181–190 of 401 posts
Like so many other articles that make some offhand remarks about conda, this article raves about a bunch of "new" features that conda has had for years. > Being independent from Python bootstrapping Yep, conda. > Being capable of installing and running Python in one unified congruent way across all situations and platforms. Yep, conda. > Having a very strong dependency resolver. Yep, conda (or mamba). The main thing…
uv is so much better than everything else, I'm just can't afraid they can't keep the team going. Time will tell but I just use uv and ruff in every project now tbh.
the amount of people who switch to R because Python is too hard to setup is crazy high.
Especially among the life scientists and statisticians
The challenge I have with adopting uv is it feels like it doesn't have a great replacement for poetry's `[tool.poetry.scripts]` block. For instance, from a personal project that uses a src layout, without being a package, I have this in my pyproject.toml: [tool.poetry] ... packages = [{ include = "*", from = "src", format = "sdist" }] ... [tool.poetry.scripts] botch = "launcher:run_bot('botch')" beat = "launcher:run_…
[project.scripts]
hello = "example:hello"
Earlier quoted context omitted.
python just didn't have much momentum until relatively recently, despite it's age. There are efforts to speed it up going on now backed by Microsoft. For pypy it's in a weird spot as the things it does fast are the ones you'd usually just offload to a module implemented in C
As a long time Pythonista I was going to push back against your suggestion that Python didn't have much momentum until recently, but then I looked at the historic graph on https://www.tiobe.com/tiobe-index/ and yeah, Python's current huge rise in popularity didn't really get started until around 2018. (TIOBE's methodology is a bit questionable though, as far as I can tell it's almost entirely based on how many search…
With uv, there is now one more.
Now we should just figure out why to stop here. Why not write everything in Rust? Recently I have moved all my projects to Rust from Python and never looked back. Of course we need projects like Torch and we are not yet there, but those simpler projects that do not require GPU libraries Rust is great.
Well, big fan of uv. But... the 86GB python dependency download cache on my primary SSD, most of which can be attributed to the 50 different versions of torch, is testament to the fact that even uv cannot salvage the mess that is pip. Never felt this much rage at the state of a language/build system in the 25 years that I have been programming. And I had to deal with Scala's SBT ("Simple Build Tool") in another life.
Since this seems to be a love fest let me offer a contrarian view. I use conda for environment management and pip for package management. This neatly separates the concerns into two tools that are good at what they do. I'm afraid that uv is another round of "Let's fix everything" just to create another soon to be dead set of patterns. I find nothing innovative or pleasing in its design, nor do I feel that it is parti…
Dozens of threads of people praising how performant and easy uv is, how it builds on standards and current tooling instead of inventing new incompatible set of crap, and every time one comment pops up with “akshually my mix of conda, pyenv, pipx, poetry can already do that in record time of 5 minutes, why do you need uv? Its going to be dead soon”.
Earlier quoted context omitted.
My use of python is somewhat recent. But the two languages that I have used a lot of - Java and JS - have interpreters that were heavily optimized over time. I wonder why that never happened with python and, instead, everyone continues to write their critical code in C/Rust. I am planning to shift some of my stuff to pypy (so a "fast" python exists, kind of). But some dependencies can be problematic, I have heard.
>> My use of python is somewhat recent. But the two languages that I have used a lot of - Java and JS - have interpreters that were heavily optimized over time. I wonder why that never happened with python and, instead, everyone continues to write their critical code in C/Rust. Improving Python performance has been a topic as far back as 2008 when I attended my first PyCon. A quick detour on Python 3 because there is…
Like so many other articles that make some offhand remarks about conda, this article raves about a bunch of "new" features that conda has had for years. > Being independent from Python bootstrapping Yep, conda. > Being capable of installing and running Python in one unified congruent way across all situations and platforms. Yep, conda. > Having a very strong dependency resolver. Yep, conda (or mamba). The main thing…