Add Graph Traversal algorithms (BFS and DFS) in Python

[Karanjot786]

📝 Description

This PR adds comprehensive Graph Traversal implementations including BFS (Breadth-First Search) and DFS (Depth-First
Search) with both iterative and recursive approaches.

📂 Files Added

• Python/data_structures/graphs/graph_traversal.py

✨ Features

• Graph class: Adjacency list representation
• Add edge methods: Support for both directed and undirected graphs
• BFS (Breadth-First Search): Level-order traversal using queue
• DFS (Depth-First Search): Two implementations:
  • Iterative version using stack
  • Recursive version
• Connectivity check: Verify if graph is connected
• Comprehensive test cases: 5 different scenarios including:
  • Simple undirected graph
  • Directed graph
  • Larger complex graph
  • Linear graph
  • Disconnected graph with connectivity check

📊 Complexity Analysis

• Time Complexity: O(V + E) for both BFS and DFS
  • V = number of vertices
  • E = number of edges
• Space Complexity: O(V) for visited set and queue/stack

🔑 Key Concepts

• Graph representation using adjacency list (defaultdict)
• BFS uses queue (FIFO) - finds shortest path in unweighted graphs
• DFS uses stack (LIFO) - explores as deep as possible
• Both iterative and recursive DFS implementations
• Connectivity checking using DFS

🎯 Use Cases

• BFS: Shortest path, level-order traversal, peer-to-peer networks
• DFS: Path finding, cycle detection, topological sorting, maze solving

✅ Testing

All test cases run successfully demonstrating:

• BFS and DFS on various graph structures
• Both directed and undirected graphs
• Iterative vs recursive DFS comparison
• Connectivity verification
• Edge cases with linear and disconnected graphs

🎃 Hacktoberfest 2025

This contribution is part of Hacktoberfest 2025. The code follows the repository's structure (Language/Topic/FileName) and
includes proper documentation.

📋 Checklist

• Code follows repository structure (Python/data_structures/graphs/)
• Proper documentation and comments added
• Test cases included
• Time and space complexity documented
• No user input required (tests run automatically)
• Code is well-formatted and readable

[github-actions]

🎉 Welcome to Hacktoberfest 2025, @Karanjot786! 🎃

Thank you for your first contribution to our DSA repository! Here's what happens next:

🔍 Automatic Checks

• ✅ Code Validation: Passed
• 🧪 Compilation Tests: Passed

📋 Next Steps

🎯 Great job! Your code compiled successfully. Maintainers @Karanjot786 and @Pradeepsingh61 will review your PR soon.

🎁 What You Get

• 🏆 Hacktoberfest Credit: This PR counts toward your 6 PR goal for exclusive T-shirt + Tree!
• 🌟 Hall of Fame: You'll be featured in our contributors list
• 📚 Learning: Code review feedback from experienced developers

💡 Tips for Success

• Follow our Contributing Guidelines
• Add comments explaining your algorithm
• Include time/space complexity analysis
• Test your code before submitting

Welcome to the community! 🚀

[github-actions]

🤖 Automated PR Status

🔍 Code Validation

✅ Passed - File naming and structure look good!

🧪 Compilation Tests

✅ Passed - All code compiles successfully!

📋 Overall Status

🎉 Ready for Review - Your PR has passed all automated checks!
👥 Maintainers have been notified for review.

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