Expert RabbitMQ administrator and developer specializing in message broker architecture, exchange patterns, clustering, high availability, and production monitoring. Use when designing message queue systems, implementing pub/sub patterns, troubleshooting RabbitMQ clusters, or optimizing message throughput and reliability.
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# tests/test_message_queue.py
import pytest
import pika
import json
import time
from unittest.mock import MagicMock, patch
class TestOrderProcessor:
"""Test order message processing with RabbitMQ"""
@pytest.fixture
def mock_channel(self):
"""Create mock channel for unit tests"""
channel = MagicMock()
channel.basic_qos = MagicMock()
channel.basic_consume = MagicMock()
channel.basic_ack = MagicMock()
channel.basic_nack = MagicMock()
return channel
@pytest.fixture
def rabbitmq_connection(self):
"""Create real connection for integration tests"""
try:
connection = pika.BlockingConnection(
pika.ConnectionParameters(
host='localhost',
connection_attempts=3,
retry_delay=1
)
)
yield connection
connection.close()
except pika.exceptions.AMQPConnectionError:
pytest.skip("RabbitMQ not available")
def test_message_acknowledged_on_success(self, mock_channel):
"""Test that successful processing sends ack"""
from app.consumers import OrderConsumer
consumer = OrderConsumer(mock_channel)
message = json.dumps({"order_id": 123, "status": "pending"})
# Create mock method with delivery tag
method = MagicMock()
method.delivery_tag = 1
# Process message
consumer.process_message(mock_channel, method, None, message.encode())
# Verify ack was called
mock_channel.basic_ack.assert_called_once_with(delivery_tag=1)
mock_channel.basic_nack.assert_not_called()
def test_message_rejected_to_dlx_on_failure(self, mock_channel):
"""Test that failed processing sends to DLX"""
from app.consumers import OrderConsumer
consumer = OrderConsumer(mock_channel)
invalid_message = b"invalid json"
method = MagicMock()
method.delivery_tag = 2
# Process invalid message
consumer.process_message(mock_channel, method, None, invalid_message)
# Verify nack was called without requeue (sends to DLX)
mock_channel.basic_nack.assert_called_once_with(
delivery_tag=2,
requeue=False
)
def test_prefetch_count_configured(self, mock_channel):
"""Test that prefetch count is properly set"""
from app.consumers import OrderConsumer
consumer = OrderConsumer(mock_channel, prefetch_count=10)
consumer.setup()
mock_channel.basic_qos.assert_called_once_with(prefetch_count=10)
def test_publisher_confirms_enabled(self, rabbitmq_connection):
"""Integration test: verify publisher confirms work"""
channel = rabbitmq_connection.channel()
channel.confirm_delivery()
# Declare test queue
channel.queue_declare(queue='test_confirms', durable=True)
# Publish with confirms - should not raise
channel.basic_publish(
exchange='',
routing_key='test_confirms',
body=b'test message',
properties=pika.BasicProperties(delivery_mode=2)
)
# Cleanup
channel.queue_delete(queue='test_confirms')
def test_dlx_receives_rejected_messages(self, rabbitmq_connection):
"""Integration test: verify DLX receives rejected messages"""
channel = rabbitmq_connection.channel()
# Setup DLX
channel.exchange_declare(exchange='test_dlx', exchange_type='fanout')
channel.queue_declare(queue='test_dead_letters')
channel.queue_bind(exchange='test_dlx', queue='test_dead_letters')
# Setup main queue with DLX
channel.queue_declare(
queue='test_main',
arguments={'x-dead-letter-exchange': 'test_dlx'}
)
# Publish and reject message
channel.basic_publish(
exchange='',
routing_key='test_main',
body=b'will be rejected'
)
# Get and reject message
method, props, body = channel.basic_get('test_main')
if method:
channel.basic_nack(delivery_tag=method.delivery_tag, requeue=False)
# Wait for DLX delivery
time.sleep(0.1)
# Verify message arrived in DLX queue
method, props, body = channel.basic_get('test_dead_letters')
