
empty_dict = {}
print(type(empty_dict))
# <class 'dict'>

Removing duplicates from a list

numbers = [1, 2, 2, 3, 3, 3, 4, 4, 5]
unique = set(numbers)
print(unique)
# {1, 2, 3, 4, 5}

# If you need a list back
unique_list = list(set(numbers))
print(unique_list)
# [1, 2, 3, 4, 5]

Converting from a string

# Characters are unique — duplicates removed, order not preserved
text = "hello world"
chars = set(text)
print(chars)
# {'h', ' ', 'l', 'o', 'w', 'r', 'd', 'e'}

# For alphabetical characters only
alpha = set("hello hello hello")
print(sorted(alpha))
# ['e', 'h', 'l', 'o']

Converting from a dictionary

# Only keys become set elements
data = {"a": 1, "b": 2, "c": 3}
keys = set(data)
print(keys)
# {'a', 'b', 'c'}

Common Patterns

Finding unique words in text

text = "the quick brown fox jumps over the lazy dog the fox"
words = set(text.lower().split())
print(words)
# {'the', 'quick', 'brown', 'fox', 'jumps', 'over', 'lazy', 'dog'}

print(f"Unique words: {len(words)}")
# Unique words: 8

Set operations with lists

list1 = [1, 2, 3, 4, 5]
list2 = [4, 5, 6, 7, 8]

# Intersection (common elements)
common = set(list1) & set(list2)
print(common)
# {4, 5}

# Union (all unique elements)
all_elements = set(list1) | set(list2)
print(all_elements)
# {1, 2, 3, 4, 5, 6, 7, 8}

# Difference (in list1 but not in list2)
diff = set(list1) - set(list2)
print(diff)
# {1, 2, 3}

Membership testing performance

# Sets have O(1) average lookup vs O(n) for lists
large_list = list(range(10000))
large_set = set(large_list)

# Both check membership the same way
print(5000 in large_list)  # True
print(5000 in large_set)   # True

# But set is much faster for large collections
import time

start = time.perf_counter()
_ = 9999 in large_list
list_time = time.perf_counter() - start

start = time.perf_counter()
_ = 9999 in large_set
set_time = time.perf_counter() - start

print(f"List: {list_time:.6f}s, Set: {set_time:.6f}s")
# List: ~0.0001s, Set: ~0.000001s

When to Use Sets

Use set() when you need:

• Unique elements (removing duplicates)
• Fast membership testing
• Mathematical set operations (intersection, union, difference)

Use a list instead when:

• Order matters
• You need indexed access
• You might have duplicate values intentionally

See Also

• built-in::frozenset — immutable set variant

• list::list — convert back to a list