It was not sufficient. The only way to communicate with a Subprocesses is using stdout, stdin and stderr. However, packages like Tensroflow will print messages to stdout, and this can be hard to turn off.
It seems useful to have a class like multiprocessing.Pipe to communicate with another process, separately from stdout/stdin. On Mon, Dec 28, 2020 at 12:50 PM Guido van Rossum <gu...@python.org> wrote: > The asyncio module already has a subprocess support: Subprocesses — > Python 3.9.1 documentation > <https://docs.python.org/3/library/asyncio-subprocess.html> > > Was that not sufficient to solve your problem? > > > On Mon, Dec 28, 2020 at 5:23 AM Roger Iyengar <raiye...@cs.cmu.edu> wrote: > >> I believe that asyncio should have a way to wait for input from a >> different process without blocking the event loop. >> >> The Asyncio module currently contains a Queue class that allows >> communication between multiple coroutines running on the same event loop. >> However, this module is not threadsafe or process-safe. >> >> The multiprocessing module contains Queue and Pipe classes that allow >> inter-process communication, but there's no way to directly read from these >> objects without blocking the event loop. >> >> I propose adding a Pipe class to asyncio, that is process-safe and can be >> read from without blocking the event loop. This was discussed a bit here: >> https://github.com/python/cpython/pull/20882#issuecomment-683463367 >> >> This could be implemented using the multiprocessing.Pipe >> class. multiprocessing.connection.Connection.fileno() returns the file >> descriptor used by a pipe. We could then use loop.add_reader() to set >> an asyncio.Event when something has been written to the pipe by the other >> process. I did this all manually in a project I was working on. However, >> this required me to learn a considerable amount about asyncio. It would >> have saved me a lot of time if there was an easy documented way to wait for >> input from another process in a non-blocking way. >> >> One compelling use case for this is a server that uses asyncio, which >> receives inputs from clients, then sends these to another process that runs >> a neural network. The server then sends the client a result after the >> neural network finishes. ProcessPoolExecutor does not seem like a good fit >> for this use case, because the process needs to stay alive and be re-used >> for subsequent requests. Starting a new process for each request is >> impractical, because loading the neural network into GPU memory is an >> expensive operation. See here for an example of such a server (however this >> one is mostly written in C++ and does not asyncio): >> https://www.tensorflow.org/tfx/guide/serving >> _______________________________________________ >> Python-ideas mailing list -- python-ideas@python.org >> To unsubscribe send an email to python-ideas-le...@python.org >> https://mail.python.org/mailman3/lists/python-ideas.python.org/ >> Message archived at >> https://mail.python.org/archives/list/python-ideas@python.org/message/2YTRR3QUFJ66MOJKVUQXAVPBY4AKB4PX/ >> Code of Conduct: http://python.org/psf/codeofconduct/ >> > > > -- > --Guido van Rossum (python.org/~guido) > *Pronouns: he/him **(why is my pronoun here?)* > <http://feministing.com/2015/02/03/how-using-they-as-a-singular-pronoun-can-change-the-world/> >
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