may be useful: concurrent.futures [https://pypi.python.org/pypi/futures] is the recommended thread pool for use with Tornado and enables the use of ThreadedResolver. It is needed only on Python 2; Python returns Futures that are compatible with coroutines: thread_pool = ThreadPoolExecutor(4) @gen.coroutine def call_blocking(): yield thread_pool.submit(blocking_func, args) Parallelism The coroutine decorator standard library since Python 3.2, installable with pip install futures in older versions). The thread pool size can be configured with: Resolver.configure('tornado.netutil.ThreadedResolver',

install, the following optional packages may be useful: • concurrent.futures is the recommended thread pool for use with Tornado and enables the use of ThreadedResolver. It is needed only on Python 2; Python returns Futures that are compatible with coroutines: thread_pool = ThreadPoolExecutor(4) @gen.coroutine def call_blocking(): yield thread_pool.submit(blocking_func, args) Parallelism The coroutine decorator The thread pool size can be configured with: Resolver.configure('tornado.netutil.ThreadedResolver', num_threads=10) Changed in version 3.1: All ThreadedResolvers share a single thread pool, whose size

The thread pool size can be configured with: Resolver.configure('tornado.netutil.ThreadedResolver', num_threads=10) Changed in version 3.1: All ThreadedResolvers share a single thread pool, whose size application will run on the event loop thread in Tornado 6.3; this will change to use an internal thread pool by default in Tornado 7.0. Warning: By default, the WSGI application is executed on the event loop’s application on the event loop thread is deprecated and will change in Tornado 7.0 to use a thread pool by default. environ(request: HTTPServerRequest) → Dict[str, Any] Converts a tornado.httputil.HTTPServerRequest

The thread pool size can be configured with: Resolver.configure('tornado.netutil.ThreadedResolver', num_threads=10) Changed in version 3.1: All ThreadedResolvers share a single thread pool, whose size application will run on the event loop thread in Tornado 6.3; this will change to use an internal thread pool by default in Tornado 7.0. Warning: By default, the WSGI application is executed on the event loop’s application on the event loop thread is deprecated and will change in Tornado 7.0 to use a thread pool by default. environ(request: HTTPServerRequest) → Dict[str, Any] Converts a tornado.httputil.HTTPServerRequest

The thread pool size can be configured with: Resolver.configure('tornado.netutil.ThreadedResolver', num_threads=10) Changed in version 3.1: All ThreadedResolvers share a single thread pool, whose size application will run on the event loop thread in Tornado 6.3; this will change to use an internal thread pool by default in Tornado 7.0. Warning: By default, the WSGI application is executed on the event loop’s application on the event loop thread is deprecated and will change in Tornado 7.0 to use a thread pool by default. environ(request: HTTPServerRequest) → Dict[str, Any] Converts a tornado.httputil.HTTPServerRequest

The thread pool size can be configured with: Resolver.configure('tornado.netutil.ThreadedResolver', num_threads=10) Changed in version 3.1: All ThreadedResolvers share a single thread pool, whose size application will run on the event loop thread in Tornado 6.3; this will change to use an internal thread pool by default in Tornado 7.0. Warning: By default, the WSGI application is executed on the event loop’s application on the event loop thread is deprecated and will change in Tornado 7.0 to use a thread pool by default. environ(request: HTTPServerRequest) → Dict[str, Any] Converts a tornado.httputil.HTTPServerRequest

The thread pool size can be configured with: Resolver.configure('tornado.netutil.ThreadedResolver', num_threads=10) Changed in version 3.1: All ThreadedResolvers share a single thread pool, whose size application will run on the event loop thread in Tornado 6.3; this will change to use an internal thread pool by default in Tornado 7.0. Warning: By default, the WSGI application is executed on the event loop’s application on the event loop thread is deprecated and will change in Tornado 7.0 to use a thread pool by default. environ(request: HTTPServerRequest) → Dict[str, Any] Converts a tornado.httputil.HTTPServerRequest

The thread pool size can be configured with: Resolver.configure('tornado.netutil.ThreadedResolver', num_threads=10) Changed in version 3.1: All ThreadedResolvers share a single thread pool, whose size different attribute name, pass a keyword argument to the decorator: @run_on_executor(executor='_thread_pool') def foo(self): pass This decorator should not be confused with the similarly-named IOLoop.run_in_executor stack_context-aware library like tornado. ioloop or tornado.iostream (for example, if you’re writing a thread pool), use stack_context. wrap() before any asynchronous operations to capture the stack context from where

standard library since Python 3.2, installable with pip install futures in older versions). The thread pool size can be configured with: Resolver.configure('tornado.netutil.ThreadedResolver', num_threads=10) Changed in version 3.1: All ThreadedResolvers share a single thread pool, whose size is set by the first one to be created. Deprecated since version 5.0: The default Resolver now different attribute name, pass a keyword argument to the decorator: @run_on_executor(executor='_thread_pool') def foo(self): pass This decorator should not be confused with the similarly-named IOLoop.run_in_executor

standard library since Python 3.2, installable with pip install futures in older versions). The thread pool size can be configured with: Resolver.configure('tornado.netutil.ThreadedResolver', num_threads=10) Changed in version 3.1: All ThreadedResolvers share a single thread pool, whose size is set by the first one to be created. Deprecated since version 5.0: The default Resolver now application will run on the event loop thread in Tornado 6.3; this will change to use an internal thread pool by default in Tornado 7.0. Warning By default, the WSGI application is executed on the event loop’s