Asynchronous Programming: Multithreading, Multi-core Processing, and Asyncio

Author - Aryan Pandey

Welcome to the Asynchronous Programming repository! This repo provides a hands-on guide to mastering parallel processing concepts and techniques such as Multithreading, Multi-core Processing, and Asyncio in Python. Whether you are a beginner or an intermediate learner, this repository offers basic programming files, along with project examples, to help you dive into asynchronous programming.

Folder Structure

Asynchronous Programming/
│
├── 1) Multithreading/
│   ├── basics/
|   ├── project/
│   └── README.md
│
├── 2) Multi-core Processing/
│   ├── basics/
│   └── README.md
│
├── 3) Asyncio/
│   ├── basics/
│   ├── project/
│   └── README.md/
│
└── README.md

Overview of Techniques

1. Multithreading
   Learn how to run multiple threads concurrently, making your program more efficient when working with I/O-bound tasks (e.g., reading files, network calls).

2. Multi-core Processing
   Take advantage of multiple CPU cores to distribute CPU-bound tasks, like heavy computations, across multiple processors.

3. Asyncio
   Master event-driven programming using the asyncio library in Python to handle I/O-bound tasks asynchronously and improve the responsiveness of your application.

Getting Started

1. Clone the repository

   git clone https://github.com/ltd-ARYAN-pvt/Introduction-to-Parallel-Processing-and-Asynchronous-Programming.git
   

2. Set up the environment
   Make sure you have Python installed (version 3.7+ is recommended). You may want to set up a virtual environment:

   python -m venv venv
   source venv/bin/activate  # For Linux/Mac
   venv\Scripts\activate  # For Windows
   

3. Install dependencies
   Ayncio project example requires additional Python libraries. Navigate to the project folder and install required packages:

   pip install aiohttp
   

Folder Details

1) Multithreading

• Basics:
  Includes introductory examples to help you understand the concept of threads, creating and managing threads, synchronization, and thread-safe operations.

• Projects:
  Image Downlaoder App:- Download apps parallely from picsum.photos using multithreading.

2) Multi-core Processing

• Basics:
  Learn how to use Python’s multiprocessing library to run CPU-bound tasks on multiple cores.

• Projects:
  For this i want you to try a Random forest classifier model and first set n_jobs=-1 and see the training speed then set it to default and then see the speed of training.

3) Asyncio

• Basics:
  Get started with asynchronous programming using Python’s asyncio library. Learn about async functions, coroutines, tasks, and the event loop.

• Projects:
  Image Downlaoder App:- Download apps asynchronously from picsum.photos using asyncio and aiohttp.

Example Usage

Here's a simple example of using asyncio to fetch data from multiple URLs:

import asyncio
import aiohttp

async def fetch(url):
    async with aiohttp.ClientSession() as session:
        async with session.get(url) as response:
            return await response.text()

async def main():
    urls = ["https://example.com", "https://python.org"]
    tasks = [fetch(url) for url in urls]
    results = await asyncio.gather(*tasks)
    for result in results:
        print(result)

asyncio.run(main())

Running a Project

To run a specific project, navigate to the respective folder, follow the instructions provided in the project’s README.md, and execute the Python scripts.

Contribution Guidelines

Contributions are welcome! If you’d like to add more examples or projects:

1. Fork the repository.
2. Create a new branch.
3. Make your changes.
4. Open a pull request.

Feel free to open issues if you encounter any problems or have questions!

License

This project is licensed under the MIT License. See the LICENSE file for details.