93 lines
2.0 KiB
Python
93 lines
2.0 KiB
Python
#!/usr/bin/env python
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import pika
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from functools import lru_cache
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import time
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# Establecemos la conexión a RabbitMQ
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def create_connection():
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try:
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connection = pika.BlockingConnection(
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pika.ConnectionParameters(host='localhost')
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)
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return connection
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except pika.exceptions.AMQPConnectionError as e:
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print(f"[!] Error al conectar a RabbitMQ: {e}")
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return None
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# Conexión a RabbitMQ
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connection = create_connection()
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if not connection:
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exit(1)
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# Canal de comunicación con RabbitMQ
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channel = connection.channel()
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# Declaración de la cola 'rpc_queue'
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channel.queue_declare(queue='rpc_queue')
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# Implementación mejorada de Fibonacci con memoización
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@lru_cache(maxsize=None)
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def fib(n):
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if n < 0:
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raise ValueError("\n[!] El número no puede ser negativo.")
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elif n == 0:
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return 0
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elif n == 1:
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return 1
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else:
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return fib(n - 1) + fib(n - 2)
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# Callback para procesar solicitudes RPC
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def on_request(ch, method, props, body):
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try:
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n = int(body)
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print(f" [+] Calculando fib({n})")
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# Simula un tiempo de procesamiento de 2 segundos
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time.sleep(2)
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response = fib(n)
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print(f" [+] Resultado: {response}")
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except ValueError as e:
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response = f"\n[!] Error: {str(e)}"
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except Exception as e:
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response = f"\n[!] Error inesperado: {str(e)}"
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# Publicar la respuesta al cliente
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ch.basic_publish(
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exchange='',
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routing_key=props.reply_to,
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properties=pika.BasicProperties(correlation_id=props.correlation_id),
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body=str(response)
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)
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# Confirmar la recepción del mensaje
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ch.basic_ack(delivery_tag=method.delivery_tag)
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# Configuración de calidad de servicio y consumo de mensajes
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channel.basic_qos(prefetch_count=1)
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channel.basic_consume(queue='rpc_queue', on_message_callback=on_request)
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print("\n[i] Esperando solicitudes RPC")
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channel.start_consuming()
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