Knowledge Nation

Hi, today we are going to learn about RabbitMQ, a message broker software.

What is Message Borker?

Message broker is an intermediary program module that translates a message from the formal messaging protocol of the sender to the formal messaging protocol of the receive

– source wikipedia

It act as an intermediate between sender and receiver.

What is RabbitMQ?

RabbitMQ is an open source message broker software which implements Advanced Message Queuing Protocol (AMQP). It can act as pub-sub, routing and queuing system.

RabbitMQ Message Flow

Producer: Creates a message to send it to exchange

Broker: It consist of three parts

Exchange: Receive published messages and send it to appropriate queue on the basis of routing key.
Binding: It is a link between queue and exchange
Routing key: It helps in selecting queue i.e. which message is will be send to which queue.

Consumer: Consumer consumes the message from the queue they are bind.

Installation

Development Environment

Ubuntu 14.04 LTS
Python 2.7
PIP (python package manager)

Follow the steps to start using RabbitMQ

# Create Directory and enter it

// create directory 
mkdir rmq 
// enter directory 
cd ./rmq

// create directory

mkdir rmq

// enter directory

cd ./rmq

# Create and activate virtual environment

Don’t know how to install virtual environment, check the official doc at docs.python-guide.org.

// create virtual environment venv
virtualenv venv
// activate virtual environment
source venv/bin/activate

// create virtual environment venv

virtualenv venv

// activate virtual environment

source venv/bin/activate

Download requirements.txt file to install all packages in your virtual environment using following command or you can go step by step with the tutorial.

// put requirements.txt in your root folder(rmq)
pip install -r requirements.txt

1 2	// put requirements.txt in your root folder(rmq) pip install -r requirements.txt

# Install RabbitMQ

sudo apt-get install rabbitmq-server

1	sudo apt-get install rabbitmq-server

Once you install rabbitmq server, it will starts running automatically

# Enable RabbiMQ management plugin

rabbitmq-plugins enable rabbitmq_management

1	rabbitmq-plugins enable rabbitmq_management

It will give you a WebUI to manage and monitor rabbitmq. By default it runs on port 15672, you can access it in your browser by going to url http://127.0.0.1:15672/. Default username and password for WebUI is guest and guest respectively.

# Install pika

Pika is a pure-Python implementation of the AMQP 0-9-1 protocol that tries to stay fairly independent of the underlying network support library.

– source python.org

pip install pika

1	pip install pika

# Create Producer (message.py)

Producer sends a string message to “messages” queue.

import pika

# creating connection with rabbitmq-server at localhost
connection = pika.BlockingConnection(pika.ConnectionParameters(
        host='localhost'))
channel = connection.channel()

# setting queue to insert the message
channel.queue_declare(queue='messages', durable=True)

# message string
message = "HI we are learning rabbitmq"

# sending message to rabbitmq with a routing key
channel.basic_publish(exchange='',
                      routing_key='messages',
                      body=message,
                      properties=pika.BasicProperties(
                         delivery_mode = 2,
                      ))
print "######\nSending new message\n######"
print message
connection.close()

import pika

# creating connection with rabbitmq-server at localhost

connection = pika.BlockingConnection(pika.ConnectionParameters(

host='localhost'))

channel = connection.channel()

# setting queue to insert the message

channel.queue_declare(queue='messages', durable=True)

# message string

message = "HI we are learning rabbitmq"

# sending message to rabbitmq with a routing key

channel.basic_publish(exchange='',

routing_key='messages',

body=message,

properties=pika.BasicProperties(

delivery_mode = 2,

))

print "######\nSending new message\n######"

print message

connection.close()

# Create Consumer (worker.py)

Consumer will receive message and process it. Here, consume is listening on “messages” queue.

import pika

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

channel.queue_declare(queue='messages', durable=True)
print('>> Waiting for messages')

def callback(ch, method, properties, body):
    print(">> Received message " % body)
    ch.basic_ack(delivery_tag = method.delivery_tag)

# prefetch+count = 1  tells consumer to recieve 1 message at a time
channel.basic_qos(prefetch_count=1)

# teling consumer to consume message from messages queue and then send a callback for further operations
channel.basic_consume(callback,
                      queue='messages')

# consuming queue starts
channel.start_consuming()

import pika

connection = pika.BlockingConnection(pika.ConnectionParameters(

host='localhost'))

channel = connection.channel()

channel.queue_declare(queue='messages', durable=True)

print('>> Waiting for messages')

def callback(ch, method, properties, body):

print(">> Received message " % body)

ch.basic_ack(delivery_tag = method.delivery_tag)

# prefetch+count = 1 tells consumer to recieve 1 message at a time

channel.basic_qos(prefetch_count=1)

# teling consumer to consume message from messages queue and then send a callback for further operations

channel.basic_consume(callback,

queue='messages')

# consuming queue starts

channel.start_consuming()

# Run Producer and Consumer

Run producer and consumer in two different terminal in order to see sending and receiving of messages simultaneously.

