Python native coroutines and send()

Question

Generator based coroutines have a send() method which allow bidirectional communication between the caller and the callee and resumes a yielded generator coroutine from the caller. This is the functionality that turns generators into coroutines.

While the new native async/await coroutines provide superior support for async I/O, I do not see how to get the equivalent of send() with them. The use of yield in async functions is explicitly forbidden, so native coroutines can return only once using a return statement. Although await expressions bring new values into a coroutine, those values come from callees, not the caller, and the awaited call is evaluated from the beginning each time, not from where it left off.

Is there a way to resume a returned coroutine from where it left off and potentially send in a new value? How can I emulate the techniques in David Beazley's Curious Course on Coroutines and Concurrency using native coroutines?

The general code pattern I have in mind is something like

def myCoroutine():   ...   while True:     ...     ping = yield(pong)     ... 

and in the caller

while True:   ...   buzz = myCoroutineGen.send(bizz)   ... 

---

Edit

I accepted Kevin's answer but I have noticed that the PEP says

Coroutines are based on generators internally, thus they share the implementation. Similarly to generator objects, coroutines have throw() , send() and close() methods.

...

throw() , send() methods for coroutines are used to push values and raise errors into Future-like objects.

So apparently native coroutines do have a send()? How does it work without yield expression to receive the values inside the coroutine?

Answer 1

After going through the same (fantastic, I must say) course on coroutines by Beazley, I asked myself the very same question - how could one adjust the code to work with the native coroutines introduced in Python 3.5?

It turns out it can be done with relatively small changes to the code. I will assume the readers are familiar with the course material, and will take the pyos4.py version as a base - the first Scheduler version that supports "system calls".

TIP: A full runnable example can be found in Appendix A at the end.

Objective

The goal is turn the following coroutine code:

def foo():     mytid = yield GetTid()  # a "system call"     for i in xrange(3):         print "I'm foo", mytid         yield  # a "trap" 

... into a native coroutine and still use just as before:

async def foo():     mytid = await GetTid()  # a "system call"     for i in range(3):         print("I'm foo", mytid)         await ???  # a "trap" (will explain the missing bit later) 

We want to run it without asyncio, as we already have our own event loop that drives the entire process - it's the Scheduler class.

Awaitable objects

Native coroutines do not work right off the bat, the following code results in an error:

async def foo():     mytid = await GetTid()     print("I'm foo", mytid)  sched = Scheduler() sched.new(foo()) sched.mainloop() 

 Traceback (most recent call last):     ...     mytid = await GetTid() TypeError: object GetTid can't be used in 'await' expression 

PEP 492 explains what kind of objects can be awaited on. One of the options is "an object with an __await__ method returning an iterator".

Just like yield from, if you are familiar with it, await acts as a tunnel between the object awaited on and the outermost code that drives the coroutine (usually an event loop). This is best demonstrated with an example:

class Awaitable:     def __await__(self):         value = yield 1         print("Awaitable received:", value)         value = yield 2         print("Awaitable received:", value)         value = yield 3         print("Awaitable received:", value)         return 42   async def foo():     print("foo start")     result = await Awaitable()     print("foo received result:", result)     print("foo end") 

Driving the foo() coroutine interactively produces the following:

>>> f_coro = foo()  # calling foo() returns a coroutine object >>> f_coro <coroutine object foo at 0x7fa7f74046d0> >>> f_coro.send(None) foo start 1 >>> f_coro.send("one") Awaitable received: one 2 >>> f_coro.send("two") Awaitable received: two 3 >>> f_coro.send("three") Awaitable received: three foo received result: 42 foo end Traceback (most recent call last):   File "<stdin>", line 1, in <module> StopIteration 

Whatever gets sent into f_coro is channeled down into the Awaitable instance. Similarly, whatever Awaitable.__await__() produces is bubbled up to the topmost code that sends the values in.

The entire process is transparent to the f_coro coroutine, which is not directly involved and does not see values being passed up and down. However, when Awaitable's iterator is exhausted, its return value becomes the result of the await expression (42 in our case), and that's where f_coro is finally resumed.

Note that await expressions in coroutines can also be chained. A coroutine can await another coroutine that awaits another coroutine... until the entire chain ends with a yield somewhere down the road.

Sending values into the coroutine itself

How can this knowledge help us? Well, in the course material a coroutine can yield a SystemCall instance. The scheduler understands these and lets the system call handle the requested operation.

In order for a coroutine to bring a SystemCall up to the scheduler, a SystemCall instance can simply yield itself, and it will be channeled up to the scheduler as described in the previous section.

The first required change is therefore to add this logic to the base SystemCall class:

class SystemCall:     ...     def __await__(self):         yield self 

With the SystemCall instances made awaitable, the following now actually runs:

async def foo():     mytid = await GetTid()     print("I'm foo", mytid)  >>> sched = Scheduler() >>> sched.new(foo()) >>> sched.mainloop() 

Output:

 I'm foo None Task 1 terminated 

Great, it does not crash anymore!

