Welcome to the main community in programming.dev! Feel free to post anything relating to programming here!
Cross posting is strongly encouraged in the instance. If you feel your post or another person's post makes sense in another community cross post into it.
Hope you enjoy the instance!
Rules
Follow the wormhole through a path of communities [email protected]
Just out of curiosity, I haven't seen anyone recommend miniconda... Why so, is there something wrong I'm not aware of?
I'm no expert, but I totally feel you, python packages, dependencies and version matching is a real nightmare. Even with venv I had a hard time to make everything work flawlessly, especially on MacOS.
However, with miniconda everything was way easier to configure and worked as expected.
Difficult? How so? I find compiling C and C++ stuff much more difficult than anything python. It never works on the first try whereas with python the chances are much much higher.
What's is so difficult to understand about virtual envs? You have global python packages, you can also have per user python packages, and you can create virtual environments to install packages into. Why do people struggle to understand this?
The global packages are found thanks to default locations, which can be overridden with environment variables. Virtual environments set those environment variables to be able to point to different locations.
python -m venv .venv/ means python will execute the module venv and tell it to create a virtual environment in the .venv folder in the current directory. As mentioned above, the environment variables have to be set to actually use it. That's when source .venv/bin/activate comes into play (there are other scripts for zsh and fish).
Now you can run pip install $package and then run the package's command if it has one.
It's that simple. If you want to, you can make it difficult by doing sudo pip install $package and fucking up your global packages by possibly updating a dependency of another package - just like the equivalent of updating glibc from 1.2 to 1.3 and breaking every application depending on 1.2 because glibc doesn't fucking follow goddamn semver.
As for old versions of python, bro give me a break. There's pyenv for that if whatever old ass package you're installing depends on an ancient 10 year old python version. You really think building a C++ package from 10 years ago will work more smoothly than python? Have fun tracking down all the unlocked dependency versions that "Worked On My Machine 🏧" at the start of the century.
The only python packages I have installing are those with C/C++ dependencies which have to be compiled at install time.
Y'all have got to be meme'ing.
This isn’t the answer you want, but Go(lang) is super easy to learn and has a ton of speed on python. Yes, it’s more difficult, but once you understand it, it’s got a lot going for it.