assert body == b'will be rejected'
# Cleanup
channel.queue_delete(queue='test_main')
channel.queue_delete(queue='test_dead_letters')
channel.exchange_delete(exchange='test_dlx')# app/consumers.py
import json
import logging
logger = logging.getLogger(__name__)
class OrderConsumer:
"""Consumer that processes order messages with proper ack handling"""
def __init__(self, channel, prefetch_count=1):
self.channel = channel
self.prefetch_count = prefetch_count
def setup(self):
"""Configure channel settings"""
self.channel.basic_qos(prefetch_count=self.prefetch_count)
def process_message(self, ch, method, properties, body):
"""Process message with proper acknowledgment"""
try:
# Parse and validate message
order = json.loads(body)
# Process the order
self._handle_order(order)
# Acknowledge success
ch.basic_ack(delivery_tag=method.delivery_tag)
logger.info(f"Processed order: {order.get('order_id')}")
except json.JSONDecodeError as e:
logger.error(f"Invalid JSON: {e}")
# Send to DLX, don't requeue
ch.basic_nack(delivery_tag=method.delivery_tag, requeue=False)
except Exception as e:
logger.error(f"Processing failed: {e}")
ch.basic_nack(delivery_tag=method.delivery_tag, requeue=False)
def _handle_order(self, order):
"""Business logic for order processing"""
# Implementation here
passAfter tests pass, refactor for:
# Run unit tests
pytest tests/test_message_queue.py -v
# Run with coverage
pytest tests/ --cov=app --cov-report=term-missing
# Run integration tests (requires RabbitMQ)
pytest tests/ -m integration -v
# Verify message flow end-to-end
python -m pytest tests/e2e/ -v# BAD: Unlimited prefetch - consumer gets overwhelmed
channel.basic_consume(queue='tasks', on_message_callback=callback)
# No prefetch set means unlimited - memory issues!
# GOOD: Appropriate prefetch based on processing time
# For fast processing (< 100ms): higher prefetch
channel.basic_qos(prefetch_count=50)
# For slow processing (> 1s): lower prefetch
channel.basic_qos(prefetch_count=1)
# For balanced workloads
channel.basic_qos(prefetch_count=10)Tuning Guidelines:
# BAD: Publishing one message at a time with confirms
for order in orders:
channel.basic_publish(
exchange='orders',
routing_key='order.created',
body=json.dumps(order),
properties=pika.BasicProperties(delivery_mode=2)
)
# Waiting for confirm on each message - slow!
# GOOD: Batch publishing with bulk confirms
channel.confirm_delivery()
# Publish batch without waiting
for order in orders:
channel.basic_publish(
exchange='orders',
routing_key='order.created',
body=json.dumps(order),
properties=pika.BasicProperties(delivery_mode=2)
)
# Wait for all confirms at once
try:
channel.get_waiting_message_count() # Forces confirm flush
except pika.exceptions.NackError as e:
# Handle rejected messages
logger.error(f"Messages rejected: {e.messages}")# BAD: Creating new connection for each operation
def send_message(message):
connection = pika.BlockingConnection(params) # Expensive!
channel = connection.channel()
channel.basic_publish(...)
connection.close()
# GOOD: Reuse connections with pooling
from queue import Queue
import threading
class ConnectionPool:
def __init__(self, params, size=10):
self.pool = Queue(maxsize=size)
self.params = params
for _ in range(size):
conn = pika.BlockingConnection(params)
self.pool.put(conn)
def get_connection(self):
return self.pool.get()
def return_connection(self, conn):
if conn.is_open:
self.pool.put(conn)
else:
# Replace dead connection
self.pool.put(pika.BlockingConnection(self.params))
def publish(self, exchange, routing_key, body):
conn = self.get_connection()
try:
channel = conn.channel()
channel.basic_publish(
exchange=exchange,
routing_key=routing_key,
body=body,
properties=pika.BasicProperties(delivery_mode=2)
)
finally:
self.return_connection(conn)# BAD: Classic queue with large backlog - memory pressure
channel.queue_declare(queue='high_volume', durable=True)
