113 lines
3.0 KiB
Markdown
113 lines
3.0 KiB
Markdown
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# Отчет по лабораторной работе №4
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Выполнил студентка гр. ИСЭбд-41 Лямзина М.А.
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## Прохождение tutorial
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Установил rabbitMQ server, erlang и зашел в брокер под гостем по http://localhost:15672/#/
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Туториал 1:
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
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Туториал 2:
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Туториал 3:
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## Разработка демонстрационных приложений
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Предметная область: Организация мероприятий.
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Разработа три приложения согласно предметной области.
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1. Publisher
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```py
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import pika
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import time
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import random
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collection = ["Types of events", "Event venues", "Event management services", "Event participants"]
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connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
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channel = connection.channel()
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channel.exchange_declare(exchange='Event', exchange_type='fanout')
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while True:
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message = f"Message: {random.choice(collection)}"
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channel.basic_publish(exchange='Event', routing_key='', body=message)
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time.sleep(1)
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connection.close()
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```
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2. Consumer 1.
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```py
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import pika
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import time
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def process_message(ch, method, properties, body):
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print(f"Получено сообщение: {body}")
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time.sleep(3)
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print("Сообщение успешно обработано")
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connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
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channel = connection.channel()
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result = channel.queue_declare(queue='', exclusive=True)
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queue_name = result.method.queue
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channel.queue_bind(exchange='Event', queue=queue_name)
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channel.basic_consume(queue=queue_name, on_message_callback=process_message, auto_ack=True)
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print('Ожидание сообщений...')
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channel.start_consuming()
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```
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3. Consumer 2.
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```py
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import pika
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def process_message(ch, method, properties, body):
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print(f"Получено сообщение: {body}")
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print("Сообщение успешно обработано")
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connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
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channel = connection.channel()
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result = channel.queue_declare(queue='', exclusive=True)
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queue_name = result.method.queue
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channel.queue_bind(exchange='Event', queue=queue_name)
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channel.basic_consume(queue=queue_name, on_message_callback=process_message, auto_ack=True)
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print('Ожидание сообщений...')
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channel.start_consuming()
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```
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## Результаты выполнения лабораторной работы
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Результат отработки Consumer_1:
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
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Результат отработки Consumer_2:
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
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
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Вывод: Consumer_2 нагружает меньше памяти, чем Consumer_1 и принимает сообщения гораздо быстрее, тем самым не позволяя очереди накапливать огромное количество сообщений.
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