rabbitmq-easy 1.0.5

A simple, robust RabbitMQ manager for Python applications

RabbitMQ Easy

A simple, robust RabbitMQ manager for Python applications with built-in connection management, retry logic, and dead letter queue support.

Features

• Automatic Connection Management: Built-in retry logic and connection recovery
• Dead Letter Queue Support: Automatic setup of dead letter exchanges and queues
• Comprehensive Logging: Both file and console logging with emoji indicators
• Environment Variable Support: Easy configuration through environment variables
• Idempotent Operations: Safe to run multiple times without errors
• Context Manager Support: Proper resource cleanup
• Production Ready: Used in production environments
• Resource Management: Built-in cleanup and deletion functions

Installation

pip install rabbitmq-easy

Quick Start

Basic Usage

from rabbitmq_easy import RabbitMQManager

# Simple setup
manager = RabbitMQManager(
    host='localhost',
    port=5672,
    username='guest',
    password='guest',
    queues=['orders', 'payments'],
    routing_keys=['orders.*', 'payments.*'],
    exchange='my_exchange'
)

# Publish a message
manager.publish_message('my_exchange', 'orders.new', '{"order_id": 123}')

# Use as context manager
with RabbitMQManager() as manager:  # Uses environment variables
    manager.publish_message('my_exchange', 'orders.new', '{"order_id": 123}')

Environment Variables Setup

Create a .env file:

RABBITMQ_HOST=localhost
RABBITMQ_PORT=5672
RABBITMQ_USERNAME=guest
RABBITMQ_PASSWORD=guest
RABBITMQ_EXCHANGE=my_exchange
RABBITMQ_QUEUES=orders,payments,notifications
RABBITMQ_ROUTING_KEYS=orders.*,payments.*,notifications.*

Then use:

from rabbitmq_easy import create_rabbitmq_manager

# Auto-loads from environment variables
manager = create_rabbitmq_manager()

Advanced Usage

Custom Configuration

from rabbitmq_easy import RabbitMQManager

# Advanced configuration
manager = RabbitMQManager(
    host='rabbitmq.example.com',
    port=5672,
    username='user',
    password='pass',
    queues=['high_priority', 'low_priority'],
    routing_keys=['urgent.*', 'normal.*'],
    exchange='task_exchange',
    dead_letter_exchange='failed_tasks',
    dead_letter_routing_key='failed',
    dead_letter_queue_name='failed_tasks',
    max_retries=3,
    retry_delay=5,
    enable_console_logging=True,
    log_level='INFO'
)

# Setup additional queues dynamically
manager.setup_queue(
    queue_name='special_queue',
    exchange='task_exchange',
    routing_key='special.*'
)

# Get queue information
info = manager.get_queue_info('high_priority')
print(f"Messages in queue: {info['message_count']}")

# Health check
health = manager.health_check()
print(f"Status: {health['status']}")

Consumer Example

import json
from rabbitmq_easy import RabbitMQManager

def process_message(ch, method, properties, body):
    """Process incoming message"""
    try:
        data = json.loads(body)
        print(f"Processing: {data}")
        
        # Your business logic here
        
        # Acknowledge message
        ch.basic_ack(delivery_tag=method.delivery_tag)
    except Exception as e:
        print(f"Error processing message: {e}")
        # Reject message (will go to dead letter queue if configured)
        ch.basic_nack(delivery_tag=method.delivery_tag, requeue=False)

# Setup consumer
with RabbitMQManager() as manager:
    manager.start_consuming('orders', process_message)

Dead Letter Queue Handling

def handle_failed_messages(ch, method, properties, body):
    """Handle messages that failed processing"""
    try:
        # Get failure information
        headers = properties.headers or {}
        death_info = headers.get('x-death', [])
        
        if death_info:
            failure_reason = death_info[0].get('reason')
            failure_count = death_info[0].get('count')
            print(f"Message failed {failure_count} times. Reason: {failure_reason}")
        
        # Reprocess or log the failure
        data = json.loads(body)
        print(f"Dead letter message: {data}")
        
        # Acknowledge to remove from DLQ
        ch.basic_ack(delivery_tag=method.delivery_tag)
        
    except Exception as e:
        print(f"Error handling dead letter: {e}")
        # Acknowledge to prevent infinite loops
        ch.basic_ack(delivery_tag=method.delivery_tag)

# Monitor failed messages
manager.start_consuming('failed_messages', handle_failed_messages)

Configuration Options

Parameter	Environment Variable	Default	Description
host	RABBITMQ_HOST	localhost	RabbitMQ server host
port	RABBITMQ_PORT	5672	RabbitMQ server port
username	RABBITMQ_USERNAME	guest	Username for authentication
password	RABBITMQ_PASSWORD	guest	Password for authentication
queues	RABBITMQ_QUEUES	[]	Comma-separated list of queues
routing_keys	RABBITMQ_ROUTING_KEYS	[]	Comma-separated list of routing keys
exchange	RABBITMQ_EXCHANGE	''	Exchange name
dead_letter_exchange	RABBITMQ_DEAD_LETTER_EXCHANGE	{exchange}_dlx	Dead letter exchange name
dead_letter_routing_key	RABBITMQ_DEAD_LETTER_ROUTING_KEY	dead_letter	Dead letter routing key
max_retries	RABBITMQ_MAX_RETRIES	5	Maximum connection retry attempts
retry_delay	RABBITMQ_RETRY_DELAY	5	Delay between retry attempts
heartbeat	RABBITMQ_HEARTBEAT	60	Connection heartbeat interval
enable_console_logging	RABBITMQ_CONSOLE_LOGGING	True	Enable console logging
log_level	RABBITMQ_LOG_LEVEL	INFO	Logging level

