[dagw]

Why did they do that? Why not have smaller venvs for separate projects?

What's a 'project'? If you count every throw away data processing script and one off exploratory Jupyter notebook, that can easily be 100 projects. Certainly before uv, having one huge venv or conda environment with 'everything' installed made it much faster and easier to get that sort of work done.

[zelphirkalt]

In what kind of scope are these data processing scripts? In some kind of pipeline used in production I very much would expect them to have reproducible dependencies.

I can understand it for exploratory Jupyter Notebook. But only in the truly exploratory stage. Say for example you are writing a paper. Reproducibility crisis. Exploring is fine, but when it gets to actually writing the paper, one needs to make ones setup reproducible, or lose credibility right away. Most academics are not aware of, or don't know how to, or don't care to, make things reproducible, leading to non-reproducible research.

I would be lying, if I claimed, that I personally always set up a lock file with hashsums for every script. Of course there can be scripts and things we care so little about, that we don't make them reproducible.

[ludwik]

For the (niche) Python library that I co-develop, we use this for demo scripts that live in an example/ directory in our repo. These scripts will never be run in production, but it’s nice to allow users to try them out and get a feel for how the library works before committing to installing dependencies and setting up a virtual environment.

In other words, of course, in most long-term cases, it’s better to create a real project - this is the main uv flow for a reason. But there’s value in being able to easily specify requirements for quick one-off scripts.