Reputation: 1639
I'm trying to make a simple async call, using gen.coroutine
function of Tornado. This is my current code:
from tornado import gen
import tornado.ioloop
import tornado.web
class MainHandler(tornado.web.RequestHandler):
@gen.coroutine
def get(self):
q = self.get_argument('query')
print q
response = yield self.process(q)
self.write(response)
@gen.coroutine
def process(self, query):
# just a long loop
for i in range(int(query)*100):
for j in range(i):
a = 10*10*10*10*10*10
return {'processed': True}
def make_app():
return tornado.web.Application([
(r"/search", MainHandler),
])
if __name__ == "__main__":
app = make_app()
port = 8888
print "listening on port: ", port
app.listen(port)
tornado.ioloop.IOLoop.current().start()
However, it is not behaving in an async manner. What am I doing wrong in this?
Upvotes: 1
Views: 1554
Reputation: 5117
Your function is blocking the event loop and no other tasks can be handled until either the process()
function completes or it relinquishes control back to the event loop. For situations like this, you can use simply yield None
(it used to be yield gen.moment
) to take a break and let the event loop run other tasks then resume processing. Example:
@gen.coroutine
def process(self, query):
for i in range(int(query)*100):
for j in range(i):
a = 10*10*10*10*10*10
if j % 500 == 0:
yield None # yield the inner loop
if i % 500 == 0:
yield None # yield outer loop
return {'processed': True}
Hopefully this helps you achieve your desired level of concurrency.
http://www.tornadoweb.org/en/stable/gen.html#tornado.gen.moment
Upvotes: 4
Reputation: 24027
Your "process" method does only calculation, so it never provides Tornado's event loop an opportunity to work on other tasks while "process" is running. Tornado can interleave concurrent network operations, however, it cannot run Python code in parallel. To parallelize a function like your "process" method requires multiple Python subprocesses.
Upvotes: 3