Although messages flow through RabbitMQ and your applications, they can be stored only inside a queue. A consumer mostly waits to receive messages. The consumer is the receiver of a message.The producer is the sender of a message.The basic elements of AMQP are (quoting from RabbitMQ’s official documentation 5):
WEBSCRAPER TUTORIAL SOFTWARE
RabbitMQ is an open source “message broker” software that implements the Advanced Message Queuing Protocol (AMQP) 4. The following picture depicts how the main parts work together:
WEBSCRAPER TUTORIAL INSTALL
pip install -r requirements.txt is preferably done in a virtualenv 3.Īlso, for this post I’m using Python 2. Note: vagrant up takes a while the first time it’s executed.
Python-scraping-service$ python worker.py Python-scraping-service$ pip install -r requirements.txt Knockout-frontend$ python -m SimpleHTTPServer 8090 Scraping-microservice-java-python-rabbitmq$ cd java-api-backend Scraping-microservice-java-python-rabbitmq$ vagrant up $ cd scraping-microservice-java-python-rabbitmq The project has three parts that are independently deployed and executed: To run the application, clone/fork the repository. Change the line to -auto=validate (after you have started up the backend at least once) to avoid data loss. However, this means all tables get erased with each new start. Note: to make things easier, in application.properties the line -auto=create allows us to automatically create the tables when starting up. Note: if you want to get rid of the vagrant virtual machine, just run vagrant destroy. All you need to do is vagrant up (requires Virtualbox installed and some hard drive space for the image). I’m using Vagrant to install Postgres and RabbitMQ on a virtual machine. If interested, have a look at the post.Īs usual, the project is available on Github 2. Because of this, I won’t repeat what I have already explained there (mainly the REST API, JPA persistence, CORS and the details of the knockout.js front-end). This project is an enhancement of a previous project that implemented a bookmark web app: Rapid prototyping with Spring Data Rest and Knockout.js, by adding scraping functionality to the bookmark service. The main backend functionality, however, is implemented in Java using Spring Boot (personally, I prefer using the JVM as the core of any application). It so happens that for Python exists a good website summary library, which we are going to use to extract a short summary of a website. This is an example that shows one advantage of the microservices 1 pattern: it is easy to implement an independent part of an application in a programming language that is most suitable for the task at hand. The application is a web scraping service that takes an URL and returns a text summary of the site.
WEBSCRAPER TUTORIAL HOW TO
In this post, I’m going to show how to implement a message-driven application that consists of three independent parts.
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