September 11, 2024

Python Tutorials

Set vs. List in Python

In Python, both sets and lists are used to store collections of items, but they have distinct characteristics and use cases. Understanding the differences between sets and lists can help you choose the right data structure for your needs.

Lists

A list is an ordered collection of items that allows duplicates. Lists are defined using square brackets [] and can hold items of different data types.

Characteristics of Lists

  • Ordered: Items in a list are maintained in the order they are added. You can access elements by their index.
  • Allow Duplicates: Lists can contain duplicate values.
  • Mutable: You can modify the contents of a list after it is created (e.g., adding, removing, or changing elements).

Example of a List

# Creating a list
my_list = [1, 2, 3, 4, 5, 2]

# Accessing elements
print(my_list[2])  # Output: 3

# Modifying elements
my_list[1] = 10
print(my_list)  # Output: [1, 10, 3, 4, 5, 2]

# Adding elements
my_list.append(6)
print(my_list)  # Output: [1, 10, 3, 4, 5, 2, 6]

# Removing elements
my_list.remove(10)
print(my_list)  # Output: [1, 3, 4, 5, 2, 6]

Sets

A set is an unordered collection of unique items. Sets are defined using curly braces {} and do not allow duplicates.

Characteristics of Sets

  • Unordered: Sets do not maintain the order of elements. Items cannot be accessed by index.
  • Unique Elements: Sets automatically remove duplicate items.
  • Mutable: You can add and remove elements from a set after it is created.

Example of a Set

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

# Displaying the set
print(my_set)  # Output: {1, 2, 3, 4, 5}  (Note: Order is not guaranteed)

# Adding elements
my_set.add(6)
print(my_set)  # Output: {1, 2, 3, 4, 5, 6}

# Removing elements
my_set.remove(3)
print(my_set)  # Output: {1, 2, 4, 5, 6}

Key Differences

Feature List Set
Order Ordered Unordered
Duplicates Allows duplicates Unique elements only
Indexing Yes No
Performance for Membership Tests O(n) O(1) on average

Use Cases

  • Lists: Use lists when you need to maintain the order of elements, allow duplicates, or need to access elements by index.
  • Sets: Use sets when you need a collection of unique items and do not require ordering or indexing. Sets are also more efficient for membership tests and removing duplicates from a collection.

Conclusion

Both lists and sets are powerful data structures in Python, each with its own strengths and use cases. Choosing between them depends on whether you need to maintain order and allow duplicates (lists) or if you need a collection of unique items with efficient membership testing (sets).

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