Python - Sets

Sets in Python: Unleashing Uniqueness and Set Operations

Sets in Python are unordered collections of unique elements. They offer a versatile way to perform mathematical set operations, such as union, intersection, and difference. Let's explore the characteristics and capabilities of sets:

1. Set Declaration :

   - Sets are declared using curly braces {} or the set() constructor.

  
# Set Declaration Example

my_set = {1, 3, 5}  # Creating a set with elements 1, 3, and 5
      

    

2. Uniqueness :

   - Sets enforce uniqueness, meaning they cannot contain duplicate elements.

  
# Set Uniqueness Example

my_set = {1, 2, 3, 2, 4, 5}  # Creating a set with duplicate elements

unique_set = set(my_set)  # Creating a new set with unique elements

print(unique_set)      # result is {1, 2, 3, 4, 5}

    

3. Set Operations :

   - Sets support various operations such as union (|), intersection (&), difference (-), and symmetric difference (^).

  
# Set Operations Example

set_a = {1, 2, 3, 6}  # Creating set A
set_b = {3, 4, 5, 6}  # Creating set B

# Union - Elements present in either set A or set B or both
union_result = set_a | set_b  # {1, 2, 3, 4, 5 ,6}

# Intersection - Elements present in both set A and set B
intersection_result = set_a & set_b  # {3 , 6}

# Difference - Elements present in set A but not in set B
difference_result = set_a - set_b  # {1, 2}

# Symmetric Difference - Elements present in either set A or set B, but not both
symmetric_difference_result = set_a ^ set_b  # {1, 2, 4, 5}
      

    

4. Adding and Removing Elements :

   - Elements can be added to a set using the add() method and removed using remove() or discard().

# Adding and Removing Elements from a Set Example

my_set = {2, 3, 5}  # Creating a set

my_set.add(4)  # Adding an element to the set
#Output 
print(my_set)     # {2, 3, 4, 5}

my_set.remove(2)       # Removing an element from the set
# Output
print(my_set)  # {3, 4, 5}

my_set.discard(5)      # Discarding an element from the set
# Output:
print(my_set)  # {3, 4}

    

5. Set Comprehensions :

   - Set comprehensions provide a concise way to create sets based on existing sequences or ranges.

  
# Set Comprehension Example

numbers = {1, 2, 3, 4, 5, 6}  # Original set

squared_numbers = {x**2 for x in numbers}  # Set comprehension

# Output:
print(squared_numbers)  # {1, 4, 9, 16, 25, 36}
      

    

6. Frozen Sets :

   - Python offers an immutable version of sets called frozen sets, created using the frozenset() constructor.

 
# Frozen Set Example

numbers = {1, 2, 3, 4, 5}  # Original set

frozen_numbers = frozenset(numbers)  # Creating a frozen set

# Output:

print(frozen_numbers)  # frozenset({1, 2, 3, 4, 5})

# Attempting to modify a frozen set will result in an error

frozen_numbers.add(6)  # This will raise an AttributeError
      

     
Understanding sets equips you with a powerful tool for handling collections of unique elements and performing set operations efficiently. Whether it's filtering out duplicates or determining the common elements between two sets, sets provide a concise and effective solution.