Docker for Python & release automation
P36.containers-delivery.01 · Audience: guest, it-ml, language-pro · Prerequisites: Pipelines as code & quality gates
A wheel ships a library; a container image ships a running service — your app plus its interpreter and OS dependencies. Getting the image right (small, reproducible, non-root) and the release right (promote the exact build that passed) is the last mile of delivery. This module has you build a Dockerfile linter for the recurring mistakes.
ⓘ Concept: App + interpreter + OS deps
FROM python or :latest) breaks reproducibility, and a single stage bakes build tools into the shipped image. A multi-stage build compiles in one stage and copies only the result into a slim, pinned final stage.Why it matters — Knowing an image is a delivery artifact (like a wheel, but for a whole service) is what lets you reason about its size, reproducibility, and attack surface.
The multi-stage, pinned, non-root shape your linter rewards — build tools stay in the first stage, only the app crosses into the slim final image:
FROM python:3.12-slim AS build
COPY requirements.txt .
RUN pip install -r requirements.txt
FROM python:3.12-slim
COPY --from=build /usr/local /usr/local
COPY . /app
USER appuser
CMD ["python", "-m", "app"]
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🎓 Practice ladder
2 graded rungs · ~23 minBuild a Dockerfile linter for release-hygiene mistakes, then reason about containers and releases in an interview-style prompt.
Rung 1 — lint a Dockerfile
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Rung 2 — containers & release (interview)
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That closes P36: you can gate, fan out, promote, containerise and release a Python project — with this repo's own pipeline as the worked example throughout.
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