I have been using flask, and some of my route handlers start computations that can take several minutes to complete. Using flask's development server, I can use app.run(threaded=True) and my server will continue to respond to other requests while it's off performing these multi-minute computation.
Now I've starting using Flask-SocketIO and I'm not sure how to do the equivalent thing. I understand that I can explicitly spawn a separate thread in python any time it starts one of these computations. Is that the only way to do it? Or is there something equivalent to threaded=True for flask-socketio. (Or, more likely, am I just utterly confused.)
Thanks for any help.
With threaded=True requests are each handled in a new thread. How many threads your server can handle concurrently depends entirely on your OS and what limits it sets on the number of threads per process. The implementation uses the SocketServer.
Flask-SocketIO gives Flask applications access to low latency bi-directional communications between the clients and the server.
Flask, being a minimalist web framework, does not have WebSocket support built-in. The old Flask-Sockets extension, which has not been maintained in the last few years, provided support for this protocol.
The idea of the threaded mode in Flask/Werkzeug is to enable the development server to handle multiple requests concurrently. In the default mode, the server can handle one request at a time, if a client sends a request while the server is already processing a previous request, then the second request has to wait until that first request is complete. In threaded mode, Werkzeug spawns a thread for each incoming request, so multiple requests are handled concurrently. You obviously are taking advantage of the threaded mode to have requests that take very long to return, while keeping the server responsive to other requests.
Note that this approach is hard to scale properly when you move out of the development web server and into a production web server. For a worker based server you have to pick a fixed number of workers, and that gives you the maximum number of concurrent requests you can have.
The alternative approach is to use a coroutine based server, such as gevent, which is fully supported by Flask. For gevent there is a single worker process, but in it there are multiple lightweight (or "green") threads, that cooperatively allow each other to run. The key to make things work under this model is to ensure that these green threads do not abuse the CPU time they get, because only one can run at a time. When this is done right, the server can scale much better than with the multiple worker approach I described above, and you can easily have hundreds/thousands of clients handled in this fashion.
So now you want to use Flask-SocketIO, and this extension requires the use of gevent. In case the reason for this requirement isn't clear, unlike HTTP requests, SocketIO uses the WebSocket protocol, which requires long-lived connections. Using gevent and green threads makes it possible to have a potentially large number of constantly connected clients, something that would be impossible to do with multiple workers.
The problem is your long calculation, which is not friendly to the gevent type of server. To make it work, you need to ensure your calculation function yields often, so that other threads get a chance to run and don't starve. For example, if your calculation function has a loop in in, you can do something like this:
def my_long_calculation():
while some_condition:
# do some work here
# let other threads run
gevent.sleep()
The sleep()
function will basically halt your thread and switch to any other threads that need CPU. Eventually control will be given back to your function, and at that point it'll move on to the next iteration. You need to make sure the sleep calls are not too spaced out (as that will make the rest of the application unresponsive) or not too closer (as that may slow down your calculation).
So to answer your question, as long as you yield properly in your long calculation, you do not need to do anything special to handle concurrent requests, as this is the normal operating mode of gevent.
If for any reason the yield approach is not possible, then you may need to think about offloading the CPU intensive tasks to another process. Maybe use Celery to have these done as a job queue.
Sorry for the long winded answer. Hope this helps!
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