// producer running in terminal 1 
python ./message.py

1 2	// producer running in terminal 1 python ./message.py

When we run message.py, message got inserted into queue but since there is no consumer listening on that queue therefor it shows one message is ready for publishing as “Ready” equals to 1.

Click on messages in above UI and we can get stats about individual queues. As you can see 1 message which we sent earlier is still in queue.

# Start consumer

// consumer running in terminal 2
python ./worker.py

1 2	// consumer running in terminal 2 python ./worker.py

As soon as we start our consumer worker.py, it will receive message from queue and now you can see ready count is 0.

Sending Multiple Messages

Create a loop to send 10 bulk message in queue.

import pika

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

channel.queue_declare(queue='messages', durable=True)
for i in range(1, 10):
	message = "This is message "+ str(i)
	channel.basic_publish(exchange='',
	                      routing_key='messages',
	                      body=message,
	                      properties=pika.BasicProperties(
	                         delivery_mode = 2,
	                      ))
	print "Sending Message >> "+message
connection.close()

import pika

connection = pika.BlockingConnection(pika.ConnectionParameters(

host='localhost'))

channel = connection.channel()

channel.queue_declare(queue='messages', durable=True)

for i in range(1, 10):

message = "This is message "+ str(i)

channel.basic_publish(exchange='',

routing_key='messages',

body=message,

properties=pika.BasicProperties(

delivery_mode = 2,

))

print "Sending Message >> "+message

connection.close()

Now start two instances of your worker.py

When you start two instances of worker.py, you can see message got evenly distributed on the basis of Round Robin Algorithm.Also, same message is not delivered to multiple workers.

It’s a simple example, now we send dict as message.

Create a new file dict-message.py

import pika
import json

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

channel.queue_declare(queue='dict_messages', durable=True)
for i in range(1, 10):
	message = {
		'id': i,
		'msg': 'message '+ str(i)
	}
	channel.basic_publish(exchange='',
	                      routing_key='dict_messages',
	                      body=json.dumps(message), # to send dict as a message in json
	                      properties=pika.BasicProperties(
	                         delivery_mode = 2, 
	                      ))
	print "Sending Message >> " + str(message)
connection.close()

import pika

import json

connection = pika.BlockingConnection(pika.ConnectionParameters(

host='localhost'))

channel = connection.channel()

channel.queue_declare(queue='dict_messages', durable=True)

for i in range(1, 10):

message = {

'id': i,

'msg': 'message '+ str(i)

}

channel.basic_publish(exchange='',

routing_key='dict_messages',

body=json.dumps(message), # to send dict as a message in json

properties=pika.BasicProperties(

delivery_mode = 2,

))

print "Sending Message >> " + str(message)

connection.close()

In order to read message now, we have to change our worker a little bit.

Create a new file dict-message-worker.py

import pika
import json

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

channel.queue_declare(queue='dict_messages', durable=True)
for i in range(1, 10):
	message = {
		'id': i,
		'msg': 'message '+ str(i)
	}
	channel.basic_publish(exchange='',
	                      routing_key='dict_messages',
	                      body=json.dumps(message), # to send dict as a message in json
	                      properties=pika.BasicProperties(
	                         delivery_mode = 2, 
	                      ))
	print "Sending Message >> " + str(message)
connection.close()

import pika

import json

connection = pika.BlockingConnection(pika.ConnectionParameters(

host='localhost'))

channel = connection.channel()

channel.queue_declare(queue='dict_messages', durable=True)

for i in range(1, 10):

message = {

'id': i,

'msg': 'message '+ str(i)

}

channel.basic_publish(exchange='',

routing_key='dict_messages',

body=json.dumps(message), # to send dict as a message in json

properties=pika.BasicProperties(

delivery_mode = 2,

))

print "Sending Message >> " + str(message)

connection.close()

We use json to send and receive message. As you can see when we send dict as message in a new queue “dict_messages” , consumer listening to that queue start receiving message instantly.

