I just use Pyenv and pip-tools. Create a requirements.in and Makefile targets to build the requirements.txt based on it. So far I haven't find an sceneario where that combination is detrimental.
Overview of Python dependency management tools
61–70 of 184 posts
Re: Overview of Python dependency management tools
#62pip-tools is almost never mentioned because it's boring but great. I always default to it. https://github.com/jazzband/pip-tools
I came to the comments to say exactly this.
There's a decent summary of why someone might still prefer pip-tools even in a world where pipenv and poetry exist here: https://hynek.me/articles/python-app-deps-2018/
For my purposes, the primary downside of this approach is that adding dependencies takes slightly more effort, because you have to edit a file and then execute a shell command, rather than just executing a shell command. But managing dependencies takes up about 0.001% of my time, so this is not an area where I have much to gain by micro-optimizing my workflow.
I do, on the other hand, have a lot to lose by switching to something that's newer and shinier and less stable.
Re: Overview of Python dependency management tools
#63pip-tools is almost never mentioned because it's boring but great. I always default to it. https://github.com/jazzband/pip-tools
Yes !! I just create a Makefile target and pip-tools is all I need. I create a requirements.in and that is all. So far never feel that has to be more complicated than that. And when I want to upgrade a package I update the requirements.in if I need to and run `make -B` for this:
default: requirements-develop.txt
pip install -r requirements-develop.txt
requirements.txt:
pip-compile -v requirements.in
requirements-develop.txt: requirements.txt
pip-compile -v requirements-develop.in
Re: Overview of Python dependency management tools
#64Serious question: What is the difference between virtual environments and just having several Python installs like:
/home/foo/a/usr/bin/python3
/home/foo/b/usr/bin/python2
I do not recall any isolation issues between those installs, unlike with conda or venv, which are both subtly broken on occasion.
But I dislike opaque automation in general.
Re: Overview of Python dependency management tools
#65People always get up in arms about this, but as someone who has used Python as her daily driver for years it's really... never been this serious of an issue for me? I have used virtualenv/venv and pip to install dependencies for years and years, since I was a teen hacking around with Python. Packaging files with setup.py doesn't really seem that hard. I've published a few packages on pypi for my own personal use and…
To be blunt, maybe you just don't know what you're missing out on? Of course, Python's package management system works and is merely an annoyance to those of us who are used to more modern package managers. By the way, your comment reminded me a of this classic: https://news.ycombinator.com/item?id=9224 :)
Re: Overview of Python dependency management tools
#66Earlier quoted context omitted.
One thing node.js got right is the module resolution logic. Node doesn't even need something like venv since module lookup is always local. Also no problem with dependency hell. Each dependency can have its own private dependencies, even different versions of dependencies shared by sibling modules. Tools like yarn/npm can remove duplicates across a project.
It's a lot more of a pressing concern when you have an average of 1,200 dependencies per project. (I'm actually not sure if it is the average but my anecdotal experience is that it's an order of magnitude higher than python, and 1200 wouldn't be unusual).
That's probably quite accurate for front-end projects which pull in a ton of packages for 1. A compatibility layer wih older browsers. 2. Build tooling.
Node projects tend to have a lot smaller dependency graphs.
Re: Overview of Python dependency management tools
#67Earlier quoted context omitted.
> does Python require you to download an entire package just to determine its dependencies? yes - the standard way of defining dependencies in Python is in setup.py, which has to be invoked as a Python script in order to work. this script may also need to read files from the rest of the project, so you do indeed need to download the whole package to determine its dependencies. even if the Python community were to agr…
It seems that this information should cacheable after an invocation of setup.py, at least for an installation without any extras. And even with extras requested, perhaps. Or is there any even greater hidden challenge from using setup.py?
setup.py can check the OS and pick necessary requirements. so it can have different dependencies in different OSes.
I've used it like this - https://github.com/JaDogg/pydoro/blob/b1b3de38ac15b9254ef1be...
Re: Overview of Python dependency management tools
#68People always get up in arms about this, but as someone who has used Python as her daily driver for years it's really... never been this serious of an issue for me? I have used virtualenv/venv and pip to install dependencies for years and years, since I was a teen hacking around with Python. Packaging files with setup.py doesn't really seem that hard. I've published a few packages on pypi for my own personal use and…
I don't think your experience is atypical but I do think your acceptance of something that is quite awful is fairly atypical.
It's also possible that you use Python on Linux, where it is at least tolerable. Try again on Windows.
Re: Overview of Python dependency management tools
#69Serious question: What is the difference between virtual environments and just having several Python installs like: /home/foo/a/usr/bin/python3 /home/foo/b/usr/bin/python2 Python is so fast to compile and install that I just install as many throwaway Pythons as needed. I do not recall any isolation issues between those installs, unlike with conda or venv, which are both subtly broken on occasion. But I dislike opaque…
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Re: Overview of Python dependency management tools
#70People always get up in arms about this, but as someone who has used Python as her daily driver for years it's really... never been this serious of an issue for me? I have used virtualenv/venv and pip to install dependencies for years and years, since I was a teen hacking around with Python. Packaging files with setup.py doesn't really seem that hard. I've published a few packages on pypi for my own personal use and…
To be blunt, maybe you just don't know what you're missing out on? Of course, Python's package management system works and is merely an annoyance to those of us who are used to more modern package managers. By the way, your comment reminded me a of this classic: https://news.ycombinator.com/item?id=9224 :)
I mean, possibly? What's considered the gold standard in package management these days?
I use yarn for managing javascript dependencies and do a lot of work with Cargo too. The community seems to love both these tools outside of slow compile and install times.