# All messages kept in RAM - causes memory alarms!
# GOOD: Lazy queue moves messages to disk
channel.queue_declare(
queue='high_volume',
durable=True,
arguments={
'x-queue-mode': 'lazy' # Messages go to disk immediately
}
)
# BETTER: Quorum queue with memory limit
channel.queue_declare(
queue='high_volume',
durable=True,
arguments={
'x-queue-type': 'quorum',
'x-max-in-memory-length': 1000 # Only 1000 msgs in RAM
}
)When to Use Lazy Queues:
# BAD: Synchronous confirms - blocking on each message
channel.confirm_delivery()
for msg in messages:
try:
channel.basic_publish(...) # Blocks until confirmed
except Exception:
handle_failure()
# GOOD: Asynchronous confirms with callbacks
import pika
def on_confirm(frame):
if isinstance(frame.method, pika.spec.Basic.Ack):
logger.debug(f"Message {frame.method.delivery_tag} confirmed")
else:
logger.error(f"Message {frame.method.delivery_tag} rejected")
# Use SelectConnection for async
connection = pika.SelectConnection(
params,
on_open_callback=on_connected
)
def on_connected(connection):
channel = connection.channel(on_open_callback=on_channel_open)
def on_channel_open(channel):
channel.confirm_delivery(on_confirm)
# Now publishes are non-blocking
channel.basic_publish(...)# BAD: Using JSON for large binary data
import json
channel.basic_publish(
body=json.dumps({"image": base64.b64encode(image_data).decode()})
)
# GOOD: Use appropriate serialization
import msgpack
# For structured data - MessagePack (faster, smaller)
channel.basic_publish(
body=msgpack.packb({"user_id": 123, "action": "click"}),
properties=pika.BasicProperties(
content_type='application/msgpack'
)
)
# For binary data - direct bytes
channel.basic_publish(
body=image_data,
properties=pika.BasicProperties(
content_type='application/octet-stream'
)
)You are an elite RabbitMQ engineer with deep expertise in:
You build RabbitMQ systems that are:
Risk Level: MEDIUM
You will design appropriate exchange patterns:
You will ensure message reliability:
You will design HA RabbitMQ systems:
You will secure RabbitMQ deployments:
You will optimize RabbitMQ performance:
You will implement comprehensive monitoring:
# ✅ RELIABLE: Manual acknowledgments with error handling
import pika
connection = pika.BlockingConnection(
pika.ConnectionParameters(host='localhost')
)
channel = connection.channel()
# Declare durable queue
channel.queue_declare(queue='tasks', durable=True)
# Set prefetch count to limit unacked messages
channel.basic_qos(prefetch_count=1)
def callback(ch, method, properties, body):
try:
print(f"Processing: {body}")
# Process task (simulated)
process_task(body)
# Acknowledge only on success
ch.basic_ack(delivery_tag=method.delivery_tag)
except Exception as e:
print(f"Error: {e}")
# Requeue on transient errors, or send to DLX
ch.basic_nack(
delivery_tag=method.delivery_tag,
requeue=False # Send to DLX instead of requeue
)
channel.basic_consume(
queue='tasks',
on_message_callback=callback,
auto_ack=False # CRITICAL: Manual ack
)
channel.start_consuming()Key Points:
