Trading with concurrency- the Basics

In this piece, we will discuss the advantages of using RabbitMQ as a message broker for an app and provide some example python code for you play around with.

Reliable

RabbitMQ is a reliable message broker. It provides a reliable, persistent messaging infrastructure that ensures messages are delivered in a timely manner, even during peak times. This ensures that the app is always available to its users, even when there is high demand. RabbitMQ also provides a variety of message routing options, allowing messages to be routed to different consumers, depending on their needs. This helps to ensure that the app is well-suited to the needs of its users.

Scale

RabbitMQ is a highly scalable message broker. It is capable of handling high volumes of messages without any performance degradation. This makes it ideal for apps that require a high level of scalability. RabbitMQ also provides support for clustering, which allows messages to be routed to multiple nodes in a distributed system. This helps to ensure that messages are always delivered, even if one node fails.

Secure

RabbitMQ is a secure message broker. It provides a secure communication layer between the producer and consumer, ensuring that messages are not intercepted or tampered with. This helps to ensure that the app is secure and that users’ data is protected.

In conclusion, RabbitMQ is an ideal message broker for an app. It provides a reliable, persistent messaging infrastructure, scalability, and security, making it an ideal choice for any app that requires asynchronous communication. With its reliable delivery and scalability, RabbitMQ can help ensure that the app is always available to its users, no matter how high the demand.

A Producer consumer example to work with:

1. First, you will need to install the RabbitMQ library for Python, “pika”, using the following command:

pip install pika
pip install websocket-client

2. In the producer code, you will parse the websocket data and put it into a queue. Below, this block imports the pika and websocket libraries and uses them to connect to a websocket and parse the data. It then connects to RabbitMQ, declares a queue, and publishes the data to the queue. Finally, it closes the connection.

import pika
import websocket

def on_message(ws, message):
    # Parse the websocket data
    data = json.loads(message)

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

    # Declare a queue
    channel.queue_declare(queue='websocket_data')

    # Publish the data to the queue
    channel.basic_publish(exchange='',
                          routing_key='websocket_data',
                          body=json.dumps(data))

    # Close the connection
    connection.close()

# Connect to the websocket
websocket.enableTrace(True)
ws = websocket.WebSocketApp("wss://your-websocket-url",
                            on_message=on_message)
ws.run_forever()

3. In the consumer code, you will demonstrate how a client can access the queue. Here is a sample implementation:

import pika

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

# Declare a queue
channel.queue_declare(queue='websocket_data')

# Callback function to handle incoming messages
def callback(ch, method, properties, body):
    # Print the data from the queue
    print("Received data: ", body.decode())

# Consume the data from the queue
channel.basic_consume(queue='websocket_data',
                      auto_ack=True,
                      on_message_callback=callback)

# Start consuming messages
print('Waiting for messages. To exit press CTRL+C')
channel.start_consuming()

Above is sample implementation of how RabbitMQ can be used as a message broker in Python to parse websocket data, put it into a queue, and demonstrate how a client can access the queue.