README.md

python-threading-utils

A set of helper classes and functions that make it easier to work with threads in Python.

• do_threaded_work - Makes it easy to parallelize mapping a given work function across a set of work items (without preserving order).
• ThreadedWorker - Makes it easy to create a thread that will pull work from a syncronized work_queue and write it to a syncronized result_queue.
• start_logging_with_thread_info - Helper to add thread id to all log messages. (may fail in some logging environments)
• stop_logging_with_thread_info - Helper to remove thread id from all log messages. (may fail in some logging environments)

ThreadedWorker Example

import Queue

urls_to_process = ["http://url1.com", "http://url2.com", "http://site1.com", "http://site2.com"]

work_queue = Queue.Queue()
result_queue = Queue.Queue()

def process_url(url):
    # TODO: Do some work with the url
    return url

def main():
    # spawn a pool of threads, and pass them queue instance 
    for i in range(5):
        t = ThreadedWorker(work_queue, result_queue, work_func=process_url)
        t.setDaemon(True)
        t.start()
        
    # populate queue with data   
    for url in urls_to_process:
        work_queue.put(url)
        
    # wait on the queue until everything has been processed     
    work_queue.join()
    
    # print results
    print repr(result_queue)

main()

Dependencies:

• Python threading
• Python Queue

References

• IBM article on python threading