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Max_Limelihood | 3 years ago

Answer: they don’t

(Seriously, I’ve gotten so fed up with Python package management that I just use CondaPkg.jl, which uses Julia’s package manager to take care of Python packages. It is just so much cleaner and easier to use than anything in Python.)

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dangerlibrary|3 years ago

I hate python package management - I really do. But I've never actually had a problem with virtual environments, and I think it's because I just use virtualenv directly (rather than conda or whatever else).

I have these aliases in my .bashrc, and I can't remember the last time I had a major issue.

alias venv='rm -rf ./venv && virtualenv venv && source ./venv/bin/activate'

alias vact='source ./venv/bin/activate'

alias pinstall='source ./venv/bin/activate && pip install . && pip install -r ./requirements.txt && pip install ./test_requirements.txt'

I don't have all the fancy features, like automatically activating the virtualenv when I cd into the directory, but I've always found those to be a bigger headache than they are worth. And if I ever run into some incompatibility or duplicate library or something, I blow away the old venv and start fresh. It's a good excuse to get up and make a cup of tea.

Joker_vD|3 years ago

> source ./venv/bin/activate

To this day I'm not quite sure why the venv developers decided that sourcing was a good idea; all it does can be effectively replaced with

    #!/bin/sh
    export VIRTUAL_ENV="path to venv"
    export PATH="$VIRTUAL_ENV/bin:$PATH"
    unset PYTHONHOME
    exec "$SHELL"
Just run this script to get into an "activated" shell. To deactivate, just press Ctrl+D. If you're really fancy, you can replace the last line with

    exec "${@:-$SHELL}"
to run a command directly in the activated environment (and then deactivate it immediately).

Izkata|3 years ago

> virtualenv venv

That would be python2, in 3 it's "python -m venv venv" (first venv is package to run, second is directory to put it in)

Otherwise yeah, it's the same and I also use it manually. Never had any problems.

danielvaughn|3 years ago

A few weeks ago I spent about a week debugging my Poetry environment. Turns out, their latest release (which I believe was a patch bump!) brought in some breaking changes. And on top of that, a bunch of stuff was forcing python3.11 under the hood, whereas I was on python3.10.

It was a nightmare.

rewgs|3 years ago

This is similar to what I do, except my "new environment" alias executes a function that takes a python version, installed/specified via pyenv.

Never had a single problem, venv + pyenv is a great combo. As far as I can tell, like so many sources of frustration in tech, the issue typically lies with user error/not fully understanding the tool you're using. That isn't saying that there isn't room for improvement -- most notably, package management in Python flies in the face of "there should be one -- and preferably only one -- obvious way to do it" -- but the tools we have work quite well.

spprashant|3 years ago

I might steal these aliases, thank you.

Using virtualenv directly has also been my approach, and has not failed me yet.

I also used Poetry for one of my personal projects, and I liked what I saw.

albert_e|3 years ago

I have struggled with conda and the huge space it usually eats up

I should learn to use venv properly

Thanks

jimnotgym|3 years ago

Agreed. I tried the new package manager combined with venv and using venv directly seems best. A lot faster for a start.

birdstheword5|3 years ago

It sounds mean to say it, but it's 100% true. I moved away from using python wherever I can. I've had colleagues struggle for days to install well used packages like pandas and numpy in conda.

danielvaughn|3 years ago

I just began writing Python a few months ago. For years prior, I'd been a JS dev, and while NPM can be frustrating at times, I never encountered so many issues as I have in Python. It's crazy.

I'm now curious whether there are languages out there that do have a really nice packaging system.

prds_lost|3 years ago

Your colleagues should consider skipping conda and stick to using venv. It will make life much easier. Given pandas/numpy is huge in data science, moving away is not much of an option unless you are working on a personal project or already have a dedicated team comfortable with using a different stack. There is also the Docker option which is great but much more involved.

zelphirkalt|3 years ago

My advice would be to not use Conda or other such "extra tooling". More trouble than benefit. Stick with venv and poetry.

swyx|3 years ago

also there's like 3 different flavors of virtual env now and me being 8 years out of date with my python skillz i have no idea what the current SOTA is with python venv tooling :/

i dont need them demystified, i need someone smarter than me to just tell me what to do lol

dwringer|3 years ago

> and me being 8 years out of date with my python skillz i have no idea what the current SOTA is with python venv tooling :/

It doesn't really matter, by the time you sit down and use it you'll find whatever that is, has also been deprecated and replaced by 2 more.

ollien|3 years ago

The reality is that if you ask 3 different people you're going to get 3 different answers. They're fundamentally the same, just a matter of package management. As far as I'm aware, the current "SOTA" is Poetry. I liked Pipenv for quite some time, but Poetry is just so much faster IME.

gosukiwi|3 years ago

It also makes it very hard for new devs willing to learn Python. Coming from Ruby and JavaScript, you just use bundler or npm, but Python is so strange, even the way it runs files is different, with the module thing.

hot_gril|3 years ago

> i dont need them demystified, i need someone smarter than me to just tell me what to do lol

Dockerfile ;)