The Algorithms - Python

All algorithms implemented in Python - for education 📚

Note: These implementations are for learning purposes only. They may be less efficient than the implementations in the Python standard library. Use them at your discretion.

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🌟 Quick Links

🚀 Get Started • 📖 Browse Algorithms • 💻 Code Examples • 🤝 Contribute • 💬 Join Discord

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📑 Table of Contents

• ✨ Why Choose This Repository?
• 🚀 Getting Started
• 📚 Algorithm Categories
• 💡 Usage Examples
• 🤝 Contributing
• 🌐 Community Channels
• 🎓 Learning Path
• 🛠️ Development Setup
• 🧪 Testing
• 📊 Project Stats
• 📖 Resources
• 🏆 Top Contributors
• 📜 License
• 💬 Get Help
• ⭐ Show Your Support

✨ Why Choose This Repository?

• 🎓 Perfect for Learning: Clean, well-commented code designed specifically for educational purposes
• 📈 1300+ Implementations: One of the most comprehensive algorithm collections on GitHub
• ✅ Quality Assured: Every algorithm includes tests and passes continuous integration
• 🌍 Community-Driven: Thousands of contributors worldwide, actively maintained
• 📝 Well-Documented: Detailed docstrings, complexity analysis, and usage examples
• 🔬 Multiple Domains: From basic sorting to machine learning, cryptography to computer vision
• 🚀 Ready to Use: Copy, learn from, and adapt code for your projects
• 🎯 Interview Prep: Perfect resource for coding interviews and competitive programming

🚀 Getting Started

Prerequisites

• Python 3.8 or higher
• pip (Python package installer)

Installation

1. Clone the repository:

git clone https://github.com/TheAlgorithms/Python.git
cd Python

2. Install dependencies:

pip install -r requirements.txt

3. Run any algorithm:

python3 sorts/quick_sort.py
python3 searches/binary_search.py

Running Tests

pytest

📚 Algorithm Categories

Computer Science Fundamentals 🗂️ Data Structures (Arrays, Trees, Graphs, Heaps) 🔄 Sorting (Quick, Merge, Heap, Radix, etc.) 🔍 Searching (Binary, Ternary, Jump, etc.) 🔙 Backtracking (N-Queens, Sudoku, Maze) 🌊 Divide and Conquer 💰 Dynamic Programming 🎯 Greedy Algorithms 📊 Graph Algorithms (BFS, DFS, Dijkstra, Floyd-Warshall) Mathematics & Science ➕ Mathematical Algorithms 🔢 Number Theory 📐 Geometry & Computational Geometry 🧮 Linear Algebra & Matrix Operations 📈 Statistics & Probability ⚛️ Physics Simulations 🌍 Geodesy

Machine Learning & AI 🤖 Machine Learning (Regression, Classification) 🧠 Neural Networks 🧬 Genetic Algorithms 🎲 Fuzzy Logic 📊 Data Mining Applied Computer Science 🔐 Cryptography & Ciphers 🖼️ Computer Vision 🎨 Digital Image Processing 🎵 Audio Filters 🌐 Web Programming 📡 Networking & Data Transfer 🗜️ Data Compression 💹 Financial Algorithms ⚡ Electronics & Circuit Design

📖 See our complete DIRECTORY.md for the full list of all 1300+ implementations.

💡 Usage Examples

Quick Start - Sorting

from sorts.quick_sort import quick_sort

arr = [64, 34, 25, 12, 22, 11, 90]
sorted_arr = quick_sort(arr)
print(sorted_arr)  # [11, 12, 22, 25, 34, 64, 90]

Binary Search

from searches.binary_search import binary_search

sorted_list = [1, 3, 5, 7, 9, 11, 13, 15, 17]
target = 7
index = binary_search(sorted_list, target)
print(f"Found {target} at index {index}")  # Found 7 at index 3

Graph Algorithms - Dijkstra's Shortest Path

from graphs.dijkstra import dijkstra

# Graph represented as adjacency list
graph = {
    'A': {'B': 1, 'C': 4},
    'B': {'C': 2, 'D': 5},
    'C': {'D': 1},
    'D': {}
}

distances = dijkstra(graph, 'A')
print(distances)  # {'A': 0, 'B': 1, 'C': 3, 'D': 4}

Machine Learning - Linear Regression

from machine_learning.linear_regression import LinearRegression

X = [[1], [2], [3], [4], [5]]
y = [2, 4, 6, 8, 10]

model = LinearRegression()
model.fit(X, y)
prediction = model.predict([[6]])
print(prediction)  # ~12

Cryptography - Caesar Cipher

from ciphers.caesar_cipher import encrypt, decrypt

message = "HELLO WORLD"
encrypted = encrypt(message, shift=3)
print(encrypted)  # "KHOOR ZRUOG"

decrypted = decrypt(encrypted, shift=3)
print(decrypted)  # "HELLO WORLD"

🤝 Contributing

We love contributions! This project exists thanks to all the people who contribute.

📋 Read through our Contribution Guidelines before you contribute.

How to Contribute

1. Fork the repository
2. Create a new branch (git checkout -b feature/algorithm-name)
3. Make your changes and commit (git commit -am 'Add new algorithm')
4. Push to the branch (git push origin feature/algorithm-name)
5. Create a Pull Request

🌐 Community Channels

We are on Discord and Gitter! Community channels are a great way for you to ask questions and get help. Please join us!

🎓 Learning Path

New to algorithms? Follow this recommended learning path:

1. Start with Basics: sorts/ → searches/ → data_structures/
2. Build Foundation: recursion/ → backtracking/ → divide_and_conquer/
3. Advanced Topics: dynamic_programming/ → graphs/ → greedy_methods/
4. Specialized Areas: machine_learning/ → ciphers/ → neural_network/

Each directory contains a README with explanations and complexity analysis.

🛠️ Development Setup

Using Virtual Environment

# Create virtual environment
python -m venv venv

# Activate it
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

Using pre-commit hooks

pip install pre-commit
pre-commit install

This will automatically format your code and run checks before each commit.

🧪 Testing

# Run all tests
pytest

# Run tests for a specific module
pytest sorts/test_sorts.py

# Run with coverage
pytest --cov=. --cov-report=html

📊 Project Stats

• Total Implementations: 1300+ algorithms
• Lines of Code: 100,000+
• Contributors: 1000+
• Stars: Check the repo!
• Programming Language: Python 3.8+

📖 Resources

• 🌐 The Algorithms Website
• 📚 Python Algorithm Documentation
• 📝 Contributing Guide
• 🤝 Code of Conduct
• 🎥 Video Tutorials

🏆 Top Contributors

A huge thanks to all our contributors! This project wouldn't be possible without you.

📜 License

This project is licensed under the MIT License - see the LICENSE.md file for details.

💬 Get Help

• 📫 Create an Issue for bug reports or feature requests
• 💭 Join our Discord for discussions
• 🗨️ Ask questions on Gitter

⭐ Show Your Support

If you find this project helpful:

• Give it a ⭐ star on GitHub
• Share it with your friends and colleagues
• Contribute by adding new algorithms or improving existing ones
• Help us translate documentation

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Made with ❤️ by contributors around the 🌍
_{Happy Coding! 🚀}