[HN Gopher] Jupyter Collaboration has a history slider
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Jupyter Collaboration has a history slider
Author : fghorow
Score : 53 points
Date : 2025-10-13 00:50 UTC (6 days ago)
(HTM) web link (blog.jupyter.org)
(TXT) w3m dump (blog.jupyter.org)
| fghorow wrote:
| This Jupyter (CRDT-based) extension appears to solve the BIGGEST
| HEADACHE I personally have with Jupyter(lab). Jupyter notebooks
| allow me to hack code/parameters too fluently, and I can't
| recover earlier positions in code/parameter space that produced
| interesting results.
|
| Jupytext and git goes some way towards fixing that, but I don't
| save to git after every cut/paste of a parameter. This extension
| is effortless.
|
| As a bonus, the extension appears to allow SubEthaEdit/GoogleDocs
| style collaboration too. (I haven't personally used that yet.)
|
| Check it out.
| cnees wrote:
| Both collaboration and history are killer features. I'm going to
| have to try this out at work!
| shevy-java wrote:
| Jupyter is really dominating now at university campus sites. I
| see it used for almost every course (at the least those that
| require data analysis via python).
| Almondsetat wrote:
| And rightfully so. It's an interactive programming environment
| with embedded explanations. Between markdown and latex, you can
| write an entire class inside it. It's perfect for live
| demostrations and homework. Bloated as hell? Sure, but a huge
| step in education IMHO
| reubenmorais wrote:
| Maybe rather an interactive explanation and exploration
| environment with embedded programming?
| jcgl wrote:
| Like a more specialized, accessible, and graphical Org mode.
| heresie-dabord wrote:
| > it integrates seamlessly with JupyterCAD, JupyterLab's
| extension for creating and manipulating 3D models.
|
| Today I learned... Jupyter has an extension for 3d modelling.
|
| Can anyone comment on this extension?
|
| https://github.com/jupytercad/JupyterCAD
| doubleg72 wrote:
| Wow that is very interesting, I cannot comment but im
| definitely going to be checking it out today.
| plipt wrote:
| I haven't used Jupyter in a few years. Wondering what is the
| current standard practice of starting a new Jupyter project.
|
| Do users typically have one system-wide Jupyter install that
| gets reused for each data analysis project that then have their
| own dependencies in a virtual environment that Jupyter
| activates?
|
| Or is Jupyter installed inside each project's virtual
| environment?
| porridgeraisin wrote:
| ipykernel (jupyter basically) is installed in the virtual
| environment itself, especially since sometimes different envs
| are different python versions.
| morkalork wrote:
| I'm definitely guilty of This system-wide install but I've
| noticed people doing per-project installs more often now and
| I'm trying to get in the habit.
| epistasis wrote:
| Typically one Jupyter install system wide, and then multiple
| kernels with each environment.
|
| Personally, I really like the juv model where dependencies
| are taken from the first cell of the notebook and a new
| kernel is created to launch the interface, but I haven't seen
| others using it much yet:
|
| https://github.com/manzt/juv
| heisenzombie wrote:
| The idea is good, but juv is a one-jupyter-per-notebook
| model which isn't very practical for how my team uses
| jupyter. My attempt at "juv, but systemwide-jupyter-plus-
| one-kernel-per-notebook model" is this:
| https://github.com/tobinjones/uvkernel
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(page generated 2025-10-19 23:01 UTC)