I have set up a Python (2.7) Flask application which uses Flask-SocketIO. I'm running the app somewhat like this
eventlet.monkey_patch(socket=True, select=True, subprocess=True)
socketio = SocketIO(app, cors_allowed_origins='*',
async_mode='eventlet')
socketio.run(app, host='0.0.0.0', debug=False,
port=5100)
Now, the app runs perfectly fine. I however for 1 API call, need to leverage Python Microprocessing module.
Here is that API method
jobs = []
queue = Queue()
for idx, val in enumerate(myArray):
process = pool(target=self.getEachNode,
args=(val['ip'], self.subscriberId, queue))
jobs.append(process)
try:
print('waiting for someone to inqueue')
result = queue.get(timeout=120)
print('finally someone inqueued..................')
print(result)
except Exception as ex:
print('Exception occurred while waiting for queue')
# terminate all jobs
for j in jobs:
j.terminate()
for j in jobs:
j.join()
myArray will have like 10 items. So this request will run 10 times.
Whenever that happens, The python console tells me that a new app has been started (as the following code is run again)
if __name__ == "__main__":
app.wsgi_app = DispatcherMiddleware(
app.wsgi_app, {getenv("API_BASEURL", "/api"): app})
socketio.run(app, host='0.0.0.0', debug=False,
port=5100, use_reloader=False)
print('python server running on port 5100')
Now what actually happens is, when these processes are running, the main app hangs. I cannot access any other API method. It basically blocks. This also results in socket disconnection because server gets blocked from my understanding.
All I want is for those 10 tasks to execute asynchronously. Should I use Pool for this?
Pool has a method of apply_async , will that help?
Also, I just want 1 response, I dont need all of them to complete (no need to Promise.all).
I cannot use any of Python 3 feature by the way.
I ended up using Celery / Message Queue which allows us to manage async tasks in Flask easily.
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