Windows at work, always a fresh inconvenience:

#ipython #windows #python

I'm still learning how to submit a patch or pull request to Guix to propose updated definitions of some packages... but---while I figure things out---here's a general guide on how to get new packages installed by defining package variants and rewriting package inputs. In short, the steps to do so are:

1. Get the sha256sum hash in the nix-base-32 format (either via `guix download` or `guix hash` of a repository)
2. Prepare the package variant Scheme file (see images; e.g. "package-variant.scm")
3. Run `guix build -f ./package-variant.scm` to build the new package in the store
4. (Optional, but recommended) Test that things work by running `git shell -f ./package-variant.scm`
5. Install the package by running `guix package -f ./package-variant.scm`

#guix #python #emacs #JupyterNotebook #ipython #sql #package #variants

Curious about #VIM but don't want to install anything?

We've got you covered with two great options: a web-based Vimulator and an embedded #Ipython console in #JupyterLite. Dive in and start exploring VIM today!
https://tessarinseve.pythonanywhere.com/vimulator/index.html

The site has a handful of "synthetic users" that serve to hold items from external sources like #Django debug pages and the #iPython "%pastebin" magic. Their profile pages recently got a little revamp, with a bot icon and more account info.

If you'd like a similar setup for your public dpaste.com integration, drop a line!

* https://dpaste.com/profile/2
* https://dpaste.com/profile/1003

How to best create, maintain and archive custom environments from within Jupyter? .. just updated the documentation for Carto-Lab Docker with examples for Python [1] and R [2].

The tricky part is linking Kernels from custom envs with a Jupyter kernelspec (specifically if the Jupyter server and the Kernel are in two different environments). However, most of this can be stored in Jupyter notebook cells, for reproducibility.

There's also a section on archival of package versions with Conda's `env export` (yml approach) and `conda list --explicit` (full archival).

[1]: https://cartolab.theplink.org/use-cases/#create-your-own-environment-in-a-bind-mount-and-install-the-ipkernel
[2]: https://cartolab.theplink.org/use-cases/#example-create-an-environment-with-a-specific-r-version

#jupyter #R #ipython # #reproducibility #Notebooks #conda

How fast can we get useful feedback on the Python code we write?

https://davidvujic.blogspot.com/2025/04/feedback-loops-in-python.html

#python #IPython #Jupyter #repldrivendevelopment #emacs

Apparently ipython has a special tip if launched today!

#Python #IPython