This content originally appeared on DEV Community and was authored by Aditi Sharma
Today, I wrapped up learning about Sets and explored more about data structures in Python.
🔹 What are Sets?
• Unordered collections of unique elements.
• Defined using curly braces {}.
• No duplicates allowed.
fruits = {"apple", "banana", "cherry", "apple"}
print(fruits) # {'apple', 'banana', 'cherry'}
🔑 Common Set Operations
a = {1, 2, 3}
b = {3, 4, 5}
print(a.union(b)) # {1, 2, 3, 4, 5}
print(a.intersection(b)) # {3}
print(a.difference(b)) # {1, 2}
print(a.symmetric_difference(b)) # {1, 2, 4, 5}
âś… Sets are very useful for mathematical operations, filtering, and removing duplicates.
🔹 Why Use Sets?
• Fast membership testing (in operator).
• Automatically remove duplicates.
• Great for mathematical/logical operations.
🔹 Data Structures Recap in Python
- List → Ordered, mutable.
- Tuple → Ordered, immutable.
- Set → Unordered, unique items.
- Dictionary → Key-value pairs.
Each data structure has its own strengths depending on the use case (speed, immutability, uniqueness, etc.).
🎯 Reflection
Sets introduced me to powerful operations for handling unique data. Understanding Python’s core data structures is essential because they form the foundation of problem-solving, algorithms, and real-world applications.
⚡ Next up: I’ll dive into libraries and explore advanced coding practices.
Python #100DaysOfCode #LearningJourney #DataStructures
This content originally appeared on DEV Community and was authored by Aditi Sharma
Aditi Sharma | Sciencx (2025-09-05T08:18:26+00:00) 🚀 Day 8 of My Python Learning Journey – Sets & Data Structures in Python. Retrieved from https://www.scien.cx/2025/09/05/%f0%9f%9a%80-day-8-of-my-python-learning-journey-sets-data-structures-in-python/
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