INinfinite8s·Jan 15, 2021
The original author of Phosphor decided to stop working on it, so JupyterLab forked it into Lumino - https://github.com/jupyterlab/lumino
In JupyterLab 3.0jupyterlab
lumino
TypeScript2020–2021
jupyterlab / lumino
lumino
Lumino is a library for building interactive web applications
2Distinct people
2Mentions
0Explicit recommenders
765GitHub stars
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What it is
Lumino is a library for building interactive web applications
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Where it is used
No documented product use has been verified yet.
What people are saying
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by week2 dated mentions
Observed mentions: 2020-08-04 12:46:15 UTC to 2021-01-15 22:24:09 UTC. Weeks start Monday, UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Aug 3 | 2020-08-03 00:00:00 UTC | 2020-08-10 00:00:00 UTC | 1 | 0 | 1 |
| Aug 10 | 2020-08-10 00:00:00 UTC | 2020-08-17 00:00:00 UTC | 0 | 0 | 0 |
| Aug 17 | 2020-08-17 00:00:00 UTC | 2020-08-24 00:00:00 UTC | 0 | 0 | 0 |
| Aug 24 | 2020-08-24 00:00:00 UTC | 2020-08-31 00:00:00 UTC | 0 | 0 | 0 |
| Aug 31 | 2020-08-31 00:00:00 UTC | 2020-09-07 00:00:00 UTC | 0 | 0 | 0 |
| Sep 7 | 2020-09-07 00:00:00 UTC | 2020-09-14 00:00:00 UTC | 0 | 0 | 0 |
| Sep 14 | 2020-09-14 00:00:00 UTC | 2020-09-21 00:00:00 UTC | 0 | 0 | 0 |
| Sep 21 | 2020-09-21 00:00:00 UTC | 2020-09-28 00:00:00 UTC | 0 | 0 | 0 |
| Sep 28 | 2020-09-28 00:00:00 UTC | 2020-10-05 00:00:00 UTC | 0 | 0 | 0 |
| Oct 5 | 2020-10-05 00:00:00 UTC | 2020-10-12 00:00:00 UTC | 0 | 0 | 0 |
| Oct 12 | 2020-10-12 00:00:00 UTC | 2020-10-19 00:00:00 UTC | 0 | 0 | 0 |
| Oct 19 | 2020-10-19 00:00:00 UTC | 2020-10-26 00:00:00 UTC | 0 | 0 | 0 |
| Oct 26 | 2020-10-26 00:00:00 UTC | 2020-11-02 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2 | 2020-11-02 00:00:00 UTC | 2020-11-09 00:00:00 UTC | 0 | 0 | 0 |
| Nov 9 | 2020-11-09 00:00:00 UTC | 2020-11-16 00:00:00 UTC | 0 | 0 | 0 |
| Nov 16 | 2020-11-16 00:00:00 UTC | 2020-11-23 00:00:00 UTC | 0 | 0 | 0 |
| Nov 23 | 2020-11-23 00:00:00 UTC | 2020-11-30 00:00:00 UTC | 0 | 0 | 0 |
| Nov 30 | 2020-11-30 00:00:00 UTC | 2020-12-07 00:00:00 UTC | 0 | 0 | 0 |
| Dec 7 | 2020-12-07 00:00:00 UTC | 2020-12-14 00:00:00 UTC | 0 | 0 | 0 |
| Dec 14 | 2020-12-14 00:00:00 UTC | 2020-12-21 00:00:00 UTC | 0 | 0 | 0 |
| Dec 21 | 2020-12-21 00:00:00 UTC | 2020-12-28 00:00:00 UTC | 0 | 0 | 0 |
| Dec 28 | 2020-12-28 00:00:00 UTC | 2021-01-04 00:00:00 UTC | 0 | 0 | 0 |
| Jan 4 | 2021-01-04 00:00:00 UTC | 2021-01-11 00:00:00 UTC | 0 | 0 | 0 |
| Jan 11 | 2021-01-11 00:00:00 UTC | 2021-01-18 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
2 sources> Cell-by-cell notebooks like Jupyter are great for prototyping, explaining and exploration, but their dependence on a Python server (with often undocumented dependencies) limits their ability to be shared and remixed. Now that browsers support dynamic imports, it has become possible to create a similar workflow entirely in the browser.
Pretty cool. As someone involved in building a machine learning platform which also allows users to leverage Jupyter notebooks, I feel your pain. We had to add many features to make working on non trivial projects more feasible. For example near-real-time collaboration so people could pair-program on one notebook.
One other problem you mention is the kernel in the backend. The problem with that is often found in issues where a user launches a long-running notebook, closes their tab/browser. The computation
Read the rest
happens but the results don't find their way, which means users must have code for side effects and artifacts in the notebook.
We've added a functionality to run notebooks asynchronously to address that problem, which also addresses the problem of multiple users competing for limited resources (tragedy of the commons) and kernels dying. Now users can run their notebooks asynchronously: they're scheduled, run, and saved seamlessly.
Jupyter is a useful tool which has these problems that aren't trivial to solve. For example, for the near-real-time collaboration, the Jupyter team is revamping their API with Lumino (https://github.com/jupyterlab/lumino), which was PhosphorJS but the development stopped when the main contributor had retired.