queue

问题 I am using simple threading modules to do concurrent jobs. Now I would like to take advantages of concurrent futures modules. Can some put me a example of using a queue with concurrent library? I am getting TypeError: 'Queue' object is not iterable I dont know how to iterate queues code snippet: def run(item): self.__log.info(str(item)) return True <queue filled here> with concurrent.futures.ThreadPoolExecutor(max_workers = 100) as executor: furtureIteams = { executor.submit(run, item): item

问题 I am using simple threading modules to do concurrent jobs. Now I would like to take advantages of concurrent futures modules. Can some put me a example of using a queue with concurrent library? I am getting TypeError: 'Queue' object is not iterable I dont know how to iterate queues code snippet: def run(item): self.__log.info(str(item)) return True <queue filled here> with concurrent.futures.ThreadPoolExecutor(max_workers = 100) as executor: furtureIteams = { executor.submit(run, item): item

问题 If I have a RabbitMQ consumer that retrieves 100 messages in bulk, but then it crashes before it can mark those messages as processed, are those messages lost? I want every message in the queue to be processed at least once. What's the recommended approach to deal with consumers that crash before they've acknowledged messages? Does RabbitMQ put them back on the queue somehow, or what do I need to do to make it happen? 回答1: What's the recommended approach to deal with consumers that crash

问题 I'm new using celery and have a question. I have this simple task: @app.task(name='test_install_queue') def test_install_queue(): return subprocess.call("exit 0",shell=True) and I am calling this task later in a test case like result = tasks.test_default_queue.apply_async(queue="install") The task run successfully in the queue install (because I am seeing it in the celery log, and it completes fine. But I would like to know a programmatically way of finding in which queue was the task test

问题 I'm new using celery and have a question. I have this simple task: @app.task(name='test_install_queue') def test_install_queue(): return subprocess.call("exit 0",shell=True) and I am calling this task later in a test case like result = tasks.test_default_queue.apply_async(queue="install") The task run successfully in the queue install (because I am seeing it in the celery log, and it completes fine. But I would like to know a programmatically way of finding in which queue was the task test

问题 I am given these structure declarations in order to implement a queue collection that uses a circular linked list. typedef struct intnode { int value; struct intnode *next; } intnode_t; typedef struct { intnode_t *rear; // Points to the node at the tail of the // queue's linked list int size; // The # of nodes in the queue's linked list } intqueue_t; intnode_t *intnode_construct(int value, intnode_t *next) { intnode_t *p = malloc(sizeof(intnode_t)); assert (p != NULL); p->value = value; p-

问题 I am designing a Python multiprocessing code to work in a queue that might be updated along the processing. The following code sometimes works, or get stuck, or rises an Empty error. import multiprocessing as mp def worker(working_queue, output_queue): while True: if working_queue.empty() is True: break else: picked = working_queue.get_nowait() if picked % 2 == 0: output_queue.put(picked) else: working_queue.put(picked+1) return if __name__ == '__main__': manager = mp.Manager() static_input =

问题 I am designing a Python multiprocessing code to work in a queue that might be updated along the processing. The following code sometimes works, or get stuck, or rises an Empty error. import multiprocessing as mp def worker(working_queue, output_queue): while True: if working_queue.empty() is True: break else: picked = working_queue.get_nowait() if picked % 2 == 0: output_queue.put(picked) else: working_queue.put(picked+1) return if __name__ == '__main__': manager = mp.Manager() static_input =

问题 I would like to use a queue for passing data from a parent to a child process which is launched via multiprocessing.Process . However, since the parent process uses Python's new asyncio library, the queue methods need to be non-blocking. As far as I understand, asyncio.Queue is made for inter-task communication and cannot be used for inter-process communication. Also, I know that multiprocessing.Queue has the put_nowait() and get_nowait() methods but I actually need coroutines that would

问题 Scenario I have a Node.JS service (written using ExpressJS) that accepts image uploads via DnD (example). After an image is uploaded, I do a few things to it: Pull EXIF data from it Resize it These calls are being handled via the node-imagemagick module at the moment and my code looks something like this: app.post('/upload', function(req, res){ ... <stuff here> .... im.readMetadata('./upload/image.jpg', function(err, meta) { // handle EXIF data. }); im.resize(..., function(err, stdout, stderr