From 6cc75cc6ebd12082f2909392ec192d79ab2ae898 Mon Sep 17 00:00:00 2001 From: Kochkareva Date: Fri, 19 Jan 2024 11:39:52 +0400 Subject: [PATCH] kochkareva_elizaveta_lab_4 is ready --- kochkareva_elizaveta_lab_4/README.md | 190 ++++++++++++++++++ .../exercise-training/consumer-1.py | 37 ++++ .../exercise-training/consumer-2.py | 28 +++ .../exercise-training/publisher.py | 17 ++ kochkareva_elizaveta_lab_4/fast-queue.jpg | Bin 0 -> 75736 bytes .../hello-world-receive.jpg | Bin 0 -> 16291 bytes .../hello-world-send.jpg | Bin 0 -> 9885 bytes .../hello-world/receive.py | 30 +++ .../hello-world/send.py | 11 + .../publish-subscribe-emit-log.jpg | Bin 0 -> 90362 bytes .../publish-subscribe-receive-logs1.jpg | Bin 0 -> 66044 bytes .../publish-subscribe-receive-logs2.jpg | Bin 0 -> 64688 bytes .../publish-subscribe/emit_log.py | 13 ++ .../publish-subscribe/receive_logs.py | 22 ++ kochkareva_elizaveta_lab_4/slow-queue.jpg | Bin 0 -> 77406 bytes .../work-queues-new-task.jpg | Bin 0 -> 42371 bytes .../work-queues-worker.jpg | Bin 0 -> 40024 bytes .../work-queues/new_task.py | 20 ++ .../work-queues/worker.py | 23 +++ 19 files changed, 391 insertions(+) create mode 100644 kochkareva_elizaveta_lab_4/README.md create mode 100644 kochkareva_elizaveta_lab_4/exercise-training/consumer-1.py create mode 100644 kochkareva_elizaveta_lab_4/exercise-training/consumer-2.py create mode 100644 kochkareva_elizaveta_lab_4/exercise-training/publisher.py create mode 100644 kochkareva_elizaveta_lab_4/fast-queue.jpg create mode 100644 kochkareva_elizaveta_lab_4/hello-world-receive.jpg create mode 100644 kochkareva_elizaveta_lab_4/hello-world-send.jpg create mode 100644 kochkareva_elizaveta_lab_4/hello-world/receive.py create mode 100644 kochkareva_elizaveta_lab_4/hello-world/send.py create mode 100644 kochkareva_elizaveta_lab_4/publish-subscribe-emit-log.jpg create mode 100644 kochkareva_elizaveta_lab_4/publish-subscribe-receive-logs1.jpg create mode 100644 kochkareva_elizaveta_lab_4/publish-subscribe-receive-logs2.jpg create mode 100644 kochkareva_elizaveta_lab_4/publish-subscribe/emit_log.py create mode 100644 kochkareva_elizaveta_lab_4/publish-subscribe/receive_logs.py create mode 100644 kochkareva_elizaveta_lab_4/slow-queue.jpg create mode 100644 kochkareva_elizaveta_lab_4/work-queues-new-task.jpg create mode 100644 kochkareva_elizaveta_lab_4/work-queues-worker.jpg create mode 100644 kochkareva_elizaveta_lab_4/work-queues/new_task.py create mode 100644 kochkareva_elizaveta_lab_4/work-queues/worker.py diff --git a/kochkareva_elizaveta_lab_4/README.md b/kochkareva_elizaveta_lab_4/README.md new file mode 100644 index 0000000..9704801 --- /dev/null +++ b/kochkareva_elizaveta_lab_4/README.md @@ -0,0 +1,190 @@ + +# Лабораторная работа 4. + +### Задание +**Цель**: изучение проектирования приложений при помощи брокера сообщений. + +**Задачи**: + +- Установить брокер сообщений RabbitMQ. +- Пройти уроки 1, 2 и 3 из RabbitMQ Tutorials на любом языке программирования. +- Продемонстрировать работу брокера сообщений. + +### Как запустить лабораторную работу +В директории с файлом характеристик docker-compose.yaml выполнить команду: +``` +docker-compose -f docker-compose.yaml up +``` +### Описание лабораторной работы +#### Прохождение tutorial + +**1. *"Hello world"*** + +Результат работы producer: +![Сборка docker-compose](hello-world-send.jpg) + +Результат работы consumer: +![Сборка docker-compose](hello-world-receive.jpg) + + +**2. *"Work Queues"*** + +Результат работы producer: +![Сборка docker-compose](work-queues-new-task.jpg) + +Результат работы consumer: +![Сборка docker-compose](work-queues-worker.jpg) + +**3. *"Publish/Subscribe"*** + +Результат работы producer: +![Сборка docker-compose](publish-subscribe-emit-log.jpg) + +Результат работы consumer1: +![Сборка docker-compose](publish-subscribe-receive-logs1.jpg) + +Результат работы consumer2: +![Сборка docker-compose](publish-subscribe-receive-logs2.jpg) + + +#### Разработка демонстрационных приложений +Для разработки демонстрационных приложений была выбрана предметная область прошлой лабораторной