Running a Tornado Server within a Jupyter Notebook

Taking the standard Tornado demonstration and pushing the IOLoop into a background thread allows querying of the server within a single script. This is useful when the Tornado server is an interactive object (see Dask or similar).

import asyncio
import requests
import tornado.ioloop
import tornado.web

from concurrent.futures import ThreadPoolExecutor

class MainHandler(tornado.web.RequestHandler):
    def get(self):
        self.write("Hello, world")

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

pool = ThreadPoolExecutor(max_workers=2)
loop = tornado.ioloop.IOLoop()

app = make_app()
app.listen(8888)
fut = pool.submit(loop.start)

print(requests.get("https://localhost:8888"))

The above works just fine in a standard python script (though it is missing safe shutdown). Jupyter notebook are optimal environment for these interactive Tornado server environments. However, when it comes to Jupyter this idea breaks down as there is already a active running loop:

>>> import asyncio
>>> asyncio.get_event_loop()
<_UnixSelectorEventLoop running=True closed=False debug=False>

This is seen when running the above script in a Jupyter notebook, both the server and the request client are trying to open a connection in the same thread and the code hangs. Building a new Asyncio loop and/or Tornado IOLoop does not seem to help and I suspect I am missing something in Jupyter itself.

The question: Is it possible to have a live Tornado server running in the background within a Jupyter notebook so that standard python requests or similar can connect to it from the primary thread? I would prefer to avoid Asyncio in the code presented to users if possible due to its relatively complexity for novice users.

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