@djangoproject · Post #529 · 19.12.2017 г., 22:08
http://www.djangocrew.com/blog/how-manage-concurrency-django-models/ In this Post we are going to present two approaches for managing #concurrency in #Django models.
Hashtags
TGINSIGHT SIMILAR POSTS
Изходен канал @clockstackwheels · Post #91 · 26.10
Сейчас 10 лет Яндекс.Такси. Кажется, именно Яндекс первым привел Uber-модель в Россию. Пишут, что мой первый заказ был в мае 2013-го. Целая вечность назад, но я помню — был где-то в районе Лесной, нужно было в точку, удалённую от метро. Как раз крутили рекламу нового сервиса от Яндекса, я скачал, запустил поиск. Ждал минут 15, потом ещё искал, где водитель припарковался. Быстрее было бы дойти. Сейчас уже стало ясно, что сервисы такси — одна из важнейших технологических вех нового времени. Сложно представить себе что-то ещё, что настолько фундаментально поменяло наши жизни. Ни роботы-пылесосы, ни сервисы доставки, ни даже каршеринг — ничто из этого настолько сильно не поделило мир на "до" и "после". Процесс вызова такси по телефону действительно был неприлично труден: следовало знать адрес, где находишься, знать номер таксопарка, а затем ждать неопределенное время, после чего платить весьма немалые деньги водителю налом. К такси прибегали в крайних случаях, когда обойтись другим способом было невозможно. Сокращение такого значительного числа издержек в столь необходимой для людей услуге — перемещение — сопоставимо с изобретением интернета или электричества. Да, и без электричества мы могли обогревать и освещать свои дома, готовить пищу, вращать мельницы. Но на этом примере становится видно, что время и усилия на получение результата очень важны. Такси стало полноценным вариантом повседневного транспорта, а не редкой вынужденной мерой для богатых. Я заказываю такси десяток раз в месяц, и уже всерьез не способен вспомнить, как в принципе возможно было жить без этих сервисов. Что я делал в таких же ситуациях 10 лет назад? Ждал автобус полчаса, шел пешком час? Или даже просто отменял своё намерение добраться в какую-то точку? Лучше, наверное, и не вспоминать. #life
Hashtags
Търсене: #concurrency
@djangoproject · Post #529 · 19.12.2017 г., 22:08
http://www.djangocrew.com/blog/how-manage-concurrency-django-models/ In this Post we are going to present two approaches for managing #concurrency in #Django models.
Hashtags
@djangoproject · Post #95 · 11.07.2016 г., 12:14
https://docs.python.org/3/library/asyncio-dev.html#asyncio-multithreading 18.5.9.3. #Concurrency and #multithreading An event loop runs in a thread and executes all callbacks and tasks in the same thread. While a task is running in the event loop, no other task is running in the same thread. But when the task uses yield from, the task is suspended and the event loop executes the next task. To schedule a callback from a different thread, the BaseEventLoop.call_soon_threadsafe() method should be used. Example: loop.call_soon_threadsafe(callback, *args) Most asyncio objects are not thread safe. You should only worry if you access objects outside the event loop. For example, to cancel a future, don’t call directly its Future.cancel() method, but: loop.call_soon_threadsafe(fut.cancel) To handle signals and to execute subprocesses, the event loop must be run in the main thread. To schedule a coroutine object from a different thread, the run_coroutine_threadsafe() function should be used. It returns a concurrent.futures.Future to access the result: future = asyncio.run_coroutine_threadsafe(coro_func(), loop) result = future.result(timeout) # Wait for the result with a timeout The BaseEventLoop.run_in_executor() method can be used with a thread pool executor to execute a callback in different thread to not block the thread of the event loop. See also The Synchronization primitives section describes ways to synchronize tasks. The Subprocess and threads section lists asyncio limitations to run subprocesses from different threads.