Queue and Exchange Operations

# Delete specific resources
manager.delete_queue("old_queue")
manager.delete_exchange("old_exchange")

# Delete only if empty/unused
manager.delete_queue("queue_name", if_empty=True)
manager.delete_exchange("exchange_name", if_unused=True)

# Purge messages without deleting queue
message_count = manager.purge_queue("queue_name")
print(f"Purged {message_count} messages")

# Clean up dead letter infrastructure
manager.cleanup_dead_letter_setup()

# Delete all resources created by this manager
results = manager.delete_all_setup_resources(confirm=True)

# Complete reset
manager.reset_manager(confirm=True)

Error Handling

The package includes custom exceptions for better error handling:

from rabbitmq_easy import RabbitMQConnectionError, RabbitMQConfigurationError

try:
    manager = RabbitMQManager(
        host='invalid-host',
        queues=['queue1', 'queue2'],
        routing_keys=['key1']  # Mismatch with queues count
    )
except RabbitMQConfigurationError as e:
    print(f"Configuration error: {e}")
except RabbitMQConnectionError as e:
    print(f"Connection error: {e}")

What Gets Created Automatically

When you initialize with:

manager = RabbitMQManager(
    exchange='orders',
    queues=['new_orders', 'pending_orders'],
    routing_keys=['orders.new', 'orders.pending']
)

RabbitMQ Easy automatically creates:

1. orders exchange (main exchange)
2. orders_dlx exchange (dead letter exchange)
3. new_orders queue → bound to orders exchange with orders.new routing key
4. pending_orders queue → bound to orders exchange with orders.pending routing key
5. failed_messages queue → bound to orders_dlx exchange for error handling

All queues are configured with dead letter routing to capture failed messages automatically.

Best Practices

1. Use Environment Variables: Store sensitive information like passwords in environment variables
2. Context Managers: Use with statements for automatic cleanup
3. Dead Letter Queues: Always configure dead letter queues for production
4. Health Checks: Implement health checks in your applications
5. Logging: Monitor logs for connection issues and errors
6. Error Handling: Always handle exceptions in your consumers
7. Resource Cleanup: Use the provided cleanup functions during development

Queue and Routing Key Validation

The number of queues must match the number of routing keys:

# Correct
manager = RabbitMQManager(
    queues=['queue1', 'queue2'],
    routing_keys=['key1', 'key2']  # Same count
)

# Will raise RabbitMQConfigurationError
manager = RabbitMQManager(
    queues=['queue1', 'queue2'],
    routing_keys=['key1']  # Mismatch!
)

Dead Letter Configuration

Don't configure dead letter queues to point to themselves:

# Don't do this - creates infinite loop
manager.setup_queue(
    'my_dlq',
    dead_letter_exchange='same_exchange'
)

# Do this instead
manager.setup_queue('my_dlq', dead_letter_exchange=None)

Monitoring and Health Checks

# Check connection health
health = manager.health_check()
if health['status'] == 'healthy':
    print("RabbitMQ connection is healthy")
else:
    print(f"RabbitMQ connection issues: {health['error']}")

# Get detailed queue information
info = manager.get_queue_info('orders')
print(f"Queue: {info['queue']}")
print(f"Messages: {info['message_count']}")
print(f"Consumers: {info['consumer_count']}")

Production Deployment

Docker Compose Example

version: '3.8'
services:
  app:
    build: .
    environment:
     - ~/etc/<org_name>/.env
    depends_on:
      - rabbitmq
  
  rabbitmq:
    image: rabbitmq:3-management
    environment:
     - ~/etc/<org_name>/.env

Kubernetes ConfigMap

apiVersion: v1
kind: ConfigMap
metadata:
  name: rabbitmq-config
data:
  RABBITMQ_HOST: "rabbitmq-service"
  RABBITMQ_PORT: "5672"
  RABBITMQ_EXCHANGE: "production"
  RABBITMQ_QUEUES: "orders,payments,notifications"
  RABBITMQ_ROUTING_KEYS: "orders.*,payments.*,notifications.*"

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Add tests for your changes
5. Run the test suite (pytest)
6. Commit your changes (git commit -m 'Add amazing feature')
7. Push to the branch (git push origin feature/amazing-feature)
8. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

• Create an issue on GitHub
• Check the documentation

Changelog

See CHANGELOG.md for a detailed list of changes and version history.

Acknowledgments

• Built on top of the excellent pika library
• Inspired by the need for simpler RabbitMQ management in Python applications
• Thanks to the RabbitMQ team for creating an amazing message broker

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Made with ❤️ for the Python community