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- from __future__ import absolute_import
- import sys
- from concurrent.futures import ThreadPoolExecutor
- from tornado.gen import convert_yielded
- from apscheduler.executors.base import BaseExecutor, run_job
- try:
- from apscheduler.executors.base_py3 import run_coroutine_job
- from apscheduler.util import iscoroutinefunction_partial
- except ImportError:
- def iscoroutinefunction_partial(func):
- return False
- class TornadoExecutor(BaseExecutor):
- """
- Runs jobs either in a thread pool or directly on the I/O loop.
- If the job function is a native coroutine function, it is scheduled to be run directly in the
- I/O loop as soon as possible. All other functions are run in a thread pool.
- Plugin alias: ``tornado``
- :param int max_workers: maximum number of worker threads in the thread pool
- """
- def __init__(self, max_workers=10):
- super(TornadoExecutor, self).__init__()
- self.executor = ThreadPoolExecutor(max_workers)
- def start(self, scheduler, alias):
- super(TornadoExecutor, self).start(scheduler, alias)
- self._ioloop = scheduler._ioloop
- def _do_submit_job(self, job, run_times):
- def callback(f):
- try:
- events = f.result()
- except BaseException:
- self._run_job_error(job.id, *sys.exc_info()[1:])
- else:
- self._run_job_success(job.id, events)
- if iscoroutinefunction_partial(job.func):
- f = run_coroutine_job(job, job._jobstore_alias, run_times, self._logger.name)
- else:
- f = self.executor.submit(run_job, job, job._jobstore_alias, run_times,
- self._logger.name)
- f = convert_yielded(f)
- f.add_done_callback(callback)
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