pixiedust_node

PixieDust extension that enable a Jupyter Notebook user to invoke Node.js commands.

How it works

The pixiedust_node Python module has access to Pixiedust's display API to render charts and maps. When pixiedust_node is imported into a notebook, a Node.js sub-process is setup and the notebook is configured so that cells beginning with '%%node' may contain JavaScript code: that code is piped to the Node.js sub-process automatically. The output of the Node.js process is parsed by pixiedust_node to handle the use of functions display/print/store/html/image. The pixiedust_node module also allows npm installs to be initiated from within the notebook. This achieved with further npm sub-processes whose output appears in the notebook.

Prerequisites

To use pixiedust_node you need to be running a Jupyter notebooks with the Pixedust extension installed. Notebooks can be run locally by installing Pixiedust and its prerequisites.

You also need Node.js/npm installed. See the Node.js downloads page to find an installer for your platform.

Installation

Inside your Jupyter notebook, install pixiedust_node with

!pip install pixiedust_node

Running

Once installed, a notebook can start up pixiedust_node with:

import pixiedust_node

Using %%node

Use the %%node prefix in a notebook cell to indicate that the content that follows is JavaScript.

%%node
print(new Date());

Installing npm modules

You can install any npm module to use in your Node.js code from your notebook. To install npm modules, in a Python cell:

npm.install('silverlining')

or install multiple libraries in one go:

npm.install( ('request', 'request-promise') )

and then "require" the modules in your Node.js code.

%%node
var silverlining = require('silverlining');
var request = require('request-promise');

You may also do :

• npm.remove('packagename') - to remove an npm module
• npm.list() - to list the installed modules

Node.js helper functions

Node.js functions are available to interact with the Notebook

• print(x) - print out the value of variable x
• display(x) - use Pixiedust's display function to visualise an array of data
• store(x,'y') - turn a JavaScript array x into a Pandas data frame and store in Python variable y
• html(x) - render HTML string x in a notebook cell
• image(x) - render image URL x in a notebook cell
• help() - show help

print

%%node
// connect to Cloudant using Silverlining
var url = 'https://reader.cloudant.com/cities';
var cities = silverlining(url);

// fetch number of cities per country
cities.count('country').then(print);

display

%%node

// fetch cities called York
cities.query({name: 'York'}).then(display);

store

%%node

// fetch the data and store in Pandas dataframe called 'x'
cities.all({limit: 2500}).then(function(data) {
  store(data, 'x');
});

The dataframe 'x' is now available to use in a Python cell:

x['population'].sum()

html

%%node
var str = 'Sales are up <b>25%</b>';
html(str);

js

%%node
var url = 'http://myserver.com/path/to/image.jpg';
image(url);

help

%%node
help();

Managing the Node.js process

If enter some invalid syntax into a %%node cell, such as code with more opening brackets than closing brackes, then the Node.js interpreter may not think you have finished typing and you receive no output.

You can cancel execution by running the following command in a Python cell:

node.cancel()

If you need to clear your Node.js variables and restart from the beginning then issue the following command in an Python cell:

node.clear()

Help

You can view the help in a Python cell:

node.help()