Today, we are going to be building an image search abstraction layer that is built on top of the Bing search API. For this purpose, we’ll make use of Node.js + Express and Mongoose as an object manager for MongoDB. Additionally, we’ll harness the power of ECMAScript 6 using Babel.
If you are not familiar with Mongoose, take a look at this recent post. If you want to know more about ECMAScript 6 usage in Node.js with Babel, give this other article a read first.
URL shorteners are very useful. Remembering long and tedious URL addresses, or sharing 100 character URLs with your peers is not what we would call, convenient. That’s why we have services such as the Google URL Shortener, Bitly or TinyURL.
We are going to replicate the functionality that these pages offer to some extent. We’ll start off by creating an API using Node.js and the Express framework, and will integrate with a MongoDB instance to store information making use of Mongoose.
The functionality is quite straightforward, we must implement two endpoints in our application:
Instead of babbling around, let’s set up the project and install all of our dependencies.
Mongoose is a Node.js library that provides MongoDB object mapping features. To put it simple, it creates extensible JavaScript Object representations of the documents stored in a MongoDB instance.
It sounds a tidy bit more complicated that what it actually is, let’s get started with a few examples straight away. If you are familiar with the MongoDB in Node.js, you probably know that managing documents can become a bit cumbersome.
This time, we are going to be creating a request header parser microservice in Node.js. Keep in mind that I’ll be using a set-up similar to that used by the previous two tutorials; for those who have not read them, that means that we’ll be using Express, and code our app using ECMAScript 6 thanks to Babel.
Feel free to go though the creation of a simple Express app post, as well as the set-up for using ECMAScript 6 within your node app.
StartJS 