I've alwyas used conda since I use the scipy stack. Can anyone clue me in if I can instead use pipenv and it will download all the requisite binaries etc. ?
Overview of Python dependency management tools
151–160 of 184 posts
Re: Overview of Python dependency management tools
#152The missing ingredient to really, REALLY solve these problems once and for all is an authoritative decision to switch package formats and run the whole dependency resolution stack by the core python language contributor team. I get backwards compatibility and open-source governance and bla-bla, but the reality is that this cannot be done by a third-party library author and needs to become part of the core stack, incl…
While npm comes with node, and bundler comes with Ruby, the governance of these projects/tools are separate from the language.
Yet someone has made the decision to do bundle them with the language and provide a default. I'm not suggesting we have common governance, but these decisions need to be made.
Re: Overview of Python dependency management tools
#153The missing ingredient to really, REALLY solve these problems once and for all is an authoritative decision to switch package formats and run the whole dependency resolution stack by the core python language contributor team. I get backwards compatibility and open-source governance and bla-bla, but the reality is that this cannot be done by a third-party library author and needs to become part of the core stack, incl…
The default is pip + python3 -m venv.
Then I guess they are not good enough?! I use them (without other tools) and I'm happy, but do fairly simple python development. There's a reason many people choose other tools if these don't cover common cases.
Re: Overview of Python dependency management tools
#154Earlier quoted context omitted.
This sort of attitude is the reason why the world doesn't move away from awful solutions. It is a testament to the lack of ability to see beyond your own nose. A lot of people who use Python, don't have the luxury of it being their "daily driver for years", so the conflicting documentation, decision paralysis and other problems that come with it end up being a huge time sink. A lot of non-programmers are being forced…
You're right of course. Still, it's worth keeping in mind that Rust was born 20 years after Python was. Python was being written before Mosaic, Netscape, and Yahoo! were around. I think it can be forgiven for failing to conceive of a perfect package management system in 1990s. There were bigger fish to fry back then, so to speak. Over the decades (!) there have been many, well-documented attempts at coming up with a…
This comment is rewriting Python history quite a bit.
First of all, Python was created around 1989 yet Python 1.0 was released in 1994. Secondly, Python was a pretty obscure language until Python 2.0 (and even long after that...), released in 2000. So realistically, Python had "only" about 15 years of historical baggage :-)
Also, cargo can be ignored because it's "new", but there was a lot of prior art in the area of good programming language specific package managers. CPAN (Perl) was launched in 1993. Maven (Java) was launched in 2004.
Python just botched its package management story, that's it. Sometimes stuff happens just because it happens, there's no good excuse for how things are. Sad, but true.
Re: Overview of Python dependency management tools
#155Re: Overview of Python dependency management tools
#156After hitting some weird PyInstaller bugs, I gave up and started compiling Python myself. One interpreter for every project. Shell scripts to set the paths. All libraries go directly in site-packages, not some other layer. A little more complicated at the outset, but this approach has yet to let me down. And compared to the nightmares I was trying to fix, building Python is dead easy.
Re: Overview of Python dependency management tools
#157Earlier 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…
Does this imply that poetry will "solve" dependencies quicker the more of the dependencies use `pyproject.toml`? Or is that "hidden" once something is sent to PyPI anyways?
With several asterisks attached, but yes, the move would make dependency resolution faster.
Re: Overview of Python dependency management tools
#158Earlier quoted context omitted.
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.
Cargo is my ideal, but really anything that doesn't make me manage virtualenvs or take 30 minutes to resolve dependencies. Note that "managing my own virtualenvs" is tricky because you have to make sure everyone has all of the same versions of the same dependencies in their virtualenv across your entire team (including production). I'm sure there are workflows that allow for this (probably with some tradeoffs), but w…
Great experience report: thank you! Wanted to point out that the Pants project has been focusing on widening that happy path recently (...by narrowing its focus to Python-only in the short term), and is ramping up to ship a 2.0.
This page covers some of the differences between v1 and v2 of the engine, and particularly its impact on Python: https://pants.readme.io/docs/pants-v1-vs-v2 ... We're using Rust and haven't bootstrapped yet, so we also appreciate Cargo and think that there is a lot to learn there.
We'd love feedback (via any of these channels: https://pants.readme.io/docs/community) on how to make it even better. Thanks!
Re: Overview of Python dependency management tools
#159Re: Overview of Python dependency management tools
#160Earlier quoted context omitted.
In the node world I see half of projects telling you how to install it with npm and half with yarn. In Python at least pip is a standard that always works to install, even if it doesn't solve the other problems.
Those are literally equivalent though, anything you can install using yarn you can install using npm. They connect to the same registry and use the same package.json format. Also, pip is relatively recent. Before that, it was a mix of setuptools, easy_install and various manual procedures.
I wouldn't call nine years relatively recent