And all this effort to eek out performance. Get off my lawn etc.
I'm also bullish on using them with Marimo notebooks as a replacement for Jupyter notebooks.
include a bin/run-python wrapper script in your project, and have that set environment variables and call the .venv/bin/python binary. done.
yes, i realise in replying to this comment i'm admitting that i'm part of the problem exactly described, but the "activate" script has caused more confusion in the long run than is worthwhile and the "running from a .venv/" directory could have been a much smaller problem instead of the wind-tunnel it has become.
#!/path/to/your/venv/bin/python
as first the line of your script, done/done
First, one often needs to set PYTHONPATH etc, and this is best done near the point of execution, in a wrapper script and not wangling around in ~/.bash_profile where it gets forgotten, and is not project-specific.
Secondly, and more importantly, your suggestion assumes the venv lives in a fixed location. This is unlikely to be the case.[1] What is preferable is something which is independent of filesystem location. The bin/run-python script is able to find its location on the filesystem, and the location of the venv relative to it.
[1] You might have a custom python distribution with a bunch of modules installed into a well-known location and therefore using that for the python in your application is a reasonable solution, but that is not what we are talking about here.
From the perspective of a user who just wants to install and use something, it doesn't matter why python is atrocious, it just is. Ideally, something like pipx would be far far better than it is, and bundled by default with the system python. Every venv should get added to a launcher that gives access to a shell, an IDE or any python program in the venv. In fact if the python venv module was just a teensy bit better it could (optionally, but by default) do this for you.
Anyway, Python is a nice language for small-ish (< 1000 lines or so) projects. It starts to get very unruly after that and without a type system of any kind your brain becomes the type system... and the compiler. MyPy tries it's best but it really isn't sufficient and requires developer buy-in...hard to get in a language so well designed for throw-away code.
Python 3's syntax is actually quite nice and you can write some very expressive code in it. My opinion, of course, but I also find it to be one of the "lowest common denominator" languages like Go. Python doesn't require much to get started and it's syntax and semantics are relatively easy for even a mediocre programmer to understand. Of course it has a terrible (mostly non-existent ABI) that relies on "consenting adults" as the contract and an awful package system. Yet another reason it's really only practical for (relatively) small projects.
Rarely is anything in Python about raw performance - imo. Of the things that are (NumPy, Pandas, various ML libraries) they call down to C handle most of it. For things that require true parallelism it's not uncommon to see `exec` calls to binaries. That being said in a lot of places (FastAPI based applications, etc) you can get quite a lot of perf out of Python before it becomes a problem.
However, what makes it super nice is how easy it is to hack something together in it. As it turns out most of ML is just hacking things together in a few files or a Jupyter notebook. What a perfect language for such purpose. This is not unlike PERL. I still remember all the random PERL scripts I hacked together for various tasks because it was so simple. It is no wonder it is as popular as it is.
To quote Bjarne Stroustrup there are only two kinds of languages: the ones people complain about and the ones nobody uses :).
You could say that LPython and Shedskin are to Python what Crystal is to Ruby.
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brudgers•10mo ago