Four data structures in Python

• List:

  • Mutable: You can change, add, or remove items after the list creation.
  • Ordered: The order of items is maintained, and items can be accessed by their index.
  • Syntax: Created using square brackets [] or the list() function.
  • Duplicates: Allows duplicate elements.
    • Example: [1, 2, 3, 'apple', 'banana']

• Tuple:

  • Immutable: Once created, you cannot change, add, or remove items.
  • Ordered: Like lists, the order is maintained, and index access is possible.
  • Syntax: Created using parentheses () or the tuple() function.
  • Duplicates: Allows duplicate elements.
    • Example: (1, 2, 3, 'apple', 'banana')

• Set:

  • Mutable: You can add or remove items, but you cannot change individual items.
  • Unordered: No index access because sets do not record element position.
  • Syntax: Created using curly braces {} or the set() function.
  • Duplicates: Does not allow duplicate elements; only unique items.
    • Example: {1, 2, 3, 'apple', 'banana'}

• Dictionary:

  • Mutable: You can change, add, or remove items, which are key-value pairs.
  • Ordered: As of Python 3.7, dictionaries maintain insertion order.
  • Syntax: Created using curly braces {} with key-value pairs or the dict() function.
  • Duplicates: Keys must be unique, but values can be duplicated.
    • Example: {1: 'apple', 2: 'banana', 3: 'cherry'}

Quick summary in code:

# List: Mutable, ordered, allows duplicates
my_list = [1, 2, 2, 'apple']

# Tuple: Immutable, ordered, allows duplicates
my_tuple = (1, 2, 2, 'apple')

# Set: Mutable, unordered, no duplicates
my_set = {1, 2, 'apple'}

# Dictionary: Mutable, ordered (since Python 3.7), unique keys
my_dict = {1: 'apple', 2: 'banana', 3: 'apple'}

Each structure has its own use-cases depending on the requirements of mutability, order, and uniqueness in your Python program.