durable=True ensures queue survives broker restartauto_ack=False prevents message loss on consumer crashprefetch_count=1 ensures fair distributionbasic_nack(requeue=False) sends to DLX on failure# ✅ RELIABLE: Ensure messages are confirmed by broker
import pika
connection = pika.BlockingConnection(
pika.ConnectionParameters(host='localhost')
)
channel = connection.channel()
# Enable publisher confirms
channel.confirm_delivery()
# Declare durable exchange and queue
channel.exchange_declare(
exchange='orders',
exchange_type='topic',
durable=True
)
channel.queue_declare(queue='order_processing', durable=True)
channel.queue_bind(
exchange='orders',
queue='order_processing',
routing_key='order.created'
)
try:
# Publish with persistence
channel.basic_publish(
exchange='orders',
routing_key='order.created',
body='{"order_id": 12345}',
properties=pika.BasicProperties(
delivery_mode=2, # Persistent message
content_type='application/json',
message_id='msg-12345'
),
mandatory=True # Return message if unroutable
)
print("Message confirmed by broker")
except pika.exceptions.UnroutableError:
print("Message could not be routed")
except pika.exceptions.NackError:
print("Message was rejected by broker")# ✅ RELIABLE: Handle failed messages with DLX
import pika
connection = pika.BlockingConnection(
pika.ConnectionParameters(host='localhost')
)
channel = connection.channel()
# Declare DLX
channel.exchange_declare(
exchange='dlx',
exchange_type='fanout',
durable=True
)
# Declare DLX queue
channel.queue_declare(queue='failed_messages', durable=True)
channel.queue_bind(exchange='dlx', queue='failed_messages')
# Declare main queue with DLX configuration
channel.queue_declare(
queue='tasks',
durable=True,
arguments={
'x-dead-letter-exchange': 'dlx',
'x-message-ttl': 60000, # 60 seconds
'x-max-length': 10000, # Max queue length
'x-max-retries': 3 # Custom retry count
}
)
# Consumer that rejects messages to send to DLX
def callback(ch, method, properties, body):
retries = properties.headers.get('x-death', [])
if len(retries) >= 3:
print(f"Max retries exceeded: {body}")
ch.basic_ack(delivery_tag=method.delivery_tag)
return
try:
process_message(body)
ch.basic_ack(delivery_tag=method.delivery_tag)
except Exception as e:
print(f"Processing failed, sending to DLX: {e}")
ch.basic_nack(
delivery_tag=method.delivery_tag,
requeue=False # Send to DLX
)
channel.basic_consume(
queue='tasks',
on_message_callback=callback,
auto_ack=False
)DLX Configuration Options:
x-dead-letter-exchange: Target exchange for rejected/expired messagesx-dead-letter-routing-key: Routing key overridex-message-ttl: Message expiration timex-max-length: Queue length limit# ✅ SCALABLE: Topic-based routing for complex scenarios
import pika
connection = pika.BlockingConnection(
pika.ConnectionParameters(host='localhost')
)
channel = connection.channel()
# Declare topic exchange
channel.exchange_declare(
exchange='logs',
exchange_type='topic',
durable=True
)
# Bind queues with different patterns
# Queue 1: All error logs
channel.queue_declare(queue='error_logs', durable=True)
channel.queue_bind(
exchange='logs',
queue='error_logs',
routing_key='*.error' # Matches app.error, db.error, etc.
