PixieDust extension that enable a Jupyter Notebook user to invoke Node.js commands.
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.
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.
Inside your Jupyter notebook, install pixiedust_node with
!pip install pixiedust_nodeOnce installed, a notebook can start up pixiedust_node with:
import pixiedust_nodeUse the %%node prefix in a notebook cell to indicate that the content that follows is JavaScript.
%%node
print(new Date());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.uninstall('packagename')- to remove an npm module (ornpm.remove('packagename'))npm.list()- to list the installed modules
Node.js functions are available to interact with the Notebook
print(x)- print out the value of variable xdisplay(x)- use Pixiedust'sdisplayfunction to visualise an array of datastore(x,'y')- turn a JavaScript array x into a Pandas data frame and store in Python variable yhtml(x)- render HTML string x in a notebook cellimage(x)- render image URL x in a notebook cellhelp()- show help
%%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);%%node
// fetch cities called York
cities.query({name: 'York'}).then(display);** This function is deprecated as Node.js global variables are copied to the Python environment automatically **
%%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()%%node
var str = 'Sales are up <b>25%</b>';
html(str);%%node
var url = 'http://myserver.com/path/to/image.jpg';
image(url);%%node
help();Any global variables that you create in your %%node cells will be automatically copied to equivalent variables in Python. e.g if you create some variables in a Node.js cell:
%%node
var str = "hello world";
var n1 = 4.1515;
var n2 = 42;
var tf = true;
var obj = { name:"Frank", age: 42 };
var array_of_strings = ["hello", "world"];
var array_of_objects = [{a:1,b:2}, {a:3, b:4}];
Then these variables can be used in Python:
# Python cell
print str, n1, n2, tf
print obj
print array_of_strings
print array_of_objects
Strings, numbers, booleans and arrays of such are converted to their equivalent in Python. Objects are converted into Python dictionaries and arrays of objects are automatically converted into a Pandas DataFrames.
Note that only variables declared with var are moved to Python, not constants declared with const.
If you want to move data from an asynchronous Node.js callback, remember to write it to a global variable:
%%node
var googlehomepage = '';
request.get('http://www.google.com').then(function(data) {
googlehomepage = data;
print('Fetched Google homepage');
});Similarly, Python variables of type str, int, float, bool, unicode, dict or list will be moved to Node.js when a cell is executed:
# Python cell
a = 'hello'
b = 2
b = 3
c= False
d = {}
d["x"] = 1
d["y"] = 2
e = 3.142
The variables can then be used in Node.js:
%%node
console.log(a,b,c,d,e);
// hello 3 false { y: 2, x: 1 } 3.142
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()You can view the help in a Python cell:
node.help()
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent