[leksak]

Where do you stop short? I'm conflicted. I sometimes look at Docker and am like "this is great", but I also sometimes look at a plethora of Dockerfiles and I'm like... what are we doing wrong? Do you, for instance, Dockerize small Python tools (or similar)? How well does this work?

I remember one project where we had tons of small Pipenv projects and one pain was that a few were Python 3.5 and a few others were Python 3.6. I guess Dockerizing these would have mitigated the pain but honestly I am a complete Docker n00b and wouldn't know how to go about setting this up in a way that wouldn't cause more pain and another layer of abstraction.

Any tips? Reference material, etc?

[yorwba]

> we had tons of small Pipenv projects and one pain was that a few were Python 3.5 and a few others were Python 3.6

Isn't pipenv supposed to take care of that? You pipenv run the tool and it's automatically executed in the right virtual environment.

[leksak]

You can't set it up without the Python binary you want already being on the machine which may be a hassle if you are chasing "latest" and you have machines in your ecosystem that run old stuff, for instance, Jenkins nodes.

[thijsvandien]

You'd have to combine it with pyenv to allow for multiple interpreters and automatic switching between them.