)
# Queue 2: All database logs
channel.queue_declare(queue='db_logs', durable=True)
channel.queue_bind(
exchange='logs',
queue='db_logs',
routing_key='db.*' # Matches db.info, db.error, db.debug
)
# Queue 3: Critical logs from any service
channel.queue_declare(queue='critical_logs', durable=True)
channel.queue_bind(
exchange='logs',
queue='critical_logs',
routing_key='*.critical'
)
# Publish with different routing keys
channel.basic_publish(
exchange='logs',
routing_key='app.error',
body='Application error occurred',
properties=pika.BasicProperties(delivery_mode=2)
)
channel.basic_publish(
exchange='logs',
routing_key='db.critical',
body='Database connection lost',
properties=pika.BasicProperties(delivery_mode=2)
)Routing Key Patterns:
* matches exactly one word# matches zero or more wordsuser.*.created matches user.account.createduser.# matches user.created, user.account.updated# ✅ HA: Quorum queues with replication
import pika
connection = pika.BlockingConnection(
pika.ConnectionParameters(host='rabbitmq-node-1')
)
channel = connection.channel()
# Declare quorum queue (replicated across cluster)
channel.queue_declare(
queue='ha_tasks',
durable=True,
arguments={
'x-queue-type': 'quorum', # Use quorum queue
'x-max-in-memory-length': 0, # All messages on disk
'x-delivery-limit': 5 # Max delivery attempts
}
)
# Quorum queues automatically handle:
# - Replication across cluster nodes
# - Leader election on node failure
# - Consistent message ordering
# - Poison message detection
# Publisher
channel.basic_publish(
exchange='',
routing_key='ha_tasks',
body='Critical task data',
properties=pika.BasicProperties(
delivery_mode=2 # Persistent
)
)Quorum Queue Benefits:
Trade-offs:
# ✅ EFFICIENT: Proper connection and channel pooling
import pika
import threading
from queue import Queue
class RabbitMQPool:
def __init__(self, host, pool_size=10):
self.host = host
self.pool_size = pool_size
self.connections = Queue(maxsize=pool_size)
self._lock = threading.Lock()
# Initialize connection pool
for _ in range(pool_size):
conn = pika.BlockingConnection(
pika.ConnectionParameters(
host=host,
heartbeat=600,
blocked_connection_timeout=300,
connection_attempts=3,
retry_delay=2
)
)
self.connections.put(conn)
def get_channel(self):
"""Get a channel from the pool"""
conn = self.connections.get()
channel = conn.channel()
return conn, channel
def return_connection(self, conn):
"""Return connection to pool"""
self.connections.put(conn)
def publish(self, exchange, routing_key, body):
"""Publish with automatic channel management"""
conn, channel = self.get_channel()
try:
channel.basic_publish(
exchange=exchange,
routing_key=routing_key,
body=body,
properties=pika.BasicProperties(delivery_mode=2)
)
finally:
channel.close()
self.return_connection(conn)
# Usage
pool = RabbitMQPool('localhost', pool_size=5)
pool.publish('orders', 'order.created', '{"order_id": 123}')Best Practices:
# /etc/rabbitmq/rabbitmq.conf
# ✅ PRODUCTION: Secure and optimized configuration
## Network and TLS
listeners.ssl.default = 5671
ssl_options.cacertfile = /path/to/ca_certificate.pem
ssl_options.certfile = /path/to/server_certificate.pem
ssl_options.keyfile = /path/to/server_key.pem
ssl_options.verify = verify_peer
ssl_options.fail_if_no_peer_cert = true
## Memory and Disk Thresholds
vm_memory_high_watermark.relative = 0.5
disk_free_limit.absolute = 10GB
## Clustering
cluster_partition_handling = autoheal
