• Stars
    star
    287
  • Rank 144,232 (Top 3 %)
  • Language
    HTML
  • License
    MIT License
  • Created over 8 years ago
  • Updated over 1 year ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Client side rendering of Jupyter notebooks

client side rendering of jupyter notebooks

tl;dr: Render Jupyter notebooks straight in the browser, without a back end converter. Can be used as a library. Or if you're on macOS, you can even fire it up in Quick Look, see ipynb-quicklook.

I often want to read through my Jupyter notebooks, but I rarely have my Jupyter instances running in the right folders. I can't quite use the online nbviewer, because I don't have a public URL for these, so I resort to running dummy Jupyter instances or uploading my file as a one-time gist on Github (one I have to delete thereafter). One last possibility is nbconvert in the command line.

I thought it could be easier and more lightweight. So I hacked together this client side rendering of Jupyter notebooks. All you need is a browser that renders an HTML file (dependent on some JavaScript and CSS, both of which can be inlined). You simply drag and drop an .ipynb file and it renders. It's rather fast and it supports most notebook features. I tried supporting the previous version (v3), since there are tons of examples in this version out there.

Try a live demo

NEW: Rendering Github notebooks

You can now render notebooks hosted on Github. You can copy and paste their URL in the viewer, linked above, or you can save this following link as a bookmark:

javascript:(function(){location.href="https://kokes.github.io/nbviewer.js/viewer.html#"+btoa(location.href);})();

Clicking this while on Github, looking at a notebook, will launch our nbviewer with this notebook rendered here instead. You'll also get a permanent link for you to share.

Usage

There are two ways one can use this. You can use the library itself, there is just a single public method, you call nbv.render(data, target), where data is the JSON representation of your Jupyter notebook and target is the node where the notebook is to be rendered.

Or you can use the demo (or a local copy), which is just a simple wrapper of the library, with dropzones and other basic features. There is no data being transferred anywhere, so feel free to bookmark it and use it.

Tech details

It's rather simple at this point, all the DOM manipulation is written in vanilla JavaScript, Markdown rendering goes through marked.js, syntax highlighting is administered by Prism.js. The example implementation leverages a few goodies from modern web design, like File API or drag&drops, so a fairly modern browser is necessary.

Showcase

screencast

Contact

Drop me an email ([email protected]) or tweet at me (@pndrej) if you have any questions or suggestions. Contributions welcome.