asynchronous code in Tornado. Coroutines use the Python await or yield keyword to suspend and resume execution instead of a chain of callbacks (cooperative lightweight threads as seen in frameworks like gevent decorate this method with gen.coroutine to make it asynchronous. If this method returns an Awaitable execution will not proceed until the Awaitable is done. New in version 3.1: Asynchronous support. RequestHandler synchronous interface, while Tornado’s concurrency model is based on single-threaded asynchronous execution. This means that running a WSGI app with Tornado’s WSGIContainer is less scalable than running the

asynchronous code in Tornado. Coroutines use the Python await or yield keyword to suspend and resume execution instead of a chain of callbacks (cooperative lightweight threads as seen in frameworks like gevent decorate this method with gen.coroutine to make it asynchronous. If this method returns an Awaitable execution will not proceed until the Awaitable is done. New in version 3.1: Asynchronous support. RequestHandler synchronous interface, while Tornado’s concurrency model is based on single-threaded asynchronous execution. This means that running a WSGI app with Tornado’s WSGIContainer is less scalable than running the

write asynchronous code in Tornado. Coroutines use the Python yield keyword to suspend and resume execution instead of a chain of callbacks (cooperative lightweight threads as seen in frameworks like gevent asynchronous (the asynchronous decorator cannot be used on prepare). If this method returns a Future execution will not proceed until the Future is done. New in version 3.1: Asynchronous support. RequestHandler synchronous interface, while Tornado’s concurrency model is based on single-threaded asynchronous execution. This means that running a WSGI app with Tornado’s WSGIContainer is less scalable than running the

write asynchronous code in Tornado. Coroutines use the Python yield keyword to suspend and resume execution instead of a chain of callbacks (cooperative lightweight threads as seen in frameworks like gevent chronous (the asynchronous decorator cannot be used on prepare). If this method returns a Future execution will not proceed until the Future is done. New in version 3.1: Asynchronous support. RequestHandler synchronous interface, while Tornado’s concurrency model is based on single- threaded asynchronous execution. This means that running a WSGI app with Tornado’s WSGIContainer is less scalable than running the

asynchronous code in Tornado. Coroutines use the Python await or yield keyword to suspend and resume execution instead of a chain of callbacks (cooperative lightweight threads as seen in frameworks like gevent chronous (the asynchronous decorator cannot be used on prepare). If this method returns a Future execution will not proceed until the Future is done. New in version 3.1: Asynchronous support. RequestHandler synchronous interface, while Tornado’s concurrency model is based on single- threaded asynchronous execution. This means that running a WSGI app with Tornado’s WSGIContainer is less scalable than running the

asynchronous code in Tornado. Coroutines use the Python await or yield keyword to suspend and resume execution instead of a chain of callbacks (cooperative lightweight threads as seen in frameworks like gevent asynchronous (the asynchronous decorator cannot be used on prepare). If this method returns a Future execution will not proceed until the Future is done. New in version 3.1: Asynchronous support. RequestHandler synchronous interface, while Tornado’s concurrency model is based on single-threaded asynchronous execution. This means that running a WSGI app with Tornado’s WSGIContainer is less scalable than running the

asynchronous code in Tornado. Coroutines use the Python await or yield keyword to suspend and resume execution instead of a chain of callbacks (cooperative lightweight threads as seen in frameworks like gevent decorate this method with gen.coroutine to make it asyn- chronous. If this method returns an Awaitable execution will not proceed until the Awaitable is done. New in version 3.1: Asynchronous support. RequestHandler synchronous interface, while Tornado’s concurrency model is based on single- threaded asynchronous execution. This means that running a WSGI app with Tornado’s WSGIContainer is less scalable than running the

asynchronous code in Tornado. Coroutines use the Python await or yield keyword to suspend and resume execution instead of a chain of callbacks (cooperative lightweight threads as seen in frameworks like gevent decorate this method with gen.coroutine to make it asyn- chronous. If this method returns an Awaitable execution will not proceed until the Awaitable is done. New in version 3.1: Asynchronous support. RequestHandler synchronous interface, while Tornado’s concurrency model is based on single- threaded asynchronous execution. This means that running a WSGI app with Tornado’s WSGIContainer is less scalable than running the

write asynchronous code in Tornado. Coroutines use the Python await keyword to suspend and resume execution instead of a chain of callbacks (cooperative lightweight threads as seen in frameworks like gevent decorate this method with gen.coroutine to make it asynchronous. If this method returns an Awaitable execution will not proceed until the Awaitable is done. New in version 3.1: Asynchronous support. RequestHandler synchronous interface, while Tornado’s concurrency model is based on single-threaded asynchronous execution. Many of Tornado’s distinguishing features are not available in WSGI mode, includ- ing efficient

write asynchronous code in Tornado. Coroutines use the Python await keyword to suspend and resume execution instead of a chain of callbacks (cooperative lightweight threads as seen in frameworks like gevent decorate this method with gen.coroutine to make it asynchronous. If this method returns an Awaitable execution will not proceed until the Awaitable is done. New in version 3.1: Asynchronous support. 6.2. Web synchronous interface, while Tornado’s concurrency model is based on single- threaded asynchronous execution. This means that running a WSGI app with Tornado’s WSGIContainer is less scalable than running the