Introduction to Sets in Python
A set in Python is an unordered collection of unique elements. Unlike lists and tuples, sets do not allow duplicate values, making them useful for tasks like removing duplicates, membership testing, and mathematical set operations.
Python sets are highly optimized for performance, allowing fast membership checks and set operations.
Creating Sets in Python
1. Using Curly Braces {}
my_set = {1, 2, 3, 4, 5}
print(my_set) # Output: {1, 2, 3, 4, 5}2. Using set() Constructor
my_set = set([1, 2, 3, 4, 5])
print(my_set) # Output: {1, 2, 3, 4, 5}3. Creating an Empty Set
empty_set = set() # This is correctUsing {} will create an empty dictionary, not a set.
Basic Set Operations
1. Adding Elements
my_set = {1, 2, 3}
my_set.add(4)
print(my_set) # Output: {1, 2, 3, 4}2. Removing Elements
Using discard() (No error if the element is absent)
my_set.discard(2)
print(my_set) # Output: {1, 3, 4}Using remove() (Raises an error if the element is absent)
my_set.remove(3)
print(my_set) # Output: {1, 4}Using pop() (Removes a random element)
removed_element = my_set.pop()
print(removed_element) # Output: Random element from the set
print(my_set) # Output: Remaining elementsUsing clear() (Removes all elements)
my_set.clear()
print(my_set) # Output: set()Set Membership Testing
my_set = {1, 2, 3, 4, 5}
print(3 in my_set) # Output: True
print(6 not in my_set) # Output: TrueSet Operations
1. Union (|)
Combines two sets into one, removing duplicates.
set_a = {1, 2, 3}
set_b = {3, 4, 5}
print(set_a | set_b) # Output: {1, 2, 3, 4, 5}2. Intersection (&)
Finds common elements between two sets.
print(set_a & set_b) # Output: {3}3. Difference (-)
Finds elements that are in the first set but not in the second.
print(set_a - set_b) # Output: {1, 2}4. Symmetric Difference (^)
Finds elements that are unique to each set.
print(set_a ^ set_b) # Output: {1, 2, 4, 5}Subset, Superset, and Disjoint Sets
1. Checking Subset (issubset())
set_x = {1, 2}
set_y = {1, 2, 3, 4}
print(set_x.issubset(set_y)) # Output: True2. Checking Superset (issuperset())
print(set_y.issuperset(set_x)) # Output: True3. Checking Disjoint Sets (isdisjoint())
set_a = {1, 2, 3}
set_b = {4, 5, 6}
print(set_a.isdisjoint(set_b)) # Output: TrueAdvanced Set Concepts
1. Set Comprehensions
even_squares = {x**2 for x in range(1, 11) if x % 2 == 0}
print(even_squares) # Output: {4, 16, 36, 64, 100}2. Frozen Sets (Immutable Sets)
Frozen sets cannot be modified after creation.
frozen = frozenset([1, 2, 3])
print(frozen) # Output: frozenset({1, 2, 3})Do’s and Don’ts of Sets
✅ Do’s
- Use sets when you need unique elements.
- Use set operations for quick comparisons.
- Use
discard()instead ofremove()if you’re unsure whether an element exists. - Use
frozensetwhen an immutable set is required.
❌ Don’ts
- Don’t use sets when order matters (use lists instead).
- Don’t try to access elements using indexing (e.g.,
my_set[0]will cause an error). - Don’t put mutable objects (like lists or dictionaries) inside a set.
Common Exceptions and Errors in Sets
1. Trying to Access Elements by Index
my_set = {1, 2, 3}
print(my_set[0]) # TypeError: 'set' object is not subscriptable2. Adding a Mutable Object (Like a List) to a Set
my_set = {1, 2, [3, 4]} # TypeError: unhashable type: 'list'3. Using remove() on a Non-Existent Element
my_set = {1, 2, 3}
my_set.remove(4) # KeyError: 4Conclusion
Sets in Python provide a powerful and efficient way to handle collections of unique elements. With built-in support for mathematical operations, they are an excellent tool for filtering data, membership testing, and eliminating duplicates. By following best practices and avoiding common mistakes, you can leverage the full potential of sets in your Python programs.
Now that you’ve mastered sets, try implementing them in real-world projects to get hands-on experience!