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Python Fundamentals

Created by OpenAI DALL-E 2

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Welcome to Python Fundamentals, a comprehensive collection of Python code implementations for basic and advanced concepts in the Python programming language. In this project, you will find the following

Basic Concepts ❄️

  • Variables and data types
  • Operators and expressions
  • Control flow statements (if-else, for loops, while loops)
  • Function

Advanced Concepts 🔥

  • Object-Oriented Programming (OOP)
  • Iterators and generators
  • Decorators
  • Exception handling

Data Structures 🌌

  • Array
  • Linked List
  • Stack
  • Queue
  • Binary Tree
  • Binary Search Tree
  • Graph
  • Heap
  • Bloom Filter
  • Disjoin Set
  • Trie
  • Priority Queue
  • Skip List
  • Hash Table
  • And many more data structures will be updated later

Algorithms 🚀

  • Sorting algorithms (Bubble sort, Insertion sort, Selection sort, etc.)
  • Searching algorithms (Linear search, Binary search, etc.)
  • Graph Algorithms
  • Backtracking Algorithms
  • Dynamic Programming
  • Greedy Algorithms
  • Brute Force Algorithms

Each concept and data structure has been thoroughly documented with clear explanations and examples to help you understand how they work and how to use them effectively. I also provide test cases for each implementation to ensure that they are working correctly.

Others 🔨

This project also includes the implementation in Python of different subjects such as mathematics, physics, and among others.

Getting Started ⚡

To get started with the project, simply clone the repository to your local machine and navigate to the appropriate folder for the concept or data structure you wish to learn about. Each implementation has its dedicated folder with the necessary files and documentation.

Run project locally on your computer without Docker

$ git clone https://github.com/TruongNhanNguyen/Python-Fundamentals.git
$ make

Run with Docker

docker pull sozeldocker/python-fundamentals
docker run -it --rm sozeldocker/python-fundamentals

All algorithms are implemented in Python (for educational purposes).

These implementations are intended for learning purposes. As such, they may be less efficient than the Python libraries.

Contributing 💖 👏

I always welcome contributions to this project. If you have an implementation of a concept or data structure that is not included here, or you have found an error in our code, please feel free to submit a pull request.

Please read the Contribution Guidelines before you contribute to this project.

License ✒️

This project is licensed under the MIT License

Contact 📧

If you have any questions or feedback about this project, please feel free to reach out to us at my email - nhantruongnguyen@123.com

Acknowledgments ❤️

I would like to thank the community for their support and contributions to this project.