🐍 Python Tutorial: Concurrency & Async Programming

1. Threading

Threads share memory and are great for I/O-bound operations (like file reading or network calls).

import threading

def greet():
    print("Hello from thread!")

thread = threading.Thread(target=greet)
thread.start()
thread.join()

2. Multiprocessing

Use this for CPU-bound tasks. It bypasses Python's GIL (Global Interpreter Lock) by creating new processes.

from multiprocessing import Process

def compute():
    print("Heavy computation in a separate process.")

process = Process(target=compute)
process.start()
process.join()

3. AsyncIO

AsyncIO uses cooperative multitasking and is excellent for managing many concurrent I/O tasks.

import asyncio

async def say_hello():
    print("Hello")
    await asyncio.sleep(1)
    print("World")

asyncio.run(say_hello())

4. When to Use Each

• Threading: Ideal for I/O-bound tasks like downloading, file access
• Multiprocessing: Use for CPU-heavy tasks like data processing or math
• AsyncIO: Best when handling thousands of network or file operations concurrently

5. Async Example with HTTP

Here's an example of asynchronous HTTP requests using aiohttp:

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():
    html = await fetch("https://example.com")
    print(html)

asyncio.run(main())

Additional Resources & References