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From Novice to Pro: Transitioning from Lists to Sets in Python

Table of Contents

From Novice to Pro: Transitioning from Lists to Sets in Python

Sets in Python are a powerful tool that can significantly enhance your code’s efficiency. Here’s why sets are so useful:

Uniqueness Guaranteed


Sets automatically eliminate duplicates, ensuring each element appears only once.

unique_numbers = set([1, 2, 2, 3, 3, 3, 4])
unique_numbers
{1, 2, 3, 4}

Lightning-Fast Lookups


Membership testing in sets is extremely fast (O(1) on average).

large_set = set(range(1000000))
999999 in large_set  # Nearly instant!
True

Efficient Set Operations

Perform mathematical set operations with ease.

Union: Combine sets to get all unique elements

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

more_fruits = {"mango", "grape"}
all_fruits = fruits.union(more_fruits)
all_fruits
{'apple', 'banana', 'cherry', 'grape', 'mango'}

Intersection: Find common elements between sets

tropical_fruits = {"banana", "mango", "pineapple"}
common_fruits = all_fruits.intersection(tropical_fruits)
common_fruits
{'banana', 'mango'}
# Difference with another set
non_tropical_fruits = all_fruits.difference(tropical_fruits)
non_tropical_fruits
{'apple', 'cherry', 'grape'}

Memory Efficiency

Sets can be more memory-efficient than lists for storing large amounts of unique data.

Quick Deduplication

Convert a list to a set and back to quickly remove duplicates.

deduplicated = list(set([1, 2, 2, 3, 3, 3])

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Work with Khuyen Tran

Work with Khuyen Tran