There is the C# 5 CTP, which performs a continuation-passing-style transformation over methods declared with the new async keyword, and continuation-passing based calls when using the await keyword. This is not actually a new CLR feature but rather a set of directives for the compiler to perform the CPS transformation over your code and a … Read more
You could always just use Data.Sequence. Alternatively, a well-known implementation of a purely functional queue is to use two lists. One for enqueue and another for dequeue. Enqueue would simply cons with the enqueue list. Dequeue takes the head of the dequeue list. When the dequeue list is shorter than the enqueue list, refill it … Read more
Celery does not support task priority. (v3.0) http://docs.celeryproject.org/en/master/faq.html#does-celery-support-task-priorities You may solve this problem by routing tasks. http://docs.celeryproject.org/en/latest/userguide/routing.html Prepare default and priority_high Queue. from kombu import Queue CELERY_DEFAULT_QUEUE = ‘default’ CELERY_QUEUES = ( Queue(‘default’), Queue(‘priority_high’), ) Run two daemon. user@x:/$ celery worker -Q priority_high user@y:/$ celery worker -Q default,priority_high And route task. your_task.apply_async(args=[‘…’], queue=”priority_high”)
In Python 3.x, you can use concurrent.futures.ThreadPoolExecutor to do this, rather than rolling your own. Python 2.x actually has a built-in thread pool you can use as well, its just not well documented: from multiprocessing.pool import ThreadPool def foo(word, number): print (word * number) r[(word,number)] = number return number words = [‘hello’, ‘world’, ‘test’, ‘word’, … Read more
Method 2 is wrong because you are doing an operation in two steps when it could be done in one. In method 2, you check if the queue is empty, and then later (very soon, but still later), try to get the item. What if you have two threads pulling items from the queue? The … Read more
In brief: A list is an ordered list of objects, where the same object may well appear more than once. For example: [1, 7, 1, 3, 1, 1, 1, 5]. It makes sense to talk about the “third element” in a list. You can add an element anywhere in the list, change an element anywhere … Read more
What you want is a List<T> where you always call RemoveAt(0) when you want to get the item from the Queue. Everything else is the same, really (calling Add would add an item to the end of the Queue).
I have implemented a reverse proxy through an Async Http Handler for benchmarking purposes (as a part of my Phd. Thesis) and run into the very same problems as you. In order to scale it is mandatory to have processModel set to false and fine tune the thread pools. I have found that, contrary to … Read more
Try this: import Queue import time def dump_queue(queue): “”” Empties all pending items in a queue and returns them in a list. “”” result = [] for i in iter(queue.get, ‘STOP’): result.append(i) time.sleep(.1) return result import multiprocessing q = multiprocessing.Queue() for i in range(100): q.put([range(200) for j in range(100)]) q.put(‘STOP’) l=dump_queue(q) print len(l) Multiprocessing queues … Read more