2. Develop application
3. Repeat 1-2 until ready to deploy
4. Run Docker image in production with same dependencies as development
5. ??
6. Profit!
As long as you don't rebuild in between steps 3-4, you'll have the same set of dependencies down to the exact patch level.
Docker images are also a great way to distribute Python CLI tools, certainly far better than installing via pip which either pollutes global state or is confined to a certain project's virtualenv.
It doesn’t have to be docker, containers just makes it easy to have immutable snapshots. Anything that packages it all up (including a simple tarball) is enough.
nowadays, requirements + docker solves 99% of everything i do.
maybe it's because i'm not using numpy and the likes?