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RabbitMQ Fundamentals

Master the core concepts of RabbitMQ message queuing and the AMQP protocol.

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What is RabbitMQ?

RabbitMQ is a message broker - it accepts and forwards messages. Think of it as a post office: you put mail in a post box, and the postal service delivers it to the recipient.

Decoupling

Producers and consumers don’t need to know about each other

Reliability

Messages are persisted and guaranteed delivery

Flexibility

Multiple routing patterns and protocols

Scalability

Clustering and federation for high availability

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Core Concepts

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Producers

Applications that send messages. 
# Producer sends a message
channel.basic_publish(
    exchange='',
    routing_key='hello',
    body='Hello World!'
)

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Queues

Buffer that stores messages. Messages wait in queues until consumed.
  • Named
  • Durable (survive broker restart) or temporary
  • Exclusive (used by only one connection) or shared
  • Auto-delete (deleted when no consumers)

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Consumers

Applications that receive messages. 
# Consumer receives messages
def callback(ch, method, properties, body):
    print(f"Received {body}")

channel.basic_consume(
    queue='hello',
    on_message_callback=callback,
    auto_ack=True
)

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Exchanges

Routes messages to queues based on rules. Types:
  • Direct: Routes to queues with exact routing key match
  • Topic: Routes based on pattern matching
  • Fanout: Broadcasts to all bound queues
  • Headers: Routes based on message headers

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Bindings

Link between exchange and queue with routing rules. 
# Bind queue to exchange
channel.queue_bind(
    exchange='logs',
    queue=queue_name,
    routing_key='error'
)

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AMQP Protocol

Advanced Message Queuing Protocol - open standard for message-oriented middleware.

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Key Features

  • Platform-agnostic: Works across languages and systems
  • Reliable: Acknowledgments, transactions, persistence
  • Flexible: Multiple exchange types and routing
  • Secure: SASL, TLS support

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Installing RabbitMQ

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Quick Start Example

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Python Producer

import pika

# Connect to RabbitMQ
connection = pika.BlockingConnection(
    pika.ConnectionParameters('localhost')
)
channel = connection.channel()

# Declare queue
channel.queue_declare(queue='hello')

# Send message
channel.basic_publish(
    exchange='',
    routing_key='hello',
    body='Hello World!'
)

print(" [x] Sent 'Hello World!'")

connection.close()

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Python Consumer

import pika

# Connect
connection = pika.BlockingConnection(
    pika.ConnectionParameters('localhost')
)
channel = connection.channel()

# Declare queue (idempotent)
channel.queue_declare(queue='hello')

# Callback function
def callback(ch, method, properties, body):
    print(f" [x] Received {body.decode()}")

# Start consuming
channel.basic_consume(
    queue='hello',
    on_message_callback=callback,
    auto_ack=True
)

print(' [*] Waiting for messages. To exit press CTRL+C')
channel.start_consuming()

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Running the Example

# Terminal 1: Start consumer
python consumer.py

# Terminal 2: Send messages
python producer.py

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Message Acknowledgments

Ensure messages aren’t lost if consumer crashes.

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Auto-Acknowledgment (Unsafe)

# Message acknowledged immediately when delivered
channel.basic_consume(
    queue='hello',
    on_message_callback=callback,
    auto_ack=True  # Dangerous!
)

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Manual Acknowledgment (Safe)

def callback(ch, method, properties, body):
    print(f"Processing {body}")
    # Do work...
    time.sleep(5)
    # Acknowledge after processing
    ch.basic_ack(delivery_tag=method.delivery_tag)

channel.basic_consume(
    queue='tasks',
    on_message_callback=callback,
    auto_ack=False  # Manual ack
)
Always use manual acknowledgments in production! Auto-ack can lose messages if the consumer crashes during processing.

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Message Durability

Survive RabbitMQ server restarts.

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Durable Queue

# Declare durable queue
channel.queue_declare(queue='task_queue', durable=True)

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Persistent Messages

# Mark message as persistent
channel.basic_publish(
    exchange='',
    routing_key='task_queue',
    body=message,
    properties=pika.BasicProperties(
        delivery_mode=2  # Persistent
    )
)
Both queue and messages must be durable for full persistence.

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Fair Dispatch

Distribute work evenly among consumers. 
# Don't give more than 1 message to a worker at a time
channel.basic_qos(prefetch_count=1)

def callback(ch, method, properties, body):
    print(f"Processing {body}")
    time.sleep(body.count(b'.'))  # Simulate work
    ch.basic_ack(delivery_tag=method.delivery_tag)

channel.basic_consume(
    queue='task_queue',
    on_message_callback=callback
)
Without prefetch_count: RabbitMQ dispatches messages round-robin, which can overload slow workers. With prefetch_count=1: RabbitMQ gives next message only when worker finishes current one.

