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 parallel_fetch(url1, url2): resp1, resp2 = await multi([http_client.fetch(url1), http_client.fetch(url2)]) async def parallel_fetch_many(urls): responses = await multi ([http_client.fetch(url) for url in urls]) # responses

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 resp1, resp2 = await multi([http_client.fetch(url1), http_client.fetch(url2)]) async def parallel_fetch_many(urls): responses = await multi ([http_client.fetch(url)

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 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 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 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 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 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 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

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 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 parallel_fetch(url1, url2): resp1, resp2 = await multi([http_client.fetch(url1), http_client.fetch(url2)]) async def parallel_fetch_many(urls): responses = await multi ([http_client.fetch(url) for url in urls]) # responses

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 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 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 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 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 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 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 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 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