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Patrick Titzler edited this page May 24, 2018 · 11 revisions

Short Name

Run Node.js code in Jupyter notebooks

Short Description

Exploit the power of Node.js in Jupyter notebooks using pixiedust_node, an open source Python library.

Offering Type

Cognitive & Data Analytics

Introduction

Notebooks are where data scientists process, analyze, and visualize data in an iterative, collaborative environment. They typically run environments for languages like Python, R, and Scala. For years, data science notebooks have served academics and research scientists as a scratchpad for writing code, refining algorithms, and sharing and proving their work. Today, it's a workflow that lends itself well to web developers experimenting with data sets in Node.js.

To that end, pixiedust_node is an add-on for Jupyter notebooks that allows Node.js/JavaScript to run inside notebook cells. Not only can web developers use the same workflow for collaborating in Node.js, but they can also use the same tools to work with existing data scientists working in Python.

Author

by Patrick Titzler

Code

Demo

N/A

Video

N/A

Overview

This Jupyter notebook outlines how to run Node.js code in Watson Studio or a local environment using the pixiedust_node library. By following the getting started instructions you will learn how to

  • use variables, functions, and promises,
  • work with remote data sources, such as Apache CouchDB (or its managed sibling Cloudant),
  • visualize data, and
  • share data between Python and Node.js.

Flow

architecture

  1. Install Node.js in target environment (Watson Studio or a local machine)
  2. Open the getting started with Node.js notebook in target environment
  3. Run Node.js code cells

Included Components

  • Watson Studio: Analyze data using RStudio, Jupyter, and Python in a configured, collaborative environment that includes IBM value-adds, such as managed Spark.

Featured Technologies

  • Jupyter Notebooks: An open-source web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text.

  • PixieDust Open source toolkit library for Jupyter notebooks

  • pixiedust_node Open source Python package, providing support for Javascript/Node.js code

Links

This code pattern is based on a series of blog posts that were first published by Glynn Bird on medium.com.

Blog

https://medium.com/ibm-watson-data-lab/running-node-js-notebooks-in-watson-studio-a8f6545d8299

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