Detailed explanation of coroutines in Python

Python is a popular programming language that is widely used because of its simplicity, ease of learning, and wide range of applications. Among them, coroutine is a very important concept in Python and one of the foundations of asynchronous IO programming in Python. This article will provide a detailed explanation of coroutines in Python.

1. What is a coroutine?

Coroutine is a user-mode lightweight thread, which is more portable than operating system threads. It is implemented by the programmer in the program, so there is no overhead of switching context. The coroutine switching is completed by the program itself without external intervention. It can also reduce the creation of threads and use CPU resources more efficiently.

Characteristics of coroutines:

1. can run concurrently in the same thread, and the switching overhead is very small, so it supports high concurrency.
2. The status of the coroutine is managed by the programmer himself, which is more lightweight than a thread.

2. Implementation of coroutines

There are three ways to implement coroutines in Python: generator, async/await and combined with gevent. Below we introduce them one by one.

1. Generator

The generator in Python itself has the function of state saving and restoration, which is very suitable for implementing coroutines. The biggest feature of the generator coroutine is to use the yield statement to suspend the function and save the function state.

The following is an example of a coroutine:

def simple_coroutine(): print('-> coroutine started') x = yield print('-> coroutine received:', x) # 调用协程 my_coroutine = simple_coroutine() print(my_coroutine) #  # 先启动协程，让协程处于暂停状态。 next(my_coroutine) # -> coroutine started # 发送消息给协程，它会恢复执行，并打印出消息 my_coroutine.send('hello world') # -> coroutine received: hello world

In this example, the function simple_coroutine contains a yield expression, which is a sign of the generator coroutine. When the function is called , which returns a generator object. The program advances the generator to the first yield statement by calling the next() method, and prints the message "-> coroutine started". Then, we sent a message "hello world" to the generator, which was captured in the variable x and printed out "-> coroutine received: hello world".

2. async/await

After Python 3.5, Python provides native syntax async/await that supports coroutines. It provides cleaner syntax and better readability.

The following is an example of async/await:

import asyncio async def countdown(n): while n > 0: print(f'T-minus {n}') await asyncio.sleep(1.0) n -= 1 asyncio.run(countdown(3))

In this example, async/await allows us to use the keyword async in the function to define the coroutine, and use await to suspend the coroutine. Procedure. Of course, in order to use async/await syntax, we need to use the asyncio library.

3. Use with gevent

gevent is a Python network library based on coroutines. It provides a yield-based programming model that allows programmers to write asynchronous, non- Blocking code is easy to write and test. In order to use gevent, we need to install it via pip first.

The following is an example of using gevent:

import gevent def task(pid): """ 函数中的sleep模拟阻塞一段时间，通过gevent中的异步框架进行并发。 """ gevent.sleep(0.5) print(f'Task {pid} done') def synchronous(): """ 任务同步执行 """ for i in range(1, 10): task(i) def asynchronous(): """ 任务异步执行 """ threads = [gevent.spawn(task, i) for i in range(10)] gevent.joinall(threads) print('Synchronous:') synchronous() print('Asynchronous:') asynchronous()

In this example, we use the gevent framework to implement asynchronous coroutines. Through this example, we can clearly see that during asynchronous execution, tasks are performed alternately, taking advantage of the asynchronous characteristics of coroutines. During synchronous execution, we can see that tasks are executed one by one.

3. Advantages and Disadvantages of Coroutines

Advantages:

1. Coroutines are single-threaded by default, which avoids the overhead caused by multi-thread switching and improves efficiency. Program execution speed.
2. Coroutines can avoid multi-process GIL (Global Interpreter Lock) problems and improve program efficiency.
3. Coroutines can be created infinitely, but the number of threads and processes is limited, but opening too many coroutines will also cause performance problems.

Disadvantages:

1. Coroutines are special and require programmers to manually control the running status of the program. Its complexity is relatively high and requires more effort.
2. The coroutine code itself does not have an error handling mechanism, making it more difficult to handle exceptions and debug the code.

4. Summary

This article introduces in detail the concept, implementation methods and advantages and disadvantages of coroutines in Python. Coroutines are a very important concept in Python and one of the foundations of asynchronous IO programming. Through coroutines, we can run businesses concurrently in the same thread, improve program execution efficiency, avoid a lot of context switching overhead, and greatly save system resources. However, coroutines also have some shortcomings, such as requiring programmers to have high programming skills and imperfect error handling mechanisms. These problems require programmers to pay attention to when using coroutines.

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