A living repository documenting my journey through the world of algorithms and data structures
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class LearningPhilosophy:
def __init__(self):
self.approach = "Learn by Building"
self.focus = ["Understanding", "Implementation", "Optimization"]
def commit(self):
while self.curiosity > 0:
self.learn()
self.implement()
self.solve_problems()
self.document()
return "Master DSA 🎓"This isn't just another DSA repository—it's a documented learning journey. Each implementation includes:
- 📝 Clear explanations and comments
- 🎨 Visual representations where applicable
- ⚡ Time and space complexity analysis
- 🧪 Practice problems and real-world applications
While this repo covers DSA fundamentals and implementations, I'm also grinding LeetCode daily to sharpen my problem-solving skills.
Pattern recognition • Optimized solutions • Multiple approaches
Language: Python 3.x
Libraries:
- NumPy: For efficient array operations
- Built-in collections: deque, heapq (coming soon)
Environment: VS Code
Approach: First Principles + Practical Implementation# Clone this repository
git clone https://github.com/ggauravky/DSA-with-Python.git
# Navigate to the project
cd "DSA with Python"
# Explore any topic
cd "001 Basics"
# Run and experiment
python "006 Functions.py"💡 Pro Tip: Start with
001 Basicsif you're new, or jump directly to data structures if you're comfortable with Python fundamentals.
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✅ Python Fundamentals
✅ Complexity Analysis
✅ Recursion Mastery
✅ Arrays & Linked Lists
✅ Stack, Queue, Deque
🔄 Trees & Graphs (In Progress)
⏳ Dynamic Programming
⏳ Advanced Algorithms