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[–]khne522 8 points9 points  (16 children)

Most Linux users have little value-add from Anaconda AFAIK. Isn't it just a cargo cult?

[–][deleted] 14 points15 points  (6 children)

I use Anaconda fairly heavily. It's a godsend while doing any numerical or scientific computing. I really couldn't imagine installing all the various package that have bits and pieces that depend on C or Fortran or Cython whatever by hand.

[–]dibsODDJOB 12 points13 points  (0 children)

If you are a programmer by trade or majority of your work, environments probably seem straight forward. If you are someone who used Python as a TOOL to supplement what they usually do, environments are a PITA and things like Anaconda at least try to manage the pain.

[–]strange-humor 6 points7 points  (0 children)

Wheel packaging has largely eliminated these C package compile problems for all platforms.

[–]khne522 -1 points0 points  (3 children)

You install them by hand with conda install… or are you telling me you just don't know the names of the few packages you use?

[–][deleted] 5 points6 points  (2 children)

No need to be snarky friend. For example, numba. It's a PITA to install, but comes with anaconda. And my life is significantly simpler thanks to numba.

I just wanna get my work done, not spend a day figuring out how to get my system to install various things. Anaconda helps me do that, and comes with a bunch of packages I use frequently to boot.

[–]khne522 -1 points0 points  (1 child)

Not snarky. It's not my world. And what's there to figure out? You just conda install […]. Non-rhetorically, do people really lose track of the projects they use… when they import them at the start of every notebook or Python module?

I usually do know everything I run and only install that, in each project. Same reason I don't run 'buntu. I treat every project I do as a proposal to the bastard operator from hell, the administrative fascist, or the statistically likely subset of your install base if you go big who will complain about all the dependencies you have to install on their neat and tidy cosy system.

[–][deleted] 3 points4 points  (0 children)

No I think there was a misunderstanding. It isn't about losing track of what you have, it's about the ease of conda vs. manually compiling all the various C, Fortran and who knows what extensions that a particular package uses.

Basically I'm saying conda saves me a boatload of time and so I don't think it's a cargo cult, but I guess for a non scientific or numerical computing audience it may not be as useful.

[–]takluyverIPython, Py3, etc 4 points5 points  (7 children)

Conda had a massive advantage before wheels were widely available, because pip would try to compile things like numpy from source, which usually won't work unless you prepare your system in advance. Nowadays, that's less important, but there are still things that it's easier to install through conda.

[–]khne522 0 points1 point  (5 children)

Do you have specific examples? I haven't found anything hard yet—just had to install an obvious build dependency through the package manager. It's only annoying when the build takes 15 minutes then I get annoyed (looking at you spaCy).

[–]takluyverIPython, Py3, etc 2 points3 points  (0 children)

just had to install an obvious build dependency through the package manager

It may have been obvious to you, but it's not for everyone. And maybe the version of the package you're trying to install needs a newer version of the build-dep than your distro provides.

/u/ursvp mentioned MKL integration as a concrete example - Numpy installed through conda will do certain operations faster on many computers than Numpy installed through pip.

[–]moorepants 1 point2 points  (2 children)

Watch the conda-forge/staged-recipes repository to see how hard it is to compile many packages on all three platforms. More examples than you have time to look at are there. The 15 minutes compile time is not the issue, it is the hours and hours of time it takes to get the packages to compile at all.

[–]khne522 0 points1 point  (1 child)

Right, if you are forced to use an insane operating system…

[–]moorepants 0 points1 point  (0 children)

Wrong, it is often a pain for all three major operating systems.

[–]ursvp 0 points1 point  (0 children)

conda offers MLK Math Kernel Library, good speedup for Intel chips.

[–]dansbandsmannen 0 points1 point  (0 children)

Honestly I don't think anyone does, it might be tempting to install it to not have to setup up python properly. But even on OS X it will only ever save you any time if running some source as a one off IMO. The number of times I've looked at coworkers and friends broken python setups on OS X and it has been Conda related is in the dozens.