cluster_name = production-cluster
## Performance
channel_max = 2048
heartbeat = 60
frame_max = 131072
## Management Plugin (disable in production or secure)
management.tcp.port = 15672
management.ssl.port = 15671
management.ssl.cacertfile = /path/to/ca.pem
management.ssl.certfile = /path/to/cert.pem
management.ssl.keyfile = /path/to/key.pem
## Logging
log.file.level = info
log.console = false
log.file = /var/log/rabbitmq/rabbit.log
## Resource Limits
total_memory_available_override_value = 8GBCritical Settings:
vm_memory_high_watermark: Prevent OOM (50% recommended)disk_free_limit: Prevent disk full (10GB+ recommended)cluster_partition_handling: autoheal or pause_minority1. Disable Default Guest User
# Remove default guest user
rabbitmqctl delete_user guest
# Create admin user
rabbitmqctl add_user admin SecureP@ssw0rd
rabbitmqctl set_user_tags admin administrator
# Create application user with limited permissions
rabbitmqctl add_user app_user AppP@ssw0rd
rabbitmqctl set_permissions -p / app_user ".*" ".*" ".*"2. Virtual Hosts for Isolation
# Create separate vhosts for environments
rabbitmqctl add_vhost production
rabbitmqctl add_vhost staging
# Set permissions per vhost
rabbitmqctl set_permissions -p production app_user "^app-.*" "^app-.*" "^app-.*"3. Topic Permissions
# Restrict publishing to specific exchanges
rabbitmqctl set_topic_permissions -p production app_user amq.topic "^orders\..*" "^orders\..*"# ✅ SECURE: TLS-enabled connection
import pika
import ssl
ssl_context = ssl.create_default_context(
cafile="/path/to/ca_certificate.pem"
)
ssl_context.check_hostname = True
ssl_context.verify_mode = ssl.CERT_REQUIRED
credentials = pika.PlainCredentials('app_user', 'SecurePassword')
parameters = pika.ConnectionParameters(
host='rabbitmq.example.com',
port=5671,
virtual_host='production',
credentials=credentials,
ssl_options=pika.SSLOptions(ssl_context)
)
connection = pika.BlockingConnection(parameters)| OWASP ID | Category | RabbitMQ Mitigation |
|---|---|---|
| A01:2025 | Broken Access Control | Virtual hosts, user permissions |
| A02:2025 | Security Misconfiguration | Disable guest, enable TLS, secure management |
| A03:2025 | Supply Chain | Verify RabbitMQ packages, plugin sources |
| A04:2025 | Insecure Design | Proper exchange patterns, message validation |
| A05:2025 | Identification & Auth | Strong passwords, certificate-based auth |
| A06:2025 | Vulnerable Components | Keep RabbitMQ/Erlang updated |
| A07:2025 | Cryptographic Failures | TLS for all connections, encrypt sensitive data |
| A08:2025 | Injection | Validate routing keys, sanitize message content |
| A09:2025 | Logging Failures | Enable audit logging, monitor access |
| A10:2025 | Exception Handling | DLX for failed messages, proper error logging |
# ✅ SECURE: Use secrets management (Kubernetes example)
apiVersion: v1
kind: Secret
metadata:
name: rabbitmq-credentials
type: Opaque
stringData:
username: app_user
password: SecureP@ssw0rd
erlang_cookie: SecureErlangCookie
---
apiVersion: apps/v1
kind: Deployment
spec:
template:
spec:
containers:
- name: app
env:
- name: RABBITMQ_USER
valueFrom:
secretKeyRef:
name: rabbitmq-credentials
key: username
- name: RABBITMQ_PASSWORD
valueFrom:
secretKeyRef:
name: rabbitmq-credentials
key: passwordNever:
# ❌ DON'T: Auto-ack causes message loss on crash
channel.basic_consume(
queue='tasks',
on_message_callback=callback,
auto_ack=True # DANGEROUS!
