Learn Algolia, Browserify and Radium

Today’s users expect great things from their search experiences — speed, relevance, and usability, to name a few. Algolia provides developers with out-of-the-box and customizable search experiences that are a joy to build.

This introductory course on the Algolia search solution focuses on the user-facing part of search. Using the Algolia InstantSearch.js front-end library, we’ll see how to build an engaging search experience in no time. (28 minutes, to be exact.) 

**Prerequisites:** 
You don’t need previous experience with search to follow this course — we’ll use an example index with an e-commerce data set preconfigured. We will work mainly in JavaScript, so basic JS knowledge is expected.

If you want to play with your own index settings and data set, you can [create a free Algolia account here](https://www.algolia.com/users/sign_up/hacker/?utm_medium=link&utm_source=egghead&utm_campaign=education), but this is not required to follow along with this first course. 

Algolia's full suite APIs enable teams to develop unique search and discovery experiences for their customers across all platforms and devices. Type a query. Click a link. Open an app. Everything your customers do sends a signal about what they want. Algolia decodes that intent to deliver the right content - instantly.

algolia

Getting Started with Algolia InstantSearch.js

React is one of the web’s most popular frameworks for building JavaScript applications. 

If you know what you’re doing, React can drastically simplify how you build, use, and maintain code.

Whether you’re a React newbie or you’re ready for advanced techniques, you can level-up with egghead. Explore our in-depth courses, lessons, and community resources to build more powerful applications and crack open your career.

react

In a CSS library like Bootstrap we can set a button's style to be "primary" or "secondary" by appending classes. For React components we want to be able to do this via props. Radium enables this by composing styles via an array. This mimicks the cascade of CSS.  

Radium: Updating Button Styles via Props

React's inline styles allow components to stand on their own by not requiring any external CSS. However HTML's style attributes don't support pseudo selectors like `:hover` and `:active`. By using Radium to listen to mouse events we can restore `:hover` and `:active` selectors to inline styles.

Styling a React button component with Radium

Gulp is a toolkit for automating painful or time-consuming tasks in your development workflow, so you can stop messing around and build something.

gulp

Building upon the `watch` task that we begin this lesson with, we’ll look at how to create a local development server using the `app` directory as the web root. By using Browsersync to achieve this, we can also instruct all connected browsers to automatically reload each time our bundle is re-generated. Browsersync has a public `.stream()` method that is designed exactly for this purpose.

Gulp and Browserify - Adding Live Reload with Browsersync

Babel has support for the latest version of JavaScript through syntax transformers. These plugins allow you to use new syntax, right now without waiting for browser support.

babel

What is already a nice workflow using Gulp, Browserify, Watchify & Browsersync to enable auto rebuilds & live browser reloading can be further improved by adding Babelify. A simple wrapper around the popular transpiler Babel, Babelify can ‘transform’ source files as they pass through our stream to enable certain Javascript features not yet available in the Browser or Node. We end the lesson by looking at how to generate & extract sourcemaps using `exorcist`.

Gulp and Browserify - Adding Babel & Source Maps

Browserify lets you require('modules') in the browser by bundling up all of your dependencies.

browserify

Let's look at the basics of setting up Gulp and Browserify. Creating a Gulp task from scratch, we'll cover how to utilise the Browserify API to generate a single `bundle.js` file, catch and log any errors that occur in the compilation process, transform the stream into a format that can be consumed by `gulp.dest` and finish by writing the bundle to a `dist` directory.

Gulp and Browserify - Initial Setup

Beginning with a single Gulp task capable of generating a one-time Browserify bundle, we enable file-watching and incremental rebuilds by incorporating Watchify. We add a second task `watch` & refactor our initial code to enable the bulk of it to be re-used. We’ll look at exactly how to ‘wire’ these tools together and how the relationship between Watchify & Browserify can manifest into a seriously efficient workflow.

Gulp and Browserify - Hooking up Watchify

This will get you started on how to setup the Javascript API client of Algolia search solution. To follow along the video having a free Algolia account already setup will make things easier (but is not required). Once the client is setup we will test it by pushing a couple of records to an index.  

Set up the Algolia JavaScript Client

We’ll load a simple JSON file containing 500 actors records from disk and push it to our Algolia index using the Javascript API client.

Push JSON Data to an Algolia Index from the JavaScript Client

We’ll learn how to push a small amount of data from a local MySQL database to an Algolia index. The first step is to connect to the DB using the `mysql` package, then select all records from the DB and finally push them to Algolia using the JS API client.

Push MySQL Data to an Algolia Index from the JS Client

Using the Lodash library, we’ll see how to split large amounts of data from a local MySQL database into smaller chunks and push them to an Algolia index.  

Push Chunks of Large MySQL Data to an Algolia Index with Lodash

Before playing with Instantsearch widgets and build a rich search experience, the fundamental step is to understand what the library will be dealing with. In this lesson we we’ll cover the anatomy of the JSON search API response send back by Algolia for each search query and how it can be used.

Anatomy of an Algolia Search API Response

We now have a good understanding of the API Response structure, we could go playing with instantsearch JS library right away, that said this Library is building on top of the JS API Client. To get a better grasp on how it works at a lower level, let’s play first with raw hits straight from the JS API client, we’ll take care of better UI with Instantsearch JS right after that.

Leverage the Algolia JS API Client to Display Raw Hits from the API Response

The first step to implement Algolia on the front end using Instantsearch : importing and setting up the library with your credentials. This is what will allow the library to initiate the connection to Algolia servers and the first step to complete before adding some useful widgets.

Set up the Instantsearch JS Library

In this lesson we’ll build a search experience reduced to it’s 2 essential components : a search input and the displayed results. As simple as it is, to build this from scratch would require a fair amount of work. Between listening to the input, making the api call, parsing and displaying the result... To build this using Algolia’s Instantsearch library requires a few lines of code with simply two widgets: the Searchbox and the Hits widget.

Search an Algolia Index with Instantsearch JS searchbox and hits widgets

Displaying barebones Hits won’t catch your user’s attention. The UI is key to provide a good search experience and hits are the meat of this experience so they need extra attention. By using Mustache templating we’ll see how to display rich results to your users. 

Display Rich results with templates in the Hits widget for Instantsearch JS

Every  good search UX make users understand instantly why a given hit is being displayed as part of the result set. One way to achieve that is to highlight the keywords from the query directly inside the Hits. This is built in the API JSON response and in this video we’ll explain how to leverage it easily.

Highlight Keywords in Query Results using the Instantsearch JS Hits Widget

Searching is obviously not limited to inputting text in a searchbox. If your dataset allows it Algolia can leverage of attributes and values. To make use of those facets on the front end, one of the most common widget that you can find in a search UI is the refinement list. With this widget, the user can filter the dataset based on facets. This widget only displays the most relevant facets for the current search context.

Filter Datasets with Facets using Instantsearch JS to add a Refinement List

The hierarchical menu widget is used to create a navigation based on a hierarchy of facet attributes. We generally implement it for categories with subcategories.

Browse results based on a hierarchy of Facets (HierarchicalMenu) in Instantsearch JS

The range input is a simple but useful widget that allows a user filter the results by selecting a numeric range with a minimum and maximum input. In an e-commerce website for instance, this widget would be useful to limit the results where the price is comprised between $X and $Y.

Refine a dataset using a numeric range in Instantsearch JS with the Range Input widget

When performing a complex query, based on several active facets and filters, its tedious for the user to start from scratch if she has to unset all refinements one by one. Thanks to the clearAll widget, this task becomes a one click action for the user and is trivial to implement for us developers as it requires no configuration.

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