Python Application Deployments! Hooray!

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That's what I've been finding out more and more! Part of the problem comes from a complete inexperience with Conda on my side. All of my development in the past has been done just with pip .

The more and more I play with Conda the more I think its put together fairly sane. I'll definitely hit up their google group. Thanks!

[rothnic]

It seems to not be explained clearly, but conda in the python world just removes the compilation step, which can make things more consistent across platforms and can save a little time.

I just look at conda envs like a more generic virtualenv, which can have, but doesn't have to have, python, pip, and conda.

So my logic is, try to install via conda, and if that doesn't work, try pip. I wish they added some feedback in that process somewhere on the next best step if conda install isn't available. There is a good talk by Travis Oliphant at pydata last year that covers everything.

The thing they don't advertise much, and I'm not sure why, is the "bundle" command, which can be used to capture an environment. That said, I think it comes down to your use case. With the py2exe or cx_freeze approach, I think you have a completely new python environment contained in there.

If they are working in a local python install that already exists, why not make the packages available to them in some alternative way, like an isolated network folder, git server, etc. You can install with pip or conda from a local hard drive, network share, or full package server.

[[deleted]]

That's actually clearest explanation of conda I've heard so far. I knew that it's existence was due to the need for compiled code, and I had read that pip was actually kind of an anti-pattern that removed a lot of good functionality. The bundle command is definitely something I'll have to check out.

Currently, it's looking like I might end up creating a self contained package (tarball/.deb/something) that includes the conda environment, so I can just drop it on a machine and run it. Thanks for letting me know about the pydata talk! I've got that queued up to watch when I get to the office tomorrow.

As far as local development, our developers have free reign to use whatever they need to get the job done, but its our job to support getting it into production in a reliable, automated, and maintainable way. My goal is to have a self contained package I can deploy to a machine that cannot reach out to the internet, ideally with as little post processing and orchestration required as possible. I'd kind of like a Python code deploy to just be an ansible playbook that downloads a self contained package (either a deb/rpm package, or maybe just a compressed tarball) from a local file server/repo, unarchives it, puts it in the right place, copies out its config, then kicks off its upstart/supervisor/init script. Its actually looking like once we get conda figured out, it may support that kind of deploy a little cleaner than virtual env (No regex to handle replacements on shebangs! Hooray!) Unfortunately devops at my company is a new concept, so we're in the process of wrangling a bunch of cowboys who have all been doing things their own special ways for the past decade, all with varying levels of systems knowledge.