Python developer here. Venv is good, venv is life. Every single project I create starts with

python3 -m venv venv

source venv/bin/activate

pip3 install {everything I need}

pip3 freeze > requirements.txt

Now write code!

Don’t forget to update your requirements.txt using pip3 freeze again anytime you add a new library with pip.

If you installed a lot of packages before starting to develop with virtual environments, some libraries will be in your OS python install and won’t be reflected in pip freeze and won’t get into your venv. This is the root of all evil. First of all, don’t do that. Second, you can force libraries to install into your venv despite them also being in your system by installing like so:

pip3 install --ignore-installed mypackage

If you don’t change between Linux and windows most libraries will just work between systems, but if you have problems on another system, just recreate the whole venv structure

rm -rf venv (…make a new venv, activate it) pip3 install -r requirements.txt

Once you get the hang of this you can make Python behave without a lot of hassle.

This is a case where a strength can also be a weakness.

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.

Yes it’s terrible. The only hope on the horizon is uv. It’s significantly better than all the other tooling (Poetry, pip, pipenv, etc.) so I think it has a good chance of reducing the options to just Pip or uv at least.

But I fully expect the Python Devs to ignore it, and maybe even make life deliberately difficult for it like they did for static analysers. They have some strange priorities sometimes.

The venv stuff is pretty annoying, I agree.

How to improve Python packaging, or why fourteen tools are at least twelve too many

Still relevant.

Yep, they are not portable, every app should come bundled with its own interpreter. As to why, I think historically it didn’t target production grade application development.

I’m not sure this can be really fixed with Python 3, maybe we just have to hope for Python 4

I’ve started using poetry and the experience has improved.

The reason you do stuff in a venv is to isolate that environment from other python projects on your system, so one Python project doesn’t break another. I use Docker for similar reasons for a lot of non-Python projects.

A lot of Python projects involve specific versions of libraries, because things break. I’ve had similar issues with non-Python projects. I’m not sure I’d say Python is particularly worse about it.

There are tools in place that can make the sharing of Python projects incredibly easy and portable and consistent, but I only ever see the best maintained projects using them unfortunately.

Python is hacky, because it hacks. There’s a bunch of ways you can do anything. You can run it on numerous platforms, or even on web assembly. It’s not maintained centrally. Each “app” you find is just somebodies hack project they’re sharing with you for fun.

Docker might be solution here.

But from my experience most python scripts are absolute junk. The barrier for entry is low so there’s a massive disparity in quality.

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.

Anti Commercial-AI license

everyone focuses on the tooling, not many are focusing on the reason: python is extremely dynamic. like, magic dynamic you can modify a module halfway through an import, you can replace class attributes and automatically propagate to instances, you can decompile the bytecode while it’s running.

combine this with the fact that it’s installed by default and used basically everywhere and you get an environment that needs to be carefully managed for the sake of the system.

js has this packaging system down pat, but it has the advantage that it got mainstream in a sandboxed isolated environment before it started leaking out into the system. python was in there from the beginning, and every change breaks someone’s workflow.

the closest language to look at for packaging is probably lua, which has similar issues. however since lua is usually not a standalone application platform it’s not a big deal there.

With all the hype surrounding Python it’s easy to forget that it’s a really old language. And, in my opinion, the leadership is a bit of a mess so there hasn’t been any concerted effort on standardizing tooling.

Some unsolicited advice from somebody who is used more refined build environments but is doing a lot of Python these days:

The whole venv thing isn’t too bad once you get the hang of it. But be prepared for people to tell you that you’re using the wrong venv for reasons you’ll never quit understand or likely need to care about. Just use the bundled “python -m venv venv” and you’ll be fine despite other “better” alternatives. It’s bundled so it’s always available to you. And feel free to just drop/recreate your venv whenever you like or need. They’re ephemeral and pretty large once you’ve installed a lot of things.

Use “pipx” to install python applications you want to use as programs rather than libraries. It creates and manages venvs for them so you don’t get library conflicts. Something like “pip-tools” for example (pipx install pip-tools).

Use “pyenv” to manage installed python versions - it’s a bit like “sdkman” for the JVM ecosystem and makes it easy to deal with the “specific versions of python” stuff.

For dependencies for an app - I just create a requirements.txt and “pip install -r requirements.txt” for the most part… Though I should use one of the 80 better ways to do it because they can help with updating versions automatically. Those tools mostly also just spit out a requirements.txt in the end so it’s pretty easy to migrate to them. pip-tools is what my team is moving towards and it seems a reasonable option. YMMV.

Yeah the tooling sucks. The only tooling I’ve liked is Poetry, I never have trouble installing or packaging the apps that use it.