Now you have fair amount of knowledge of RabbiMQ you can use it in any appropriate project like for send notification, storing logs, sending bulk emails and many more.

For further reading check rabbitmq official docs at rabbitmq.com.

That’s all for today, hope you enjoy and do try at home.

Download source code Up-and-Running-with-RabbitMQ-A-Message-Broker-tusharsharma.in.zip

Hi all, today we will learn about “traits in php”. As we know, PHP is a single inheritance language i.e. a class defined in PHP can’t inherit more than one class. “Traits” are introduced to solve this problem.

What are Traits?

“A Trait is similar to a class, but only intended to group functionality in a fine-grained and consistent way.” source php.net

Trait is just like a helper class which group reusable code.

It helps to follow DRY (Don’t Repeat Yourself).

You cannot instantiate a Trait on its own.

Trait vs Interface

When we use Interface then the class which is implementing have to implement all the method but in Trait we can define many function and can use a few. In trait, we can give definitions of a function for ex. a function can perform some task and return value.

Example

Let’s create two files main.class.php and child.class.php where child class inherits main class.

<?php
/**
* main.class.php
*/
class Main
{
	
	function showMessage()
	{
		echo "Hi from parent class ".__METHOD__;
	}
}
?>

<?php

/**

* main.class.php

class Main

{

function showMessage()

{

echo "Hi from parent class ".__METHOD__;

}

<?php
include __DIR__.DIRECTORY_SEPARATOR.'main.class.php';
/**
* child.class.php
*/
class Child extends Main
{
	
}
?>

<?php

include __DIR__.DIRECTORY_SEPARATOR.'main.class.php';

/**

* child.class.php

class Child extends Main

{

}

Now we will create a trait file to use in child class, so let’s create a trait file as message.trait.php

<?php
/**
* message.trait.php
*/
trait Message {
	
	public function showMessage()
	{
		echo 'Hi friends you are learning traits in php';
	}

	public function sum( $num1, $num2 )
	{
		$sum = $num1 + $num2;
		return 'Method called '.__METHOD__.' Sum of '.$num1.' and '.$num2.' is '.$sum;
	}

}
?>

<?php

/**

* message.trait.php

trait Message {

public function showMessage()

{

echo 'Hi friends you are learning traits in php';

}

public function sum( $num1, $num2 )

{

$sum = $num1 + $num2;

return 'Method called '.__METHOD__.' Sum of '.$num1.' and '.$num2.' is '.$sum;

}

Now let’s create an object of child class and call showMessage method and get output as follows

“Hi from parent class Main::showMessage”

Now, to use trait we have to include file in child and use keyword “use” and updated file look as follows.

<?php
include __DIR__.DIRECTORY_SEPARATOR.'main.class.php';
include __DIR__.DIRECTORY_SEPARATOR.'message.trait.php';
/**
* child.class.php
*/
class Child extends Main
{
	use Message;

	public function sum( $num1, $num2 )
	{
		$sum = $num1 + $num2;
		return 'Method called '.__METHOD__.' Sum of '.$num1.' and '.$num2.' is '.$sum;
	}

}

<?php

include __DIR__.DIRECTORY_SEPARATOR.'main.class.php';

include __DIR__.DIRECTORY_SEPARATOR.'message.trait.php';

/**

* child.class.php

class Child extends Main

{

use Message;

public function sum( $num1, $num2 )

{

$sum = $num1 + $num2;

return 'Method called '.__METHOD__.' Sum of '.$num1.' and '.$num2.' is '.$sum;

}

Create object of child class and call method showMessage and you can see output as follows

“Hi friends you are learning traits in php” which comes from showMessage function from trait.

Now create an object and call method sum with params 1 and 2 and you will get output as follows:

“Method called Child::sum Sum of 1 and 2 is 3” i.e. we can easily override trait function.

That’s it from traits, hope it will be a great add-on in your next project.

Up and Running with RabbitMQ – A Message Broker

What is Message Borker?

What is RabbitMQ?

RabbitMQ Message Flow

Installation

Sending Multiple Messages

Traits in PHP

What are Traits?

Trait vs Interface

Example

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