docker-uv-image-builds

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Translated

Build Docker images for Python services following team conventions. Use this skill when writing Dockerfiles, authoring CI image build pipelines, or adding a new service — covers mitodl image naming, git short-ref tags, relocatable uv venvs, and shared library handling.

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Sourcemitodl/agent-kit
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NPX Install

npx skill4agent add mitodl/agent-kit docker-uv-image-builds

Tags

Translated version includes tags in frontmatter
docker-image-buildpython-servicesci-pipelinesuv-venvconcourse-ci

SKILL.md Content

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Docker Image Builds for Python Services

Image naming

Images follow the pattern: 
mitodl/<service-name>
The service name should match the application or code location name used elsewhere in configuration (Helm values, Pulumi stacks, Concourse pipelines).

Image tags

Tag images with the git short ref (7-character SHA):
bash
GIT_TAG=$(git rev-parse --short HEAD)
docker build -t mitodl/${SERVICE_NAME}:${GIT_TAG} .
Do not use 
latest
as a production tag.

Python environment inside the image

Use a relocatable virtual environment so the venv works after Docker layer assembly:
dockerfile
WORKDIR /app
COPY pyproject.toml uv.lock ./
RUN uv venv --relocatable /app/.venv && \
    uv sync --frozen --no-dev

Shared libraries

Install shared internal libraries (e.g. 
ol-orchestrate-lib
) as build-time dependencies — do not mount them as Docker volumes at runtime. Add them to 
pyproject.toml
and let 
uv sync
install them during the image build.

Build context & 
.dockerignore

Exclude development artifacts:
.venv/
__pycache__/
*.pyc
.git/

Concourse CI integration

Concourse pipelines use 
paths:
filters on git resources to trigger image rebuilds only when relevant files change. When adding a new service, add its path to the corresponding pipeline's git resource 
paths
list.