Tornado, often thought of as a web development framework and toolset is built on top of a protocol-agnostic IOLoop, presenting an alternative to Twisted as a foundation for asynchronous application development in Python. This talk covers the Tornado IOLoop, its features and the process of writing drivers and applications using it. Video available at https://www.youtube.com/watch?v=3BYN3ouwkRA

1. More than just a pretty web framework:
the Tornado IOLoop
Gavin M. Roy

2. About myYearbook
According to comScore,
myYearbook is one of the 25 most-
trafficked sites in the United States
as measured by page views, by
minutes, and by minutes per visitor
per month.
http://www.myyearbook.com/careers
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3. Tornado @
myYearbook
• At myYearbook, we used Tornado in high-
request-velocity applications.
• Web apps
• Finite State Machine Game Server
• Take what you need? We do.
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4. Async Network
Programming
• Core revolves around an I/O loop
• Let the Operating System indicate when
to read, when to write and when there
are errors on sockets.
• select, poll, epoll (Linux), kqueue (BSD)
• Callback-Passing Style
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5. Async Network
Programming
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6. Callback Passing Style
def start(foo):
# Do stuff with foo and when done call the next function
stuff(callback=next_step, data=foo);
def next_step(bar):
# Call more_stuff to parse bar
more_stuff(callback=last_step, data=bar);
def last_step(baz):
# Send the response
send_response(baz)
# Let our handler know we are done
finish()
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7. tornado.IOLoop
• Core of Tornado’s network stack
• Fast and easy to use
• Single instance per process Works on windows but
not supported.
C-Based epoll, not required
• Cross-platform
• Easy to read source: http://goo.gl/VFeAF
• Used for client libraries & server
applications
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8. tornado.IOStream
• Convenient utility class for dealing with the
IOLoop
• Does most of the work for you
• This too is for use by clients and server
applications
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9. IOStream: How to read
• read_until_regex
(regex, callback)
• read_until
(delimiter, callback)
• read_bytes
(num_bytes, callback,
streaming_callback=None)
• read_until_close
(callback,
streaming_callback=None)
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10. IOStream: What’s Going On?
reading(), writing(), closed()
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11. Serious
Business Uses
SSL
And that’s why SSLIOStream Exists.
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12. tornado.netutil.TCPServer
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13. Hello Async World
from tornado import ioloop
from tornado import netutil
class EchoServer(netutil.TCPServer):
def handle_stream(self, stream, address):
self._stream = stream
self._read_line()
def _read_line(self):
self._stream.read_until('n', self._handle_read)
def _handle_read(self, data_in):
self._stream.write('You sent: %s' % data_in)
self._read_line()
if __name__ == '__main__':
server = EchoServer()
server.listen(2007)
ioloop.IOLoop.instance().start() Source: http://goo.gl/eB7z4
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14. What just happened?
tornado.stack_context.StackContext
“Slight Magic”
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15. Diving Deeper
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16. tornado.IOLoop
• IOLoop.instance()
• ioloop.add_handler
(fd, handler, events)
• ioloop.update_handler
(fd, handler, events)
• ioloop.remove_handler(fd)
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17. Events?
READ, WRITE, ERROR
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18. “Example”
import socket
from tornado import ioloop
def on_events(fd, events, error=None):
if events & ioloop.IOLoop.READ:
print 'Socket read: %r' % fd.recv(1024)
if events & ioloop.IOLoop.ERROR:
print 'Error received: %r' % error
if events & ioloop.IOLoop.WRITE:
pass
_ioloop = ioloop.IOLoop.instance()
fd = socket.socket() # Other stuff needs to be done here
events_desired = ioloop.IOLoop.READ | ioloop.IOLoop.ERROR
_ioloop.add_handler(fd, on_events, events_desired)
_ioloop.start()
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19. Timers add_timeout returns a
reference
deadline can be unix
timestamp or a
datetime.timedelta
• add_timeout
(deadline, callback)
• remove_timeout
(timeout)
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20. add_callback(callback)
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21. “Pythonic”
Simplification
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22. tornado.gen
for coding not in Callback Passing Style:
@gen.engine
def foo():
http_client = AsyncHTTPClient()
response1, response2 = yield [gen.Task(http_client.fetch,
url1),
gen.Task(http_client.fetch,
url2)]
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23. tornado.platform.twisted
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24. Last Thoughts
• Single threaded, use processes
• Watch out for resource contention
• Benchmark your application
• Fork work to remote workers
• multiprocessing.reduction
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25. multiprocessing.reduction:
# Main process
from multiprocessing.reduction import reduce_handle
h = reduce_handle(client_socket.fileno())
pipe_to_worker.send(h) #instance of multiprocessing.Pipe
# Worker process
from multiprocessing.reduction import rebuild_handle
h = pipe.recv()
fd = rebuild_handle(h)
client_socket = socket.fromfd(fd, socket.AF_INET,
socket.SOCK_STREAM)
client_socket.send("hello from the worker processrn")
Questions?
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