Python's packaging is not great. Pip and venvs help but, it's lightyears behind anything you're used to. My go-to is using a venv for everything.
It's something of a "14 competing standards" situation, but uv seems to be the nerd favourite these days.
I still do the python3 -m venv venv && source venv/bin/activate
How can uv help me be a better person?
pyproject.toml track the dependencies and dev-dependencies you actually care aboutuv.lock file that contains each and every lib that's needed.uv sync and uv run <application> is pretty much all you need to get goingPython is the only programming language that has forced me to question what the difference is between an egg and a wheel.
You re not stupid, python's packaging & versionning is PITA. as long as you write it for yourself, you re good. As soon as you want to share it, you have a problem
as long as you write it for yourself, you re good. As soon as you want to share it, you have a problem
A perfect summary of the history of computer code!
No, it's not just you, Python's tooling is a mess. It's not necessarily anyone's fault, but there are a ton of options and a lot of very similarly named things that accomplish different (but sometimes similar) tasks. (pyenv, venv, and virtualenv come to mind.) As someone who considers themselves between beginner and intermediate proficiency in Python, this is my biggest hurdle right now.
Python’s tooling is a mess.
Not only that. It's a historic mess. Over the years, growing a better and better toolset left a lot of projects in a very messy state. So many answers on Stack Overflow that mention easy_install - I still don't know what it is, but I guess it was some kind of proto uv.
Every time I'm doing anything with Python I ask myself if Java's tooling is this complicated or I'm just used to it by now. I think a big part of the weirdness is that a lot of Python tooling is tied to the Python installation whereas in Java things like Maven and Gradle are separate. In addition, I think dependencies you install get tied to that Python installation, while in Java they just are in a cache for Maven/Gradle. And in the horrible scenario where you need to use different versions of Maven/Gradle (one place I was at specifically needed Maven 3.0.3 for one project and a different for a different, don't ask, it's dumb and their own fault for setting it up that way) at least they still have one common cache for everything.
I guess it also helps that with Java you (often) don't need platform specific jar files. But Python is often used as an easy and dynamic scripting interface over more performant, native code. So you don't really run into things like "this artifact doesn't have a 64 bit arm version for python 2" often with Java. But that's not a fault of Python's tooling, it's just the reality of how it's used.
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.
I like the idea of uv, but I hate the name. Libuv is already a very popular C library, and used in everything from NodeJS to Julia to Python (through the popular uvloop module). Every time I see someone mention uv I get confused and think they're talking about uvloop until I remember the Astral project, and then reconfirm to myself how much I disapprove of their name choice.
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.
pip3 freeze > requirements.txt
I hate this. Because now I have a list of your dependencies, but also the dependencies of the dependencies, and I now have regular dependencies and dev-dependencies mixed up. If I'm new to Python I would have NO idea which libraries would be the important ones because it's a jumbled mess.
I've come to love uv (coming from poetry, coming from pip with a requirements/base.txt and requirements/dev.txt - gotta keep regular dependencies and dev-dependencies separate).
uv sync
uv run <application>
That's it. I don't even need to install a compatible Python version, as uv takes care of that for me. It'll automatically create a local .venv/, and it's blazingly fast.
Okay, now give me those steps but what to do if I clone an already existing repo please
The git repo should ignore the venv folder, so when you clone you then create a new one and activate it with those steps.
Then when you are installing requirements with pip, the repo you cloned will likely have a requirements.txt file in it, so you 'pip install -r requirements.txt'
You have been in lala land for too long. That list of things to do is insane. Venv is possibly one of the worst solutions around, but many Python devs are incapable of seeing how bad it is. Just for comparison, so you can understand, in Ruby literally everything you did is covered by one command bundle. On every system.
OP sounds like a victim of Python 3, finding various Python 2 projects on the internet, a venv isn't going to help
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.
Python never had much of a central design team. People mostly just scratched their own itch, so you get lots of different tools that do only a small part each, and aren't necessarily compatible.
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.
Python is the new Perl
After using python, I'm of the opinion that perl was much cleaner.
Nothing comes close to Perl’s abuse of global variables. Oh you called this function? Take a guess which global variables it will use.
I agree. Python is my language of choice 80% or so of the time.
But my god, it does packaging badly! Especially if it's dependent on linking to compiled code!
Why it is like that, I couldn't tell. The language is older than git, so that might be part of it.
However, you're installing python libraries from github? I very very rarely have to do that. In what context do you have to do that regularly?
I've started using poetry and the experience has improved.
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.
This is exactly how I feel about python as well... IMHO, it's good for some advanced stuff, where bash starts to hit its limits, but I'd never touch it otherwise
I'm no Python expert either and yeah, from an outsider's perspective it seems needlessly confusing. easy_install that's never been easy, pip that should absolutely be put on a Performance Improvement Plan, and now this venv nonsense.
You can criticize javascript's ridiculous dependencies all you want (left-pad?), but one thing that they absolutely got right is how to manage them. Everything's in node_modules and that's it. Yeah, you might get eleven copies of left-pad on your system, but you know what you NEVER get? Version conflicts between projects you're working on.
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.
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.
Python is truly a mess when Docker is considered a solution.
It... depends. There is some great tooling for Python -- this was less true only a few years ago, mind you -- but the landscape is very much in flux, and usage of the modern stuff is not yet widespread. And a lot of the legacy stuff has a whole host of pitfalls.
Things are broadly progressing in the right direction, and I'd say I'm cautiously optimistic, although if you have to deal with anything related to conda then for the time being: good luck, and sorry.
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