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nsqworker - an async task worker for NSQ

Currently only a threaded worker is supported. it handles NSQ messaging with the official Python/Tornado library and executes a blocking message handler function in an executor thread pool.

The motivation behind this package is to replace Celery/RabbitMQ worker processes which perform long running tasks with NSQ.

Installation

pip install git+https://github.com/bsphere/nsqworker.git

Usage

import nsq
import time
from nsqworker import nsqworker


def process_message(message):
  print "start", message.id
  time.sleep(2)
  print "end", message.id

def handle_exc(message, e):
  traceback.print_exc()
  w.io_loop.add_callback(message.requeue)

w = nsqworker.ThreadWorker(message_handler=process_message,
                           exception_handler=handle_exc, concurrency=5, ...)

w.subscribe_reader()

nsq.run()

The arguments for the ThreadWorker constructor are a synchronous, blocking function that handles messages, concurrency, an optional exception_handler and all other arguments for the official NSQ Python library - pynsq.

  • The worker will explicitly call message.finish() in case the handler function didn't call message.finish() or message.requeue().

  • The worker will periodically call message.touch() every 30s for long running tasks so they won't timeout by nsqd.

  • The exception handler is called with a message and an exception as the arguments in case it was given during the worker's initialization and an exception is raised while processing a message.

  • Multiple readers can be added for handing messages from multiple topics and channels.

  • Any interactions with NSQ from within a thread worker, such as message.requeue(), message.finish() and publishing message must be added as callback to the ioloop

  • An optional timeout=<seconds> can be added to the worker constructor, if it is defined, after the defined timeout the optional exception handler will invoked with an nsqworker.errors.TimeoutError. Due to concurrent.futures.ThreadPoolExecutor limitations it is impossible to cancel the running executor thread and it may continue running even after the timeout exception was raised.

  • An optional --loglevel command line argument can be provided to set the logging level, default is INFO. The same logging level can be used with other loggers by getting it form the worker with numric_level = worker.logger.level

  • TODO - message de-duping.