Exploring Concurrency in Python: asyncio, trio, and curio ⚡️🚀
Concurrency in Python is a powerful way to handle multiple tasks simultaneously without running into bottlenecks. When it comes to building high-performance applications, understanding how to leverage concurrency can make a huge difference. Today, we’ll explore three popular concurrency frameworks in Python: asyncio, trio, and curio.
1. What is Concurrency? 🤔
Concurrency involves executing multiple tasks at the same time, but not necessarily in parallel. It’s particularly useful for I/O-bound operations, like fetching data from APIs, reading files, or handling user requests in a web server.
Python has several ways to handle concurrency, but let’s focus on the asynchronous frameworks: asyncio, trio, and curio.
2. asyncio: The Standard Library’s Concurrency Tool 🛠️
asyncio is Python’s built-in library for asynchronous programming. It uses an event loop to manage tasks and allows you to write asynchronous code with async and await syntax.
Example of asyncio:
import asyncio
async def fetch_data():
print("Fetching data...")
await asyncio.sleep(2) # Simulating an I/O operation
print("Data fetched!")
async def main()…
