Name: nodebook-code-pattern
Owner: International Business Machines
Description: Run Node.js code in Python notebooks
Created: 2018-02-06 22:49:52.0
Updated: 2018-05-24 00:43:43.0
Pushed: 2018-05-24 00:37:01.0
Size: 3797
Language: Jupyter Notebook
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Notebooks are where data scientists process, analyse, and visualise 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. To learn more follow the setup steps and explore the getting started notebook or click on the sample image below to preview the output.
You can run Node.js code in Watson Studio or your local environment:
To preview an example notebook without going through a setup follow this link.
A runtime environment in Watson Studio (IBM's Data Science platform) is defined by its hardware and software configuration. By default, Node.js is not installed in runtime environments and you therefore need to create a custom runtime environment definition. [[Learn more about environments…]](https://dataplatform.ibm.com/docs/content/analyze-data/notebook-environments.html)
Open Watson Studio in your web browser. Sign up for a free account if necessary.
Create a project. [[Learn more about projects…]](https://dataplatform.ibm.com/docs/content/manage-data/manage-projects.html)
In this project, open the Environments tab. A list of existing environment definitions for Python and R is displayed.
Create a new environment definition.
Assign a name to the new environment definition, such as Python 2 with Node.js.
Enter a brief environment description.
Choose the desired hardware configuration, such as a minimalist free setup (which is sufficient for demonstration purposes).
Select Python 2 as software version. (Python 3 is currently not supported by pixiedust_node.)
Save the environment definition.
Customize the software definition.
Add the nodejs conda package dependency, as shown below:
lease add conda channels here
nnels:
efaults
lease add conda packages here
endencies:
odejs
lease add pip packages here
o add pip packages, please comment out the next line
pip:
Save the environment definition. It should look as follows:
You can now associate notebooks with this environment definition and run Node.js in the code cells, as illustrated in the getting started notebook.
Note: An environment definition is only available within the project that it was defined in.
The getting started notebook outlines how to
In the project you've created, add a new notebook from URL:
Enter any notebook name.
Specify remote URL https://raw.githubusercontent.com/IBM/nodebook-code-pattern/master/notebooks/nodebook_1.ipynb as source.
Select the custom runtime environment Python 2 with Node.js. you've created earlier.
Follow the notebook instructions.
You should be able to run all cells without making any changes.
To get started with nodebooks you'll need a local installation of
To access the samples, clone this repository and launch a Jupyter server on your local machine.
it clone https://github.com/IBM/nodebook-code-pattern.git
d nodebook-code-pattern
upyter notebook notebooks/
Open nodebook_1 to learn more about
No notebook changes should be required to complete all steps.
Some of the nodebook code pattern examples access a read-only Cloudant database for illustrative purposes. If you prefer you can create your own copy of this database by replicating from remote database URL https://56953ed8-3fba-4f7e-824e-5498c8e1d18e-bluemix.cloudant.com/cities. [Learn more about database replication…]
Open this link to preview the completed notebook.