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What are the concurrent programming models in Python? - Code example
In modern computer systems, we usually need to deal with multiple tasks running at the same time. Concurrent programming is a programming model that allows a program to handle multiple tasks at the same time. Python provides a variety of concurrent programming models. This article will introduce several of them and give corresponding code examples.
A thread is a lightweight execution unit that can run in the same process and share the same resources. In Python, we can use the threading
module to create and manage threads.
import threading import time def task(): print("Thread is running...") time.sleep(2) print("Thread is done.") if __name__ == "__main__": thread = threading.Thread(target=task) thread.start() print("Main thread is running...") thread.join() # 等待子线程运行完毕 print("Main thread is done.")
The process is the entity on which the program runs. Each process has its own independent memory space and resources. In Python, we can use the multiprocessing
module to create and manage processes.
import multiprocessing import time def task(): print("Process is running...") time.sleep(2) print("Process is done.") if __name__ == "__main__": process = multiprocessing.Process(target=task) process.start() print("Main process is running...") process.join() # 等待子进程运行完毕 print("Main process is done.")
Coroutine is a lightweight subroutine that can be switched and executed within the program. In Python, we can use the asyncio
module to implement coroutine programming.
import asyncio async def task(): print("Coroutine is running...") await asyncio.sleep(2) print("Coroutine is done.") if __name__ == "__main__": loop = asyncio.get_event_loop() loop.run_until_complete(task()) loop.close()
Asynchronous programming is an event-driven programming model that can handle multiple tasks in the same thread. In Python, we can use the asyncio
module and the await/async
keyword to implement asynchronous programming.
import asyncio async def task(): print("Async task is running...") await asyncio.sleep(2) print("Async task is done.") async def main(): await asyncio.gather(task(), task()) if __name__ == "__main__": asyncio.run(main())
Summary:
This article introduces several concurrent programming models in Python and gives corresponding code examples. Using multi-threading, multi-process, coroutine and asynchronous programming models, we can better utilize the resources of the computer system and improve the performance and responsiveness of the program. However, in actual applications, it is necessary to choose an appropriate programming model according to specific needs and scenarios to obtain the best concurrency effect.
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