Class ThreadedResolver

tornado/netutil.py:501–537

Multithreaded non-blocking `Resolver` implementation. The thread pool size can be configured with:: Resolver.configure('tornado.netutil.ThreadedResolver', num_threads=10) .. versionchanged:: 3.1 All ``ThreadedResolvers`` share a single thread pool

class ThreadedResolver(ExecutorResolver):
    """Multithreaded non-blocking `Resolver` implementation.

    The thread pool size can be configured with::

        Resolver.configure('tornado.netutil.ThreadedResolver',
                           num_threads=10)

    .. versionchanged:: 3.1
       All ``ThreadedResolvers`` share a single thread pool, whose
       size is set by the first one to be created.

    .. deprecated:: 5.0
       The default `Resolver` now uses `.IOLoop.run_in_executor`; use that instead
       of this class.
    """

    _threadpool = None  # type: ignore
    _threadpool_pid = None  # type: int

    def initialize(self, num_threads: int = 10) -> None:  # type: ignore
        threadpool = ThreadedResolver._create_threadpool(num_threads)
        super().initialize(executor=threadpool, close_executor=False)

    @classmethod
    def _create_threadpool(
        cls, num_threads: int
    ) -> concurrent.futures.ThreadPoolExecutor:
        pid = os.getpid()
        if cls._threadpool_pid != pid:
            # Threads cannot survive after a fork, so if our pid isn't what it
            # was when we created the pool then delete it.
            cls._threadpool = None
        if cls._threadpool is None:
            cls._threadpool = concurrent.futures.ThreadPoolExecutor(num_threads)
            cls._threadpool_pid = pid
        return cls._threadpool


class OverrideResolver(Resolver):