работы, состоящая из тренировок и упражнений. + +Согласно заданию необходимо создать: +1. Publisher, которая создаёт один exchange с типом fanout. + +Для этого создадим список logs, который хранит различные сообщения логов, которые могут быть отправлены. + +```python +logs = ["started exercise", "finished exercise", "started training", "finished training"] +``` + +Установим соединение с локальным *RabbitMQ* сервером на `localhost` и создадим канал связи с *RabbitMQ* для отправки и получения сообщений. + +```python +connection = pika.BlockingConnection(pika.ConnectionParameters('localhost')) +channel = connection.channel() +``` + +Далее определим имя обмена в *RabbitMQ*, в данном случае logs и объявем обмен с указанным именем и типом fanout, что означает, что все сообщения, отправленные в этот обмен, будут отправлены всем подписчикам, которые присоединены к нему. +```python +exchange_name = 'logs' +channel.exchange_declare(exchange=exchange_name, exchange_type='fanout') +``` + +Для того, чтобы программа раз в секунду генерировала сообщения в журнал событий создадим цикл, в котором будет выбираться случайное сообщение из списка `logs`, публиковаться в обмен `logs` без указания ключа маршрутизации (сообщение будет доставлено всем подписчикам этого обмена). И также укажем задержку в 1 секунду между каждой публикацией сообщения. +```python +while 1: + log = random.choice(logs) + channel.basic_publish(exchange=exchange_name, routing_key='', body=log) + print(f" [x] Published: {log}") + time.sleep(1) +``` + +2. Consumer 1, которая создаёт под себя отдельную не анонимную очередь, создаёт binding на exchange и начинает принимать сообщения. Программа должна обрабатывать сообщения 2-3 секунды. + +Создадим функцию `message_manager`, которая принимает три аргумента: `channel` (канал связи с RabbitMQ), `queue_name` (имя очереди) и `exchange_name` (имя обмена). +Затем объявляем очеред с указанным именем, связываем очередь с обменом, чтобы сообщения из этого обмена были доставлены в эту очередь. + +Также создаем функцию `callback`, которая будет вызываться при получении нового сообщения из очереди. В данной функции происходит декодирование полученного сообщения из байтового формата в строку, вывод результата в консоль и имитация обработки сообщения с помощью задержки сообщения на 2-3 секунды. В зависимости от полученного значения декодированого сообщения, происходит вывод сообщение о статусе обработки, а также происходит подтверждение успешной обработки сообщения. + +```python + def callback(ch, method, properties, body): + task = body.decode() + print(f" [x] Received : {task}") + time.sleep(random.randint(2, 3)) + if task == "started exercise": + print(" [x] Started timer") + elif task == "finished exercise": + print(" [x] Stopped timer, started another exercise") + elif task == "started training": + print(" [x] Started manage exercise") + else: + print(" [x] Result of training given") + ch.basic_ack(delivery_tag=method.delivery_tag) +``` + +Далее устанавливаем обработчик callback для сообщений из указанной очереди и запускаем бесконечный цикл получения и обработки сообщений из очереди. +Таким образом, функция `message_manager` выглядет следующим образом: + +```python +def message_manager(channel, queue_name, exchange_name): + channel.queue_declare(queue=queue_name) + channel.queue_bind(exchange=exchange_name, queue=queue_name) + + def callback(ch, method, properties, body): + task = body.decode() + print(f" [x] Received : {task}") + time.sleep(random.randint(2, 3)) + if task == "started exercise": + print(" [x] Started timer") + elif task == "finished exercise": + print(" [x] Stopped timer, started another exercise") + elif task == "started training": + print(" [x] Started manage exercise") + else: + print(" [x] Result of training given") + ch.basic_ack(delivery_tag=method.delivery_tag) + + channel.basic_consume(queue=queue_name, on_message_callback=callback) + print("[*] Waiting for messages. To exit press CTRL+C") + channel.start_consuming() +``` + +Далее создаем соединение с *RabbitMQ*, создаем канал и определяем