我发现大多数答案都太专业了，尽管这是一个技术问题。我很难理解协同程序的过程。我有点明白，但我不能同时明白。

我发现这个答案非常有用:

https://dev.to/thibmaek/explain-coroutines-like-im-five-2d9

引用伊丹·阿耶的话:

To build on your story, I'd put it something like this: You start watching the cartoon, but it's the intro. Instead of watching the intro you switch to the game and enter the online lobby - but it needs 3 players and only you and your sister are in it. Instead of waiting for another player to join you switch to your homework, and answer the first question. The second question has a link to a YouTube video you need to watch. You open it - and it starts loading. Instead of waiting for it to load, you switch back to the cartoon. The intro is over, so you can watch. Now there are commercials - but meanwhile a third player has joined so you switch to the game And so on... The idea is that you don't just switch the tasks really fast to make it look like you are doing everything at once. You utilize the time you are waiting for something to happen(IO) to do other things that do require your direct attention.

一定要检查链接，还有更多我不能引用的东西。

协程作为并发性的实现和多线程的替代方案。

协程是实现并发的单线程解决方案。

         A-Start ------------------------------------------ A-End   
           | B-Start -----------------------------------------|--- B-End   
           |    |      C-Start ------------------- C-End      |      |   
           |    |       |                           |         |      |
           V    V       V                           V         V      V      
1 thread->|<-A-|<--B---|<-C-|-A-|-C-|--A--|-B-|--C-->|---A---->|--B-->| 

与多线程解决方案相比:

thread A->|<--A|          |--A-->|
thread B------>|<--B|            |--B-->|
thread C ---------->|<---C|             |C--->|

协程是异步编程的一种实现，异步编程用于实现并发。 许多语言使用协程实现异步编程。其他答案表明Python, Kotlin, Lua, c++已经做到了。 最有用/通常用于涉及I/O绑定问题的场景，例如在获取数据时呈现UI，或从多个数据源下载。

协程和并发在很大程度上是正交的。协程是一种通用的控制结构，流控制在两个不同的例程之间协作传递而不返回。

Python中的'yield'语句就是一个很好的例子。它创建了一个协程。当遇到yield时，将保存函数的当前状态，并将控制返回给调用函数。然后，调用函数可以将执行转移回屈服函数，它的状态将恢复到遇到“屈服”的位置，并继续执行。

我发现大多数答案都太专业了，尽管这是一个技术问题。我很难理解协同程序的过程。我有点明白，但我不能同时明白。

我发现这个答案非常有用:

https://dev.to/thibmaek/explain-coroutines-like-im-five-2d9

引用伊丹·阿耶的话:

To build on your story, I'd put it something like this: You start watching the cartoon, but it's the intro. Instead of watching the intro you switch to the game and enter the online lobby - but it needs 3 players and only you and your sister are in it. Instead of waiting for another player to join you switch to your homework, and answer the first question. The second question has a link to a YouTube video you need to watch. You open it - and it starts loading. Instead of waiting for it to load, you switch back to the cartoon. The intro is over, so you can watch. Now there are commercials - but meanwhile a third player has joined so you switch to the game And so on... The idea is that you don't just switch the tasks really fast to make it look like you are doing everything at once. You utilize the time you are waiting for something to happen(IO) to do other things that do require your direct attention.

一定要检查链接，还有更多我不能引用的东西。

在Lua编程中，“协程”部分:

A coroutine is similar to a thread (in the sense of multithreading): it is a line of execution, with its own stack, its own local variables, and its own instruction pointer; but it shares global variables and mostly anything else with other coroutines. The main difference between threads and coroutines is that, conceptually (or literally, in a multiprocessor machine), a program with threads runs several threads in parallel. Coroutines, on the other hand, are collaborative: at any given time, a program with coroutines is running only one of its coroutines, and this running coroutine suspends its execution only when it explicitly requests to be suspended.

所以关键是:协程是“协作的”。即使在多核系统中，也只有一个协程在任何给定时间运行(但多个线程可以并行运行)。协程之间存在不可抢占性，运行中的协程必须显式放弃执行。

关于“并发性”，你可以参考Rob Pike的幻灯片:

并发是独立执行计算的组合。

所以在协程A的执行过程中，它把控制权传递给了协程B。经过一段时间后，协程B又把控制权传递给了协程A。由于协程之间存在依赖关系，它们必须串联运行，所以这两个协程不是并发的。

我将详述@user21714的答案。协程是独立的执行路径，不能同时运行。它们依赖于一个控制器(例如python控制器库)来处理这些路径之间的切换。但是为了实现这一点，协同程序本身需要调用yield或类似的结构，以允许它们的执行暂停。

相反，线程运行在独立的计算资源上，并且彼此并行。由于它们位于不同的资源上，因此不需要调用yield来允许其他执行路径继续进行。

您可以通过启动一个多线程程序(例如jvm应用程序)来看到这种效果，其中所有八个核心i7超线程核心都被利用了:您可能会在Activity Monitor或Top中看到797%的利用率。相反，当运行一个典型的python程序(即使是带有协程或python线程的程序)时，利用率最高将达到100%。例如，一台机器超线程。