officially supported or recommended for production use. Some features are missing on Windows (including multi-process mode) and scalability is limited (Even though Tornado is built on asyncio, which supports my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that support some shorthand for waiting on multiple objects by yielding a list or dict. Use tornado.gen.multi to do this in native coroutines. can support integration with other packages including Twisted via

compatible with Tornado. Applications that use Tornado on Windows with Python 3.8 must call asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy()) at the beginning of their main file/function my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that support some shorthand for waiting on multiple objects by yielding a list or dict. Use tornado.gen.multi to do this in native coroutines. can support integration with other packages including Twisted via

AsyncHTTPClient() my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that the support some shorthand for waiting on multiple objects by yielding a list or dict. Use tornado.gen.multi to do this in native coroutines. • Decorated coroutines can support integration with other packages blocking_func, args) Parallelism The multi function accepts lists and dicts whose values are Futures, and waits for all of those Futures in parallel: from tornado.gen import multi async def parallel_fetch(url1

officially supported or recommended for pro- duction use. Some features are missing on Windows (including multi-process mode) and scalability is limited (Even though Tornado is built on asyncio, which supports AsyncHTTPClient() my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that the support some shorthand for waiting on multiple objects by yielding a list or dict. Use tornado.gen. multi to do this in native coroutines. – can support integration with other packages including Twisted

compatible with Tornado. Applications that use Tornado on Windows with Python 3.8 must call asyncio.set_event_loop_policy(asyncio. WindowsSelectorEventLoopPolicy()) at the beginning of their main file/function AsyncHTTPClient() my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that the support some shorthand for waiting on multiple objects by yielding a list or dict. Use tornado.gen. multi to do this in native coroutines. – can support integration with other packages including Twisted

Future() fetch_future = http_client.fetch(url) fetch_future.add_done_callback( lambda f: my_future.set_result(f.result())) return my_future The raw Future version is more complex, but Futures are nonetheless you can yield a list of Futures, while in a native coroutine you must wrap the list in tornado.gen.multi. This also eliminates the integration with concurrent.futures. You can use tornado.gen.convert_yielded that yields Queue.get pauses until there is an item in the queue. If the queue has a maximum size set, a coroutine that yields Queue.put pauses until there is room for another item. A Queue maintains

fetch_future = http_client.fetch(url) fetch_future.add_done_callback( lambda f: my_future.set_result(f.result())) return my_future The raw Future version is more complex, but Futures are nonetheless you can yield a list of Futures, while in a native coroutine you must wrap the list in tornado.gen.multi. This also eliminates the integration with concurrent.futures [https://docs.python.org/3.5/library/concurrent that yields Queue.get pauses until there is an item in the queue. If the queue has a maximum size set, a coroutine that yields Queue.put pauses until there is room for another item. A Queue maintains

my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that support some shorthand for waiting on multiple objects by yielding a list or dict. Use tornado.gen.multi to do this in native coroutines. Decorated coroutines can support integration with other packages blocking_func, args) Parallelism The multi function accepts lists and dicts whose values are Futures, and waits for all of those Futures in parallel: from tornado.gen import multi async def parallel_fetch(url1

officially supported or recommended for pro- duction use. Some features are missing on Windows (including multi-process mode) and scalability is limited (Even though Tornado is built on asyncio, which supports AsyncHTTPClient() my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that the support some shorthand for waiting on multiple objects by yielding a list or dict. Use tornado.gen.multi to do this in native coroutines. – can support integration with other packages including Twisted

officially supported or recommended for pro- duction use. Some features are missing on Windows (including multi-process mode) and scalability is limited (Even though Tornado is built on asyncio, which supports AsyncHTTPClient() my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that the support some shorthand for waiting on multiple objects by yielding a list or dict. Use tornado.gen.multi to do this in native coroutines. – can support integration with other packages including Twisted