Python queue code#
Python queue download#

Threads will take turns dequeuing URLs to download them. The loop below willĬontinue to add items until the feed is exhausted, and the worker Should pick it up and start downloading it. As soonĪs the first URL is added to the queue, one of the worker threads The next step is to retrieve the feed contents (using Mark Pilgrim’sįeedparser module) and enqueue the URLs of the enclosures. Safe to start the threads before there is anything in the queue. Url = q.get() until the queue has something to return, so it is Notice that downloadEnclosures() will block on the statement Once the threads’ target function is defined, we can start the worker Sleeping a variable amount of time, depending on the thread id. In this example, we simulate a download delay by Its just like a real-life queue, where the first in line. To actuallyĭownload the enclosure, you might use urllib or A Queue is a data structure where the first element to be inserted is also the first element popped. Illustration purposes this only simulates the download.

Will run in the worker thread, processing the downloads. Next, we need to define the function downloadEnclosures() that

Python queue code#

For ourĮxample we hard code the number of threads to use and the list of URLs Normally these wouldĬome from user inputs (preferences, a database, whatever). join () print '*** Done'įirst, we establish some operating parameters. print '*** Main thread waiting' enclosure_queue. put ( enclosure ) # Now wait for the queue to be empty, indicating that we have # processed all of the downloads. get ( 'enclosures', ): print 'Queuing:', enclosure enclosure_queue. Queue Data Structure and Implementation in Python In a queue, the item that enters first exists first, which means that it is a First In First Out (FIFO) data. parse ( url, agent = 'fetch_podcasts.py' ) for entry in response : for enclosure in entry. for url in feed_urls : response = feedparser. start () # Download the feed(s) and put the enclosure URLs into # the queue. task_done () # Set up some threads to fetch the enclosures for i in range ( num_fetch_threads ): worker = Thread ( target = downloadEnclosures, args = ( i, enclosure_queue ,)) worker.

get () print ' %s : Downloading:' % i, url # instead of really downloading the URL, # we just pretend and sleep time. ''' while True : print ' %s : Looking for the next enclosure' % i url = q. These daemon threads go into an infinite loop, and only exit when the main thread ends. It processes items in the queue one after another. feed_urls = def downloadEnclosures ( i, q ): '''This is the worker thread function. # System modules from Queue import Queue from threading import Thread import time # Local modules import feedparser # Set up some global variables num_fetch_threads = 2 enclosure_queue = Queue () # A real app wouldn't use hard-coded data.