However, the coroutine did not receive the task ID, and got None instead. This is because the value set by the system call's handle() method and sent by the Task.run() method:

# in Task.run() self.target.send(self.sendval) 

... ended up in the SystemCall.__await__() method. If we want to bring the value into the coroutine, the system call must return it, so that it becomes the value of the await expression in the coroutine.

class SystemCall:     ...     def __await__(self):         return (yield self) 

Running the same code with the modified SystemCall produces the desired output:

 I'm foo 1 Task 1 terminated 

Running the coroutines concurrently

We still need a way to suspend a coroutine, i.e. to have a system "trap" code. In the course material, this is done with a plain yield inside a coroutine, but an attempt to use a plain await is actually a syntax error:

async def foo():     mytid = await GetTid()     for i in range(3):         print("I'm foo", mytid)         await  # SyntaxError here 

Fortunately, the workaround is easy. Since we already have working system calls, we can add a dummy no-op system call whose only job is to suspend the coroutine and immediately re-schedule it:

class YieldControl(SystemCall):     def handle(self):         self.task.sendval = None   # setting sendval is optional         self.sched.schedule(self.task) 

Setting a sendval on the task is optional, as this system call is not expected to produce any meaningful value, but we opt to make this explicit.

We now have everything in place to run a multitasking operating system!

async def foo():     mytid = await GetTid()     for i in range(3):         print("I'm foo", mytid)         await YieldControl()   async def bar():     mytid = await GetTid()     for i in range(5):         print("I'm bar", mytid)         await YieldControl()   sched = Scheduler() sched.new(foo()) sched.new(bar()) sched.mainloop() 

Output:

 I'm foo 1 I'm bar 2 I'm foo 1 I'm bar 2 I'm foo 1 I'm bar 2 Task 1 terminated I'm bar 2 I'm bar 2 Task 2 terminated 

Footnotes

The Scheduler code is completely unchanged.

It. Just. Works.

This shows the beauty of the original design where the scheduler and the tasks that run in it are not coupled to each other, and we were able to change the coroutine implementation without the Scheduler knowing about it. Even the Task class that wraps the coroutines did not have to change.

Trampolining is not needed.

In the pyos8.py version of the system, a concept of a trampoline is implemented. It allows the coroutines to delegate a part of their work to another coroutine with the help of the shceduler (the scheduler calls the sub-coroutine on behalf of the parent coroutine and sends the former's result into the parent).

This mechanism is not needed, since await (and its older companion, yield from) already make such chaining possible as explained at the beginning.

Appendix A - a full runnable example (requires Python 3.5+)

example_full.py

from queue import Queue   # ------------------------------------------------------------ #                       === Tasks === # ------------------------------------------------------------ class Task:     taskid = 0     def __init__(self,target):         Task.taskid += 1         self.tid = Task.taskid   # Task ID         self.target = target        # Target coroutine         self.sendval = None          # Value to send      # Run a task until it hits the next yield statement     def run(self):         return self.target.send(self.sendval)   # ------------------------------------------------------------ #                      === Scheduler === # ------------------------------------------------------------ class Scheduler:     def __init__(self):         self.ready = Queue()            self.taskmap = {}              def new(self,target):         newtask = Task(target)         self.taskmap[newtask.tid] = newtask         self.schedule(newtask)         return newtask.tid      def exit(self,task):         print("Task %d terminated" % task.tid)         del self.taskmap[task.tid]      def schedule(self,task):         self.ready.put(task)      def mainloop(self):          while self.taskmap:             task = self.ready.get()             try:                 result = task.run()                 if isinstance(result,SystemCall):                     result.task  = task                     result.sched = self                     result.handle()                     continue             except StopIteration:                 self.exit(task)                 continue             self.schedule(task)   # ------------------------------------------------------------ #                   === System Calls === # ------------------------------------------------------------ class SystemCall:     def handle(self):         pass      def __await__(self):         return (yield self)   # Return a task's ID number class GetTid(SystemCall):     def handle(self):         self.task.sendval = self.task.tid         self.sched.schedule(self.task)   class YieldControl(SystemCall):     def handle(self):         self.task.sendval = None   # setting sendval is optional         self.sched.schedule(self.task)   # ------------------------------------------------------------ #                      === Example === # ------------------------------------------------------------ if __name__ == '__main__':     async def foo():         mytid = await GetTid()         for i in range(3):             print("I'm foo", mytid)             await YieldControl()       async def bar():         mytid = await GetTid()         for i in range(5):             print("I'm bar", mytid)             await YieldControl()      sched = Scheduler()     sched.new(foo())     sched.new(bar())     sched.mainloop()