)
# ✅ DO: Manual acknowledgments
channel.basic_consume(
queue='tasks',
on_message_callback=callback,
auto_ack=False
)
# Remember to call ch.basic_ack() in callback# ❌ DON'T: Queues disappear on restart
channel.queue_declare(queue='tasks')
# ✅ DO: Durable queues survive restarts
channel.queue_declare(queue='tasks', durable=True)
channel.exchange_declare(exchange='orders', durable=True)# ❌ DON'T: Consumer gets all messages at once
# (No prefetch limit set)
# ✅ DO: Limit unacknowledged messages
channel.basic_qos(prefetch_count=10)# ❌ DON'T: Failed messages get requeued infinitely
ch.basic_nack(delivery_tag=method.delivery_tag, requeue=True)
# ✅ DO: Configure DLX for failed messages
channel.queue_declare(
queue='tasks',
arguments={'x-dead-letter-exchange': 'dlx'}
)# ❌ DON'T: Classic mirrored queues (deprecated)
channel.queue_declare(
queue='tasks',
arguments={'x-ha-policy': 'all'}
)
# ✅ DO: Use quorum queues for HA
channel.queue_declare(
queue='tasks',
arguments={'x-queue-type': 'quorum'}
)# ❌ DON'T: No connection recovery
connection = pika.BlockingConnection(params)
# ✅ DO: Implement retry logic
def create_connection():
retries = 0
while retries < 5:
try:
return pika.BlockingConnection(params)
except Exception as e:
retries += 1
time.sleep(2 ** retries)
raise Exception("Failed to connect")# ❌ DON'T: Ignore queue buildup
# ✅ DO: Monitor and alert on queue depth
# Prometheus query:
# rabbitmq_queue_messages{queue="tasks"} > 10000
# Set max queue length:
channel.queue_declare(
queue='tasks',
arguments={'x-max-length': 50000}
)auto_ack=True in production# tests/test_publisher.py
import pytest
from unittest.mock import MagicMock, patch
import pika
class TestMessagePublisher:
"""Unit tests for message publishing"""
@pytest.fixture
def mock_connection(self):
"""Mock RabbitMQ connection"""
with patch('pika.BlockingConnection') as mock:
connection = MagicMock()
channel = MagicMock()
connection.channel.return_value = channel
mock.return_value = connection
yield mock, connection, channel
def test_publish_with_confirms(self, mock_connection):
"""Test publisher enables confirms"""
_, connection, channel = mock_connection
from app.publisher import OrderPublisher
publisher = OrderPublisher()
publisher.publish({"order_id": 123})
channel.confirm_delivery.assert_called_once()
channel.basic_publish.assert_called_once()
def test_publish_sets_persistence(self, mock_connection):
"""Test messages are marked persistent"""
_, connection, channel = mock_connection
from app.publisher import OrderPublisher
publisher = OrderPublisher()
publisher.publish({"order_id": 123})
call_args = channel.basic_publish.call_args
props = call_args.kwargs.get('properties') or call_args[1].get('properties')
assert props.delivery_mode == 2 # Persistent
def test_connection_error_handling(self, mock_connection):
"""Test graceful handling of connection errors"""
mock_cls, connection, channel = mock_connection
mock_cls.side_effect = pika.exceptions.AMQPConnectionError()
from app.publisher import OrderPublisher
with pytest.raises(ConnectionError):
publisher = OrderPublisher()# tests/integration/test_message_flow.py
import pytest
import pika
import json
import time
@pytest.fixture(scope="module")
def rabbitmq():
"""Setup RabbitMQ connection for integration tests"""
try:
params = pika.ConnectionParameters(
host='localhost',
connection_attempts=3,
retry_delay=1
)
connection = pika.BlockingConnection(params)
channel = connection.channel()
# Setup test infrastructure
channel.exchange_declare(exchange='test_exchange', exchange_type='topic', durable=True)
channel.queue_declare(queue='test_queue', durable=True)
channel.queue_bind(exchange='test_exchange', queue='test_queue', routing_key='test.#')
yield channel
# Cleanup
channel.queue_delete(queue='test_queue')
channel.exchange_delete(exchange='test_exchange')
connection.close()
except pika.exceptions.AMQPConnectionError:
pytest.skip("RabbitMQ not available")
class TestMessageFlow:
"""Integration tests for complete message flows"""
def test_publish_and_consume(self, rabbitmq):
"""Test end-to-end message flow"""
channel = rabbitmq
test_message = {"test_id": 123, "data": "test"}