имя обмена и имя очереди. Затем, создаем поток `consumer_thread`, который вызывает функцию `message_manager` с передачей канала, имени очереди и имени обмена в качестве аргументов. После этого, поток запускается и ожидает его завершения с помощью `consumer_thread.join()`, чтобы основной поток программы не завершился до завершения работы обработчика сообщений. + +```python +connection = pika.BlockingConnection(pika.ConnectionParameters('localhost')) +channel = connection.channel() +exchange_name = 'logs' +queue_name = 'slow-queue' + +consumer_thread = threading.Thread(target=message_manager, args=(channel, queue_name, exchange_name)) +consumer_thread.start() +consumer_thread.join() +``` + + +3. Consumer 2. Аналогично Consumer 1, только сообщения необходимо обрабатывать моментально и имя очереди должно отличаться от Consumer 1. + +Аналогично создаем подключение к серверу с помощью `pika.BlockingConnection`,создаем канал для обмена сообщениями с помощью `connection.channel()`. Определяем имя обменника *"logs"* и имя очереди *"fast-queue"*. Далее объявляем саму очередь с данным именем. + +```python +connection = pika.BlockingConnection(pika.ConnectionParameters('localhost')) +channel = connection.channel() +exchange_name = 'logs' +queue_name = 'fast-queue' + +channel.queue_declare(queue=queue_name) +channel.queue_bind(exchange=exchange_name, queue=queue_name) +``` + +После чего создаем функцию `callback`, которая будет вызываться при получении сообщений из очереди. Функция принимает параметры `ch` (канал), `method` (метод доставки), `properties` (свойства сообщения) и `body` (тело сообщения). В данном случае, функция аналогично декодирует тело сообщения в строку и выводит соответствующее сообщение в зависимости от значения `task`. +```python +def callback(ch, method, properties, body): + task = body.decode() + print(f" [x] Received : {task}") + if task == "started exercise": + print(" [x] Started timer") + elif task == "finished exercise": + print(" [x] Stopped timer, started another exercise") + elif task == "started training": + print(" [x] Started manage exercise") + else: + print(" [x] Result of training given") + ch.basic_ack(delivery_tag=method.delivery_tag) + +``` +Код будет ожидать и обрабатывать сообщения, пока не будет прерван. + +Результат работы быстрой очереди: +![Сборка docker-compose](fast-queue.jpg) + +Результат работы медленной очереди: +![Сборка docker-compose](slow-queue.jpg) + +Таким образом, можно сделать вывод о том, что в очереди fast-queue сообщения обрабатываются мгновенно, а в очереди slow-queue они обрабатываются с задержкой и в следствии этого сообщения накапливаются в очереди. + +### Видео + +https://disk.yandex.ru/i/Qei-5DvhovOBJA \ No newline at end of file diff --git a/kochkareva_elizaveta_lab_4/exercise-training/consumer-1.py b/kochkareva_elizaveta_lab_4/exercise-training/consumer-1.py new file mode 100644 index 0000000..046d0bd --- /dev/null +++ b/kochkareva_elizaveta_lab_4/exercise-training/consumer-1.py @@ -0,0 +1,37 @@ +import pika +import random +import threading +import time + + +def message_manager(channel, queue_name, exchange_name): + channel.queue_declare(queue=queue_name) + channel.queue_bind(exchange=exchange_name, queue=queue_name) + + def callback(ch, method, properties, body): + task = body.decode() + print(f" [x] Received : {task}") + time.sleep(random.randint(2, 3)) + if task == "started exercise": + print(" [x] Started timer") + elif task == "finished exercise": + print(" [x] Stopped timer, started another exercise") + elif task == "started training": + print(" [x] Started manage exercise") + else: + print(" [x] Result of training given") + ch.basic_ack(delivery_tag=method.delivery_tag) + + channel.basic_consume(queue=queue_name, on_message_callback=callback) + print("[*] Waiting for messages. To exit press CTRL+C") + channel.start_consuming() + + +connection = pika.BlockingConnection(pika.ConnectionParameters('localhost')) +channel = connection.channel() +exchange_name = 'logs' +queue_name = 'slow-queue' + +consumer_thread = threading.Thread(target=message_manager, args=(channel, queue_name, exchange_name)) +consumer_thread.start() +consumer_thread.join() diff --git a/kochkareva_elizaveta_lab_4/exercise-training/consumer-2.py b/kochkareva_elizaveta_lab_4/exercise-training/consumer-2.py new file mode 100644 index 0000000..59f9da8 --- /dev/null +++ b/kochkareva_elizaveta_lab_4/exercise-training/consumer-2.py @@ -0,0 +1,28 @@ +import pika + +connection = pika.BlockingConnection(pika.ConnectionParameters('localhost')) +channel = connection.channel() +exchange_name = 'logs' +queue_name = 'fast-queue' + +channel.queue_declare(queue=queue_name) +channel.queue_bind(exchange=exchange_name, queue=queue_name) + + +def callback(ch, method, properties, body): + task = body.decode() + print(f" [x] Received : {task}") + if task == "started exercise": + print(" [x] Started timer") + elif task == "finished exercise": + print(" [x] Stopped timer, started another exercise") + elif task == "started training": + print(" [x] Started manage exercise") + else: + print(" [x] Result of training given") + ch.basic_ack(delivery_tag=method.delivery_tag) + + +channel.basic_consume(queue=queue_name, on_message_callback=callback) +print("[*] Waiting for messages. To exit press CTRL+C") +channel.start_consuming() diff --git a/kochkareva_elizaveta_lab_4/exercise-training/publisher.py b/kochkareva_elizaveta_lab_4/exercise-training/publisher.py new file mode 100644 index 0000000..d0ecc6b --- /dev/null +++ b/kochkareva_elizaveta_lab_4/exercise-training/publisher.py @@ -0,0 +1,17 @@ +import pika +import random +import time + +logs = ["started exercise", "finished exercise", "started training", "finished training"] + +connection = pika.BlockingConnection(pika.ConnectionParameters('localhost')) +channel = connection.channel() +exchange_name = 'logs' +channel.exchange_declare(exchange=exchange_name, exchange_type='fanout') +print(' [*] Started. To exit press CTRL+C') + +while 1: + log = random.choice(logs) + channel.basic_publish(exchange=exchange_name, routing_key='', body=log) + print(f" [x] Published: {log}") + time.sleep(1) diff --git a/kochkareva_elizaveta_lab_4/fast-queue.jpg b/kochkareva_elizaveta_lab_4/fast-queue.jpg new file mode 100644 index 0000000000000000000000000000000000000000..2e82f449ade124156610484bdd1a071dc1d21bca GIT binary patch literal 75736 zcmeFZ1ymi&wkX*jm_pbn|l$fL#00993=z$O5`wGOIq_D8=OGSAx zNf}Wv0{|fU0dRp70su=Z2RlXa7o=+H8l=Eq%4-9Ao4=rc2f;QjCIRpn06@G*w{V5LSPul?vvRC%Is*Wxs6T1?aR5*g006l2f6^#30pRg_0H_B2 zNjsJQala7Q?GA5Tz;yutImYLJ&1<{Y4=?}){y-WT0l-Nf03fRa0LBOaAZY%q#}5e@ zdvHVlfc|}_?{k130R5xDfD0TPEF2sH{G&(k2#*mE!N+546jT)OA2uc~208{VCIulb zE+NHJa#HfA%=Glk0=xnW3YHN6Zw-8J2hbitvcmvS5NH4-8Uz#?#P?2s1KeJakWdf) z_IrVWg@A^Hf_nrH_RgQ>cMbpv0R;^M3-^5%K!O76p+cd8S+`ez@c%yqJSs`Ga$@kv zr3XT3fd!ne ziBZgB6?4Oa-J=l6XC)=QYZbOyht(zS>HNGcl`BXueNbe_~{nv4(zszrqY&(Q=94*^*?_>U=S}sNN2cDwpZRJZW?MFPQAh@ 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+channel.queue_declare(queue='task_queue', durable=True) + +message = ' '.join(sys.argv[1:]) or "Hello World!" +channel.basic_publish( + exchange='', + routing_key='task_queue', + body=message, + properties=pika.BasicProperties( + delivery_mode=pika.DeliveryMode.Persistent + )) +print(f" [x] Sent {message}") +connection.close() + diff --git a/kochkareva_elizaveta_lab_4/work-queues/worker.py b/kochkareva_elizaveta_lab_4/work-queues/worker.py new file mode 100644 index 0000000..6f52082 --- /dev/null +++ b/kochkareva_elizaveta_lab_4/work-queues/worker.py @@ -0,0 +1,23 @@ +import pika +import time + +connection = pika.BlockingConnection( + pika.ConnectionParameters(host='localhost')) +channel = connection.channel() + +channel.queue_declare(queue='task_queue', durable=True) +print(' [*] Waiting for messages. To exit press CTRL+C') + + +def callback(ch, method, properties, body): + print(f" [x] Received {body.decode()}") + time.sleep(body.count(b'.')) + print(" [x] Done") + ch.basic_ack(delivery_tag=method.delivery_tag) + + +channel.basic_qos(prefetch_count=1) +channel.basic_consume(queue='task_queue', on_message_callback=callback) + +channel.start_consuming() +