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Exchange Types

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Direct Exchange

Routes to queues with exact routing key match. 
# Declare direct exchange
channel.exchange_declare(exchange='direct_logs', exchange_type='direct')

# Publish with routing key
channel.basic_publish(
    exchange='direct_logs',
    routing_key='error',  # Routing key
    body='Error message'
)

# Bind queue to routing key
channel.queue_bind(
    exchange='direct_logs',
    queue=queue_name,
    routing_key='error'
)
Use case: Log levels (info, warning, error)

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Topic Exchange

Routes based on pattern matching. 
# Declare topic exchange
channel.exchange_declare(exchange='topic_logs', exchange_type='topic')

# Publish
channel.basic_publish(
    exchange='topic_logs',
    routing_key='kern.critical',  # Pattern
    body='Critical kernel error'
)

# Bind with pattern
channel.queue_bind(
    exchange='topic_logs',
    queue=queue_name,
    routing_key='kern.*'  # Matches kern.critical, kern.info, etc.
)

# Wildcards:
# * matches exactly one word
# # matches zero or more words
Use case: Logging with categories (kern.critical, app.info, db.error)

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Fanout Exchange

Broadcasts to all bound queues (ignores routing key). 
# Declare fanout exchange
channel.exchange_declare(exchange='logs', exchange_type='fanout')

# Publish (routing_key ignored)
channel.basic_publish(
    exchange='logs',
    routing_key='',
    body='Log message'
)

# All bound queues receive the message
Use case: Broadcasting notifications, cache invalidation

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Headers Exchange

Routes based on message headers instead of routing key. 
# Publish with headers
channel.basic_publish(
    exchange='headers_exchange',
    routing_key='',
    body='Message',
    properties=pika.BasicProperties(
        headers={'format': 'pdf', 'type': 'report'}
    )
)

# Bind with header matching
channel.queue_bind(
    exchange='headers_exchange',
    queue=queue_name,
    arguments={'x-match': 'all', 'format': 'pdf', 'type': 'report'}
)

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Practical Examples

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Example 1: Task Queue

# producer.py
import pika
import sys

connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
channel = connection.channel()

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=2)  # Persistent
)

print(f" [x] Sent {message}")
connection.close()

# worker.py
import pika
import time

connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
channel = connection.channel()

channel.queue_declare(queue='task_queue', durable=True)
channel.basic_qos(prefetch_count=1)

def callback(ch, method, properties, body):
    print(f" [x] Received {body.decode()}")
    time.sleep(body.count(b'.'))  # Simulate work
    print(" [x] Done")
    ch.basic_ack(delivery_tag=method.delivery_tag)

channel.basic_consume(queue='task_queue', on_message_callback=callback)

print(' [*] Waiting for messages. To exit press CTRL+C')
channel.start_consuming()

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Example 2: Pub/Sub Logging

# emit_log.py
import pika
import sys

connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
channel = connection.channel()

channel.exchange_declare(exchange='logs', exchange_type='fanout')

message = ' '.join(sys.argv[1:]) or "info: Hello World!"
channel.basic_publish(exchange='logs', routing_key='', body=message)

print(f" [x] Sent {message}")
connection.close()

# receive_logs.py
import pika

connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
channel = connection.channel()

channel.exchange_declare(exchange='logs', exchange_type='fanout')

# Exclusive queue (auto-deleted when consumer disconnects)
result = channel.queue_declare(queue='', exclusive=True)
queue_name = result.method.queue

channel.queue_bind(exchange='logs', queue=queue_name)

def callback(ch, method, properties, body):
    print(f" [x] {body.decode()}")

channel.basic_consume(queue=queue_name, on_message_callback=callback, auto_ack=True)

print(' [*] Waiting for logs. To exit press CTRL+C')
channel.start_consuming()

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Management UI

Access at http://localhost:15672 (default credentials: guest/guest) Features:
  • View queues, exchanges, connections
  • Monitor message rates
  • Publish/consume messages manually
  • Manage users and permissions
  • View cluster status

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Best Practices

Prevents message loss if consumer crashes
channel.basic_consume(queue='tasks', on_message_callback=callback, auto_ack=False)
Survive broker restarts
channel.queue_declare(queue='tasks', durable=True)
properties=pika.BasicProperties(delivery_mode=2)
Fair work distribution
channel.basic_qos(prefetch_count=1)
Implement retry logic and connection pooling
try:
    connection = pika.BlockingConnection(params)
except pika.exceptions.AMQPConnectionError:
    # Retry logic
    pass

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Key Takeaways

  • RabbitMQ is a message broker that decouples producers and consumers
  • Queues store messages, exchanges route them
  • Use manual acknowledgments and durable queues in production
  • Choose exchange type based on routing needs
  • Monitor with management UI
Next: RabbitMQ Messaging Patterns →