Python Data Structures

Lists

A list is a collection which is ordered and changeable (mutable). Lists allow duplicate members and are Python's version of a dynamic array. They are one of the most versatile data types.

• Indexing & Slicing: Access elements with my_list[i] and ranges with my_list[start:stop:step].
• Common Methods: .append(item), .insert(i, item), .pop(i), .remove(item), .sort(), .reverse().
• List Comprehensions: A concise way to create lists. For example, squares = [x*x for x in range(10)] creates a list of the first 10 squares.

my_list = ["apple", "banana", "cherry"]
my_list.append("orange")    # Add item to end -> ['apple', 'banana', 'cherry', 'orange']
my_list[1] = "mango"        # Change an item -> ['apple', 'mango', 'cherry', 'orange']
print(my_list[1:3])         # Slicing -> ['mango', 'cherry']

Tuples

A tuple is a collection which is ordered and unchangeable (immutable). Tuples allow duplicate members and are written with round brackets.

Because they are immutable, they can be used as keys in a dictionary, unlike lists. They are also generally slightly more memory-efficient than lists.

• Use Cases: Use tuples for data that should not change, like coordinates (x, y), or for returning multiple values from a function.
• Unpacking: You can assign the values of a tuple to multiple variables at once. e.g., x, y = (10, 20).

my_tuple = ("apple", "banana", "cherry")
print(my_tuple[0]) # Access items like a list
# my_tuple[0] = "mango"  -> This would cause a TypeError!

Sets

A set is a collection which is unordered, unindexed, and has no duplicate members. They are highly optimized for membership testing.

Sets support powerful mathematical operations like union, intersection, difference, and symmetric difference.

• Common Methods: .add(item), .remove(item) (raises error if not found), .discard(item) (does nothing if not found), .pop().
• Set Operations: Use operators (| for union, & for intersection) or methods (.union(), .intersection()).

my_set = {"apple", "banana", "cherry"}
my_set.add("apple")   # Does nothing, as "apple" is already in the set
print("banana" in my_set) # Fast membership testing -> True

Dictionaries

A dictionary is a collection which is ordered (as of Python 3.7), changeable, and does not allow duplicate keys. They store data in key-value pairs and are optimized for retrieving values when the key is known.

• Accessing Items: Use square brackets my_dict['key'] (raises error if key not found) or the .get('key') method (returns None or a default value if not found).
• Iterating: You can iterate over keys, values, or both using .keys(), .values(), and .items().

my_dict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
my_dict["year"] = 2024   # Change a value
my_dict["color"] = "red" # Add a new key-value pair
print(my_dict.get("model"))