Learn Browserify, Karma and Twit

In this course we’ll learn how to create Twitter bots. We’ll first learn how to interface with the Twitter API using Twit.js, which allows us to post statuses, search tweets, and interact with followers. We’ll create several example bots that show the diversity of possibilities, using powerful tools such as RiTa.js, Google’s Cloud Vision API, and Tracery. We’ll learn how to tweet data from Google Spreadsheets, and to compose and tweet a song for an audio bot. We’ll also learn how to host our bot logic on Heroku and Docker. 

Twitter API Client for node

Supports both the REST and Streaming API.

twit

Create your own twitter bots

We’ll get a real-time stream of tweets, and learn how to filter a stream by keyword, location, and user.

Use the Twitter Stream API with Twit.js

webpack is a tool to build JavaScript modules in your application. To start using webpack from its cli or api, follow the Installation instructions. webpack simplifies your workflow by quickly constructing a dependency graph of your application and bundling them in the right order. webpack can be configured to customise optimisations to your code, to split vendor/css/js code for production, run a development server that hot-reloads your code without page refresh and many such cool features.

webpack

There are several steps involved with setting up [`Karma`](http://karma-runner.github.io/) to work on your webpack project. In this first step we'll initialize our karma configuration and setup our `package.json` `scripts`.

Initialize a Webpack Project with Karma for Testing

Chai is a BDD / TDD assertion library for node and the browser that can be delightfully paired with any javascript testing framework.

chai

[Chai](https://npmjs.com/package/chai) assertions work great with the [Mocha](https://npmjs.com/package/mocha) testing framework. In this lesson we'll walk through out to install Chai and [karma-chai](https://npmjs.com/package/karma-chai) so you can use the `expect` assertions in your tests.

Use Chai assertions for tests in a Karma project

When writing tests run by Karma for an application that’s bundled with webpack, it’s easiest to integrate webpack and Karma directly together. In this lesson we’ll see how to utilize the [`karma-webpack`](https://npmjs.com/package/karma-webpack) plugin and reuse our existing webpack configuration to preprocess our test files with webpack.

Use Karma for Unit Testing with Webpack

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

browserify

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

Lightweight yet powerful IDE, perfectly equipped for complex client-side development and server-side development with Node.js.

webstorm

A quick tutorial covering installing Karma and running tests from the command line and Webstorm.

Introduction to Karma

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

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

In this lesson, our bot will tweet hello to the Twitter world! We'll do this by using Twit's POST method to post our status to the statuses/update endpoint.

Post Statuses with Twit.js

In this lesson, we’ll create multiple functions to request, download, and save photos and data from NASA's API, and then have our bot upload these photos to Twitter and post them along with their descriptions. We'll also learn how to tweet videos using a video from NASA’s space archives.

Tweet Media Files with Twit.js

We’ll learn how your bot can get its list of followers, follow people, and look up friendships. We'll use Twit's GET method to get our followers at the followers/list endpoint, to get the users we follow at the friends/ids and friends/list endpoints, and to look up our friendships with the friendships/lookup endpoint. We'll also use Twit's POST method to follow someone at the friendships/create endpoint, and to send messages by posting to the direct_messages/new endpoint. 

Work with Users in Twit.js

We’ll learn the basics of interacting with tweets, including retweeting, deleting, favoriting, and replying to tweets. We'll get our home timeline by using Twit's GET method to access the `statuses/home_timeline` endpoint, including the count parameter, which lets us get back a certain number of tweets. We'll also pass it a callback. We'll learn how to cycle through the data (the tweets) we get back and see what information is included. We'll learn how to retweet statuses by posting to `statuses/retweet` and including the tweet id. We can unretweet by posting to `statuses/unretweet` with the same tweet id. We'll also learn how to like a tweet by posting to `favorites/create` with a tweet id, and unlike a tweet by posting to `favorites/destroy` with a tweet id. We'll also learn how to reply to a tweet by posting to `statuses/update`, with a status that includes the handle of the user we're replying to and `in_reply_to_status_id` parameter, which is the id of the tweet we're replying to. We'll learn how to delete a tweet by posting to `statuses/destroy` with the tweet's id. 

Interact with Tweets with Twit.js 

We’ll learn how to search tweets with the Twitter Search API, using Twit's GET method to get the search/tweets endpoint. We'll use the query and count parameters to get the search term(s) and number of tweets that we want. We'll learn how to get exact phrases, multiple words, one of several words, emoticons, hashtags, photos/videos, urls, and how to remove words from our results. We'll learn how to implement the safe filter and how to filter by media, website, or date. We'll learn how to get recent results, popular results, results by location, and results by language. 

The search API returns for relevance, and not completeness. If you want all the tweets from a search term, you should use the stream API (which we'll go over in the next lesson). 

Use the Twitter Search API with Twit.js

We’ll go over the basic Twitter bot setup, including how to start a project from scratch, install necessary packages, and store our private keys in environment variables. 

Set Up a Basic Twitter Bot with Twit.js

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.

Topics

Instructors

Content Type