Good discussion and examples on best practices for building/delivering python poetry projects with Docker: Dockerfile tips, which command line arguments/ env vars to use for poetry, and how to approach multi-stage builds.

Build a multi-stage Docker image from official Python images with support for Poetry projects.

A good (concise) example of multi-stage dockerizing if you already somewhat know about basic docker concepts.

'Static' and very low-overhead type checking for Python. Uses the standard python type hints, requires a simple decorator and will crash the program if inputs do not fit types hinted.

Amazing little library making writing 'scripts' in D so much easier: user interaction, shell commands, dry-run mode, return fail codes, and some more.