Hashtags
@djangoproject · Post #195 · 08.11.2016 г., 03:18
http://stackoverflow.com/questions/29269370/how-to-properly-create-and-run-concurrent-tasks-using-pythons-asyncio-module In the case of trying to concurrently run two looping Tasks, I've noticed that unless the Task has an internal await expression, it will get stuck in the while loop, effectively blocking other tasks from running (much like a normal while loop). However, as soon the Tasks have to wait--even for just a fraction of a second--they seem to run concurrently without an issue. Thus, the await statements seem to provide the event loop with a foothold for switching back and forth between the tasks, giving the effect of #concurrency. Example output with internal await: running async test ...#boo 0 ...#baa 0 ...boo 1 ...baa 1 ...boo 2 ...baa 2
Hashtags
@djangoproject · Post #157 · 06.09.2016 г., 19:55
https://docs.python.org/2/library/multiprocessing.html #multiprocessing is a package that supports spawning processes using an #API similar to the #threading module. The multiprocessing package offers both local and remote #concurrency, effectively side-stepping the Global Interpreter Lock by using subprocesses instead of #threads. Due to this, the multiprocessing module allows the programmer to fully leverage multiple processors on a given machine. It runs on both Unix and Windows.
@djangoproject · Post #106 · 30.07.2016 г., 21:03
top prev next #ZeroMQ (also known as ØMQ, 0MQ, or #zmq) looks like an embeddable networking #library but acts like a #concurrency framework. It gives you sockets that carry atomic messages across various transports like in-process, inter-process, TCP, and multicast. You can connect sockets N-to-N with patterns like fan-out, pub-sub, task distribution, and request-reply. It's fast enough to be the fabric for clustered products. Its asynchronous I/O model gives you scalable multicore applications, built as asynchronous message-processing tasks. It has a score of language APIs and runs on most operating systems. ZeroMQ is from iMatix and is LGPLv3 open source. http://zguide.zeromq.org/page:all
Hashtags
@githubtrending · Post #14859 · 24.06.2025 г., 11:30
#typescript#cli#clustering#concurrency#dependency_injection#effect#error_handling#javascript#observability#opentelemetry#platform#schema#typescript#workflows Effect is a powerful TypeScript framework that helps you build reliable and complex applications by managing side effects like logging, network calls, and database operations in a safe and organized way. It uses a core `Effect` type to describe workflows that are lazy, composable, and type-safe, allowing you to handle errors and dependencies explicitly. The framework is modular, with many packages for AI, CLI tools, distributed computing, SQL databases, and more, making it flexible for various needs. Using Effect improves code quality, concurrency handling, and maintainability, helping you write robust TypeScript apps efficiently[1][2][4][5]. https://github.com/Effect-TS/effect
@djangoproject · Post #224 · 07.01.2017 г., 16:53
#AI #automated_testing #automation #asyncio #atexit #button #concurrency #Coroutines #data_mining #dropdownbox #Debian #decorators #django_cms #form #Google #Gym #intelligence #input #lists #machine_learning #map #Metaprogramming #Micro_services #monitoring #Multipart #multi_touch_apps #multiprocessing #Nodes #numerical #OAuth #package #pytest #python #requests #Requests #satellite #scrapy #scikit_learn #SciPy #searching #submit #selectbox #sessions #TensorFlow #text_boxes #text #telegram #Threads #tuples #Universe #urllib #upload
Hashtags
@djangoproject · Post #298 · 17.04.2017 г., 07:42
