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Advanced-Python: A course that explores Python beyond the basics, covering advanced concepts such as object-oriented programming, decorators, generators, context managers, metaclasses, concurrency, and best practices for writing efficient, scalable, and maintainable Python code.

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Advanced-Python

Advanced-Python is a repository dedicated to exploring Python beyond the basics. It focuses on advanced concepts, techniques, and best practices to write efficient, scalable, and maintainable Python code.

Features

This repository covers topics such as:

  • Object-Oriented Programming (OOP) – Classes, Inheritance, Polymorphism, Encapsulation, Abstraction
  • Decorators and Higher-Order Functions
  • Generators and Iterators
  • Context Managers and the with statement
  • Metaclasses and Dynamic Class Creation
  • Concurrency – threading, multiprocessing, asyncio
  • Pythonic Best Practices and Design Patterns

Getting Started

Prerequisites

  • Python 3.8 or higher
  • Pip (Python package manager)

Installation

Clone the repository:

git clone https://github.com/yourusername/Advanced-Python.git
cd Advanced-Python

(Optional) Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Install required packages (if any):

pip install -r requirements.txt

Usage

Explore the scripts and notebooks in the repository. Each module focuses on a specific advanced Python concept. Run the scripts using:

python filename.py

Contributing

Contributions are welcome!

  1. Fork the repository
  2. Create a new branch (git checkout -b feature/YourFeature)
  3. Commit your changes (git commit -m 'Add feature')
  4. Push to the branch (git push origin feature/YourFeature)
  5. Open a Pull Request

License

This project is licensed under the MIT License.


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Advanced-Python: A course that explores Python beyond the basics, covering advanced concepts such as object-oriented programming, decorators, generators, context managers, metaclasses, concurrency, and best practices for writing efficient, scalable, and maintainable Python code.

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