How can concurrent programming be implemented in Python?

6 months ago

2 minutes

In Python, there are several methods to implement concurrent programming, with the most commonly used ones being threads and coroutines. Here are some popular methods for concurrent programming:

By utilizing the threading module, you can create and manage threads in order to concurrently execute multiple tasks and improve the performance of a program. Using the threading.Thread class allows for the creation of new threads, which can be started using the start() method. The threading.Lock class can be used to implement synchronization between threads.

import threading

def worker():
    print('Hello from worker')

thread = threading.Thread(target=worker)
thread.start()

With the concurrent.futures module, you can easily manage concurrent tasks using the ThreadPoolExecutor class to create a thread pool and submit tasks with the submit() method. The ThreadPoolExecutor.map() method can be used to execute multiple tasks concurrently and return the results.

from concurrent.futures import ThreadPoolExecutor

def worker():
    return 'Hello from worker'

with ThreadPoolExecutor() as executor:
    result = executor.submit(worker).result()
    print(result)

The asyncio module offers support for asynchronous programming, allowing you to define coroutines using the async and await keywords. You can run coroutines using the asyncio.run() function. Tasks can be created using the asyncio.create_task() function, and then awaited for completion using the await keyword.

import asyncio

async def worker():
    return 'Hello from worker'

async def main():
    task = asyncio.create_task(worker())
    result = await task
    print(result)

asyncio.run(main())

These are common methods for implementing concurrent programming in Python, and developers can choose the appropriate method according to their specific needs.