#AI#Artificial_Intelligence #aiohttp #API #AWS #asyncio #audio #automated_testing #automation #atexit #BeeWare #button #client #concurrency #cron #Coroutine #data_analysis #data_mining #data_processing #database #Deep_Learning #Debian #decorator #dispatch #django #dropdownbox #Docker #event #Firefox #form #freeze #functool #Generator #GeoDjango #Google #GPU #Gym #learn #Image_processing #intelligence #input #IOT #lambda #lists #machine_learning #Magenta #map #Metaprogramming #Micro_services #mind #monitoring #MongoDB #Mozilla #Multipart #multi_touch_apps #multiprocessing #Nodes #NoSQL #numeric_computation #numerical #NumPy #OAuth #object_serialization #OCR #overloading #package #parallel #pipeline #protocols #PostGIS #pyAudioAnalysis #PyInstaller #PySide #PyTorch #pytest #python #Pyvideo_archives #Qt #Redis #random #request #REST #satellite #scrapy #scikit_learn #SciPy #searching #submit #selectbox #Selenium #serialization #server #session #socket #sound #task #TensorFlow #text_boxes #text #test #telegram #Thread #transport #tuples #Universe #Unix #urllib #upload #Web
Hashtags
@djangoproject · Post #425 · 28.08.2017 г., 03:37
#AI#Artificial_Intelligence #aiohttp #AngularJS #API #AWS #asyncio #audio #automated_testing #automation #atexit #BeeWare #button #client #concurrency #Coroutine #cron #curl #data_analysis #data_mining #data_processing #database #Deep_Learning #Debian #decorator #dict #dispatch #django #django_cms #dropdownbox #Docker #event #Firefox #form #Generator #GeoDjango #git #Google #GPU #Gym #learn #Image_processing #intelligence #input #IOT #lambda #learn #lists #machine_learning #Magenta #map #Metaprogramming #Micro_services #mind #monitoring #MongoDB #Mozilla #Multipart #multi_touch_apps #multiprocessing #Nodes #NoSQL #numeric_computation #numerical #NumPy #OAuth #object_serialization #OCR #overloading #package #parallel #pipeline #protocols #PostGIS #pyAudioAnalysis #pycon #Pyflakes #PyInstaller #PySide #PyTorch #pytest #python #Pyvideo_archives #Qt #React #Redis #random #request #REST #satellite #scrapy #scikit_learn #SciPy #searching #submit #selectbox #Selenium #serialization #server #socket #task #telegram #TensorFlow #test #text_boxes #text #tuples #unicode #Universe #Unix #urllib #upload #Web
Hashtags
@djangoproject · Post #513 · 30.11.2017 г., 22:00
#AI#Artificial_Intelligence #AJAX #aiohttp #Anaconda #AngularJS #API #Atom #AWS #asyncio (#Asynchronous) #audio #automated_testing #automation #atexit #BeeWare #Big_Data #bitcoin #blockchain #Bluemix #Brython #button #Celery #client #class #classmethod #concurrency #Coroutine #cron #CSS #curl #data_analysis #data_mining #data_processing #database #Deep_Learning#deep_learning #Debian #decorator #deploy #dict #dispatch #django #django_cms #Django_REST_Framework #dropdownbox #Docker #event #Firefox #Flask #form #functions #Generator #GeoDjango #git #Google #GPU #GUI #Gym #host #HTML #httplib #learn #Image_processing #intelligence #input #Instagram #IOT #iPython #Jupyter #lambda #learn #License #Linux #lists #machine_learning #Magenta #map #Matplotlib #Metaprogramming #Micro_services #Micropython #mind #monitoring #MongoDB #modules #Mozilla #Multipart #multi_touch_apps #multiprocessing #Nodes #NoSQL #numeric_computation #numerical #NumPy #network #neural_network #OAuth #object_serialization #OCR #overloading #package #parallel #pipeline #protocols #PostGIS #pyAudioAnalysis #pycon #Pyflakes #PyInstaller #PyPI #PyQt #PySide #PyTorch #pytest #python #Pyvideo_archives #Qt #Raspberry_Pi #React #Redis #random #request #Regular_Expressions (#re) #REST #RSS #satellite #scikit_learn #SciPy #scrapy #searching #selectbox #Selenium #serialization #server #sessions #single_responsibility_principle #socket #Spark #str #submit #task #telegram #template #TensorFlow #test #text_boxes #text #tuples #unicode #Universe #Unix #unit_test #urllib #upload #uWSGI #Web #WSGI
Hashtags