Running an async background task in Tornado

I have a time-consuming task in post request, maybe more than 30 minutes need, but client required return a result immediately.

First, I used IOLoop.current().spawn_callback. It works! but! If the first request task is running, second request task blocked! Because all tasks are in main event loop when use spawn_callback, so one task is synchronous execution, other tasks blocked.

Last, I use tornado.concurrent. Example:

import datetime
import time

from tornado.ioloop import IOLoop
import tornado.web
from tornado import concurrent

executor = concurrent.futures.ThreadPoolExecutor(8)


class Handler(tornado.web.RequestHandler):

    def get(self):
        def task(arg):
            for i in range(10):
                time.sleep(1)
                print(arg, i)

        executor.submit(task, datetime.datetime.now())
        self.write('request accepted')


def make_app():
    return tornado.web.Application([
        (r"/", Handler),
    ])


if __name__ == "__main__":
    app = make_app()
    app.listen(8000, '0.0.0.0')
    IOLoop.current().start()

and visit http://127.0.0.1:8000, you can see it's run ok:

2017-01-17 22:42:10.983632 0
2017-01-17 22:42:10.983632 1
2017-01-17 22:42:10.983632 2
2017-01-17 22:42:13.710145 0
2017-01-17 22:42:10.983632 3
2017-01-17 22:42:13.710145 1
2017-01-17 22:42:10.983632 4
2017-01-17 22:42:13.710145 2
2017-01-17 22:42:10.983632 5
2017-01-17 22:42:16.694966 0
2017-01-17 22:42:13.710145 3
2017-01-17 22:42:10.983632 6
2017-01-17 22:42:16.694966 1
2017-01-17 22:42:13.710145 4
2017-01-17 22:42:10.983632 7
2017-01-17 22:42:16.694966 2
2017-01-17 22:42:13.710145 5
2017-01-17 22:42:10.983632 8
2017-01-17 22:42:16.694966 3
2017-01-17 22:42:13.710145 6
2017-01-17 22:42:19.790646 0
2017-01-17 22:42:10.983632 9
2017-01-17 22:42:16.694966 4
2017-01-17 22:42:13.710145 7
2017-01-17 22:42:19.790646 1
2017-01-17 22:42:16.694966 5
2017-01-17 22:42:13.710145 8
2017-01-17 22:42:19.790646 2
2017-01-17 22:42:16.694966 6
2017-01-17 22:42:13.710145 9
2017-01-17 22:42:19.790646 3
2017-01-17 22:42:16.694966 7
2017-01-17 22:42:19.790646 4
2017-01-17 22:42:16.694966 8
2017-01-17 22:42:19.790646 5
2017-01-17 22:42:16.694966 9
2017-01-17 22:42:19.790646 6
2017-01-17 22:42:19.790646 7
2017-01-17 22:42:19.790646 8
2017-01-17 22:42:19.790646 9

Want to help everyone!

I recommend using toro. It provides a relatively simple mechanism for setting up a background queue of tasks.

The following code (put in queue.py for example), starts a simple "worker()" that simply waits until there is something in his queue. If you call queue.add(function,async,*args,**kwargs) this adds an item to the queue which will wake up worker() which then kicks off the task.

I added the async parameter so that this can support background tasks wrapped in @gen.coroutine and those without.

import toro,tornado.gen
queue = toro.Queue()
@tornado.gen.coroutine
def add(function,async,*args,**kwargs):
   item = dict(function=function,async=async,args=args,kwargs=kwargs)
   yield queue.put(item)

@tornado.gen.coroutine
def worker():
   while True:
      print("worker() sleeping until I get next item")
      item = yield queue.get()
      print("worker() waking up to process: %s" % item)
      try:
         if item['async']:
            yield item['function'](*item['args'],**item['kwargs'])
         else:
            item['function'](*item['args'],**item['kwargs'])
      except Exception as e:
         print("worker() failed to run item: %s, received exception:\n%s" % (item,e))

@tornado.gen.coroutine
def start():
   yield worker()

In your main tornado app:

import queue
queue.start()

And now you can schedule a back ground task quite simply:

def my_func(arg1,somekwarg=None):
   print("in my_func() with %s %s" % (arg1,somekwarg))

queue.add(my_func,False,somearg,somekwarg=someval)

Update: Since Tornado 4.0 (July 2014), the below functionality is available in the IOLoop.spawn_callback method.

Unfortunately it's kind of tricky. You need to both detach the background task from the current request (so that a failure in the background task doesn't result in a random exception thrown into the request) and ensure that something is listening to the background task's result (to log its errors if nothing else). This means something like this:

from tornado.ioloop import IOLoop
from tornado.stack_context import run_in_stack_context, NullContext
IOLoop.current().add_future(run_in_stack_context(NullContext(), self._background_task),
                            lambda f: f.result())

Something like this will probably be added to tornado itself in the future.