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Sets in Python

 

Sets in Python

A set is an unordered collection of unique elements in Python. Unlike lists and tuples, sets do not allow duplicate values and do not maintain the order of their elements. Sets are mutable, meaning that you can add and remove elements after their creation. They are often used when you need to store distinct items, perform mathematical set operations, or check for membership efficiently.

1. Creating Sets

Sets can be created using curly braces {} or by using the set() constructor. When creating a set, any duplicate elements are automatically removed.

Example 1: Creating Sets

# Creating a set using curly braces
fruits = {"apple", "banana", "cherry"}

# Creating a set using the set() constructor
numbers = set([1, 2, 3, 4, 5])

# Creating a set with duplicate elements (duplicates will be removed)
fruits_with_duplicates = {"apple", "banana", "cherry", "apple"}
print(fruits_with_duplicates)  # Output: {'apple', 'banana', 'cherry'}

# Creating an empty set (note: you cannot use {} for an empty set, it creates an empty dictionary)
empty_set = set()

print(fruits)  # Output: {'banana', 'cherry', 'apple'}
print(numbers)  # Output: {1, 2, 3, 4, 5}

  • Set with Duplicate Elements: If you try to add duplicate elements to a set, they will automatically be removed. In the example above, "apple" appears twice but is stored only once.

  • Empty Set: You must use the set() constructor to create an empty set. Using {} will create an empty dictionary.

2. Accessing Set Elements

Sets do not support indexing or slicing because they are unordered collections. However, you can iterate over the elements of a set using a loop.

Example 2: Iterating Through a Set

fruits = {"apple", "banana", "cherry"}

# Looping through a set
for fruit in fruits:
    print(fruit)
  • Since sets are unordered, the order in which elements are displayed may vary each time you run the program.

3. Adding and Removing Elements

You can add elements to a set using the add() method and remove elements using the remove(), discard(), or pop() methods.

Example 3: Adding and Removing Elements

fruits = {"apple", "banana", "cherry"}

# Adding an element
fruits.add("orange")
print(fruits)  # Output: {'banana', 'cherry', 'apple', 'orange'}

# Removing an element (raises a KeyError if the element does not exist)
fruits.remove("banana")
print(fruits)  # Output: {'cherry', 'apple', 'orange'}

# Using discard() removes an element without raising a KeyError if it doesn't exist
fruits.discard("pear")  # No error even if 'pear' is not in the set
print(fruits)  # Output: {'cherry', 'apple', 'orange'}

# Popping an element (removes and returns an arbitrary element)
popped_element = fruits.pop()
print(popped_element)  # Output: an arbitrary element, e.g., 'apple'
print(fruits)  # Output: set with remaining elements
  • add(): Adds a single element to the set. If the element already exists, no change occurs.
  • remove(): Removes a specified element, but raises a KeyError if the element is not found.
  • discard(): Removes an element, but does not raise an error if the element is not found.
  • pop(): Removes and returns an arbitrary element from the set. Since sets are unordered, you cannot predict which element will be removed.

4. Set Operations

Sets support various mathematical operations, such as union, intersection, difference, and symmetric difference. These operations allow you to perform common set operations that are useful for tasks like comparing collections or finding common elements.

Example 4: Set Operations

set1 = {1, 2, 3, 4}
set2 = {3, 4, 5, 6}

# Union: Combine all elements from both sets (duplicates are removed)
union_set = set1 | set2  # or set1.union(set2)
print(union_set)  # Output: {1, 2, 3, 4, 5, 6}

# Intersection: Get common elements between sets
intersection_set = set1 & set2  # or set1.intersection(set2)
print(intersection_set)  # Output: {3, 4}

# Difference: Elements in set1 but not in set2
difference_set = set1 - set2  # or set1.difference(set2)
print(difference_set)  # Output: {1, 2}

# Symmetric Difference: Elements that are in either set, but not in both
symmetric_difference_set = set1 ^ set2  # or set1.symmetric_difference(set2)
print(symmetric_difference_set)  # Output: {1, 2, 5, 6}
  • Union (|): Returns all elements from both sets, removing duplicates.
  • Intersection (&): Returns the common elements between sets.
  • Difference (-): Returns the elements that are only in the first set and not in the second.
  • Symmetric Difference (^): Returns the elements that are in either of the sets but not both.

5. Set Membership

You can test if an element is present in a set using the in keyword. The operation is highly efficient and fast because sets are implemented using hash tables.

Example 5: Membership Testing

fruits = {"apple", "banana", "cherry"}

# Testing if an element is in the set
print("apple" in fruits)  # Output: True
print("orange" in fruits)  # Output: False

6. Set Comprehension

Similar to list and dictionary comprehensions, you can create sets using set comprehension. This is a concise way to generate sets.

Example 6: Set Comprehension

# Creating a set of squares of numbers from 1 to 5
squares = {x ** 2 for x in range(1, 6)}
print(squares)  # Output: {1, 4, 9, 16, 25}

# Creating a set of even numbers from 1 to 10
evens = {x for x in range(1, 11) if x % 2 == 0}
print(evens)  # Output: {2, 4, 6, 8, 10}
  • Set comprehension allows you to build sets in a concise and readable way, optionally filtering elements with conditions.

7. Frozen Sets

A frozen set is an immutable version of a set. Once created, the elements of a frozen set cannot be modified, making it hashable and suitable for use as keys in dictionaries or elements in other sets.

Example 7: Frozen Sets

# Creating a frozen set
frozen_fruits = frozenset(["apple", "banana", "cherry"])

print(frozen_fruits)  # Output: frozenset({'banana', 'cherry', 'apple'})

# Attempting to add or remove elements (will raise an error)
# frozen_fruits.add("orange")  # Uncommenting this will raise an AttributeError
# frozen_fruits.remove("banana")  # Uncommenting this will raise an AttributeError
  • frozenset(): Creates an immutable set. Operations that modify sets, such as add() or remove(), are not available for frozen sets.

8. Summary of Sets

  • Unordered: Sets do not guarantee the order of elements.
  • Unique: Sets automatically remove duplicate values.
  • Mutable: You can add and remove elements.
  • Efficient Membership Testing: The in keyword is very fast for checking membership.
  • Set Operations: Supports mathematical set operations such as union, intersection, difference, and symmetric difference.
  • Set Comprehension: A concise way to create sets.
  • Frozen Sets: Immutable sets that can be used as dictionary keys or elements in other sets.

Sets are very useful when you need to eliminate duplicates, perform set-based mathematical operations, or simply need an efficient way to check for membership without worrying about the order of elements.

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