As with all things I write, what follows stems from the limits of my understanding of the concept. The basics of async in Python and the I/O loopĪllow me to preface by saying that I am absolutely, positively, surely, and securely not an expert in asynchronous programming. Let's talk a little more about input, output, and asynchronicity. We begin our I/O loop with IOLoop.current().start(). You could do without the print line if you so chose. I like some kind of a print statement somewhere that tells me when I'm serving my application, but that's me. Thankfully, Tornado comes with that out of the box in the form of. We must do one more step to have a working application that can listen for requests and return responses. Anything that goes in the position of the first argument will be the attribute's name, and what's assigned to the default keyword argument will be the value of that attribute.Īs an example, if we name the attribute potato instead of port, we can access its value via options.potato.Ĭalling listen on the HTTPServer doesn't start the server yet. When we use the define function, we end up creating attributes on the options object. # _init_.pyįrom tornado.httpserver import HTTPServerįrom tornado.options import define, optionsĭefine('port', default=8888, help='port to listen on') Then we instantiate Tornado's HTTPServer, passing the instance of the Application object as its argument. First, we define a port to listen on with. Because Tornado serves the application with its own HTTP server, we also have to set up how the application is served. While building our app, we have to set up the application instance. Like Flask, Tornado is a mostly DIY framework. ![]() ![]() """Construct and serve the tornado application.""" This will handle the hookups for routing and views, including our database (when we get there) and any extra settings needed to run our Tornado app. From tornado.web, we'll import the Application object. ![]() Like Flask and Pyramid, Tornado has some central configuration that will go in _init_.py. Let's make our inner todo directory and fill it with the first few files we'll need. (tornado-someHash) $ pipenv install tornadoĬreate a setup.py for installing our application: (tornado-someHash) $ touch setup.py # setup.pyįrom setuptools import setup, find_packagesĭescription='A To-Do List built with Tornado',īecause Tornado doesn't require any external configuration, we can dive right into writing the Python code that'll run our application. If you've been following along with this series, what we do first shouldn't come as much of a surprise. Let's continue the pattern we set in the first two articles and start by tackling the setup and config. That special sauce isn't terribly useful in the app we're building in this series, but we'll see where we can use it and how it works in a more general situation. Tornado is, for the most part, as bare-bones as Flask, but with a major difference: Tornado is built specifically to handle asynchronous processes. Now let's look at a somewhat different option: the Tornado framework. ![]() We've built the same app twice and seen the similarities and differences between a complete DIY framework and a framework with a few more batteries included. In the first two articles in this four-part series comparing different Python web frameworks, we've covered the Pyramid and Flask web frameworks.
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