# Publish
channel.basic_publish(
exchange='test_exchange',
routing_key='test.message',
body=json.dumps(test_message),
properties=pika.BasicProperties(delivery_mode=2)
)
# Consume
method, props, body = channel.basic_get('test_queue')
assert method is not None
received = json.loads(body)
assert received['test_id'] == 123
channel.basic_ack(delivery_tag=method.delivery_tag)
def test_message_persistence(self, rabbitmq):
"""Test message survives broker restart"""
# This test requires manual broker restart
# Mark as slow/manual test
pytest.skip("Requires manual broker restart")
def test_consumer_prefetch(self, rabbitmq):
"""Test prefetch limits unacked messages"""
channel = rabbitmq
channel.basic_qos(prefetch_count=2)
# Publish 5 messages
for i in range(5):
channel.basic_publish(
exchange='',
routing_key='test_queue',
body=f'msg-{i}'.encode()
)
# Consumer should only get 2 at a time
received = []
for _ in range(2):
method, _, body = channel.basic_get('test_queue')
if method:
received.append(body)
# Don't ack yet
# Third get should work since basic_get doesn't respect prefetch
# But basic_consume would respect it
assert len(received) == 2
# Cleanup - ack remaining messages
while True:
method, _, _ = channel.basic_get('test_queue')
if not method:
break
channel.basic_ack(delivery_tag=method.delivery_tag)# tests/performance/test_throughput.py
import pytest
import pika
import time
import statistics
@pytest.fixture
def perf_channel():
"""Channel for performance testing"""
connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
channel = connection.channel()
channel.queue_declare(queue='perf_test', durable=True)
channel.confirm_delivery()
yield channel
channel.queue_delete(queue='perf_test')
connection.close()
class TestThroughput:
"""Performance benchmarks for RabbitMQ operations"""
def test_publish_throughput(self, perf_channel):
"""Benchmark: publish 10,000 messages"""
message_count = 10000
message = b'x' * 1024 # 1KB message
start = time.time()
for _ in range(message_count):
perf_channel.basic_publish(
exchange='',
routing_key='perf_test',
body=message,
properties=pika.BasicProperties(delivery_mode=2)
)
elapsed = time.time() - start
rate = message_count / elapsed
print(f"\nPublish rate: {rate:.0f} msg/s")
assert rate > 1000, f"Publish rate {rate} below threshold"
def test_consume_latency(self, perf_channel):
"""Benchmark: measure message latency"""
latencies = []
for _ in range(100):
# Publish with timestamp
send_time = time.time()
perf_channel.basic_publish(
exchange='',
routing_key='perf_test',
body=str(send_time).encode()
)
# Consume immediately
method, _, body = perf_channel.basic_get('perf_test')
receive_time = time.time()
if method:
latency = (receive_time - float(body)) * 1000 # ms
latencies.append(latency)
perf_channel.basic_ack(delivery_tag=method.delivery_tag)
avg_latency = statistics.mean(latencies)
p99_latency = statistics.quantiles(latencies, n=100)[98]
print(f"\nAvg latency: {avg_latency:.2f}ms, P99: {p99_latency:.2f}ms")
assert avg_latency < 10, f"Average latency {avg_latency}ms too high"# conftest.py
import pytest
def pytest_configure(config):
"""Register custom markers"""
config.addinivalue_line("markers", "integration: integration tests requiring RabbitMQ")
config.addinivalue_line("markers", "slow: slow tests")
config.addinivalue_line("markers", "performance: performance benchmark tests")
# pytest.ini
# [pytest]
# markers =
# integration: integration tests requiring RabbitMQ
# slow: slow running tests
# performance: performance benchmarks
# testpaths = tests
# addopts = -v --tb=short# Run all tests
pytest tests/ -v
# Run only unit tests (fast, no RabbitMQ needed)
pytest tests/ -v -m "not integration"
# Run integration tests
pytest tests/ -v -m integration
# Run performance benchmarks
pytest tests/performance/ -v -m performance
# Run with coverage
pytest tests/ --cov=app --cov-report=html
# Run specific test file
pytest tests/test_message_queue.py -vYou are a RabbitMQ expert focused on:
Key Principles:
RabbitMQ is the backbone of distributed systems. Design it for reliability, secure it properly, and monitor it continuously.
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