Starting with NodeJS-HapiJS and ReactJS

Name: Starting with NodeJS-HapiJS and ReactJS
Rating: 4.5 (158 reviews)

Build Restful sentiment analysis API with HapiJS, connect with React. Learn NodeJS, ReactJS, NLTK-sentiment analysis

Created byEvans Boateng Owusu

Last updated 1/2018

English

What you'll learn

Build a NodeJS/HapiJS API server.
Integrate Python NLP sentiment analysis in their NodeJS application.
Build a ReactJS application that interacts with a server API.
Understand Promises in JavaScript.
Understand fetch API in JavaScript.
Integrate python in NodeJS.

Course content

4 sections • 16 lectures • 1h 53m total length

Introduction1:40
Build a NodeJS json-based API server for sentiment analysis. Create a React JS client that interacts with the server, sends sentences, and displays results.

Initialize NodeJS project3:53
Configure Babel transpiler6:30
initialize with package.json, install babel-register and babel-preset-env to transpile ES6/ES7 to ES5, configure .babelrc with env, and require babel-register in index.js to run the server.
Start hapi server10:11
Install happy package, add babel polyfill, create a hapi server in Node.js with a server.js file and routes for home page and centralized path, then start on localhost:5000.
JS Promise explained6:43
Explains synchronous vs asynchronous code using a setTimeout example, introduces promise as an object representing an eventual completion, and shows how await, async, and then handle resolution or rejection.
Separate server routes8:49
Learn to separate server routes from the model using a routes module, register routes, and test a post-based endpoint that accepts a json sentence and returns sentiment analysis.
Nodemon for auto-reload2:45
Install nodemon to enable auto-reload during development, replacing npm start with nodemon to watch for code changes.
Introduce NLTK (Natural Language ToolKit) for sentiment analysis6:08
Learn to build a sentiment analysis API using nltk in python, integrate python with nodejs, and configure the vader lexicon for sentiment analysis.
Implement sentiment analysis Python module8:31
Create a Python Vader model to analyze sentence sentiment via command line, computing negative, neutral, and positive scores and selecting the top sentiment.
Integrate sentiment analysis python module via Python-shell12:02
Integrate a Python sentiment analyzer into a Node.js app using Python Shell and promisify. Create a route that runs the script and returns positive, negative, or neutral sentiment.

Start with create-react-app5:23
Implement a React client that posts sentences to the sentiment analysis API and displays the result (positive, negative, neutral) using a text area, a submit button, and reusable components.
Create form component10:55
Build a React class-based query form component with a text area for sentiment analysis and a submit button, while exploring Create React App structure, jsx className, state, and render.
Add styles to form8:44
Style the form by adding a query form css, center a 50% wrapper, use white labels, and set the text area and button to full width with hover effects.
Add event handler to textarea in form7:03
Learn to attach an onChange handler to a textarea, manage component state with setState to reflect input, and enable or disable the submit button based on trimmed text presence.
Onclick listener and fetch API11:03

Requirements

Basic programming knowledge

Description

With this course, you will learn to build a NodeJS (HapiJS) JSON-based Restful API backend for sentiment analysis and a ReactJS client that interacts with the API. HapiJS, a rich and configuration-centric server framework for NodeJS allows us to build powerful and configurable applications. Moreover, sentiment analysis allows automated reasoning about sentences to determine whether they are positive, negative or neutral. A popular use case is to find out how people feel about a product or service. This is course introduces you to a powerful Python package, NLTK (Natural Language ToolKit), that allows you to do more than sentiment analysis. Aside from learning and building together a HapiJS API and ReactJS App, we learn how to integrate the NLTK Python package (and for that matter any other Python package) into a NodeJS application.

We will start by first building a HapiJS server that can receive texts and send simple responses. We will interact with our server via Chrome's Postman plugin. Then, we will integrate VADER NLTK sentiment analysis into the server, that will allow the server to determine the sentiments of sentences in English. Afterwards, we will build a ReactJS client that allows us to enter and send sentences to the server and display the sentiment of a our sentence.

So, in summary, this learning by doing doing course is prepared for you to:

learn the HapiJS framework of NodeJS for building API backends.
learn to use the VADER module of the NLTK (Natural Language ToolKit) for sentiment analysis.
learn to integrate Python modules into NodeJS.
learn to build apps in ReactJS.
understand the new concepts in JavaScript (e.g Promise, arrow functions, etc).

Who this course is for:

Anyone who wants to learn to build NodeJS/HapiJS API servers.
Anyone who wants to learn to integrate sentiment analysis into their server.
Anyone who wants to learn to integrate Python in their NodeJS applications.
Anyone who wants to start building applications with ReactJS.

Starting with NodeJS-HapiJS and ReactJS

What you'll learn

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Course content

Introduction1 lecture • 2min

Setting up development environment1 lecture • 3min

NodeJS-HapiJS sentiment analysis API9 lectures • 1hr 6min

ReactJS Client App for interacting with sentiment analyzer API backend5 lectures • 43min

Requirements

Description

Who this course is for: