npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

@cocalc/jupyter

v0.1.2

Published

CoCalc Jupyter -- code to support using Jupyter in cocalc, mainly across all clients

Downloads

4

Readme

@cocalc/jupyter

What this is

Jupyter code in CoCalc. This is used by the frontend, the project and compute.

There is still a lot of Jupyter related code that hasn't been organized yet into this package. It's a refactor-in-progress situation.

Directories

The blobs subdirectory stores large objects, while execute manages code execution. ipynb is for handling ipynb files, and kernel handles kernel enumeration and spawning. nbgrader contains CoCalc's grading tool for Jupyter notebooks, and pool maintains pre-started kernels to reduce waiting time. redux houses actions and stores for Jupyter's notebook doc compatibility. stateless-api implements a stateless code-evaluating API, and util includes miscellaneous Jupyter-related functionalities.

  • blobs: the backend blobstore, where large objects are stored, instead of storing them in the client or sync file.
  • execute: handles execution of code
  • ipynb: handles importing and exporting to the ipynb format. CoCalc uses its own internal jsonlines format.
  • kernel: enumerating and spawning kernels
  • nbgrader: our implementation of nbgrader, especially the backend support
  • pool: manages a pool of prestarted kernels so people often don't have to wait for a kernel to start
  • redux: Redux Actions and Store for jupyter, so we can work with the jupyter notebook doc
  • stateless-api: implements stateless api for evaluating code, which is used e.g., for the share server and in markdown.
  • types: typescript declarations.
  • util: little jupyter related things