dec5b0d5ea
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59 lines
2.0 KiB
Docker
59 lines
2.0 KiB
Docker
FROM python:3.12-slim-bookworm
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# --- Install uv (pinned for reproducibility) ---
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COPY --from=ghcr.io/astral-sh/uv:0.10.8 /uv /uvx /bin/
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WORKDIR /app
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# Create non-root user with explicit UID/GID 1000
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RUN addgroup --gid 1000 appgroup && \
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adduser --uid 1000 --gid 1000 --disabled-password --gecos "" appuser
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# Install system dependencies:
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# - git: required to fetch util-services from GitLab (tool.uv.sources)
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# - curl: optional healthcheck / runtime tooling
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RUN apt-get update \
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&& apt-get install -y --no-install-recommends \
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git=1:2.39.5-0+deb12u3 \
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curl=7.88.1-10+deb12u14 \
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&& apt-get clean \
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&& rm -rf /var/lib/apt/lists/* \
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&& rm -rf /tmp/* \
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&& rm -rf /var/tmp/*
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# Ensure appuser can create the project virtual environment in /app
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RUN chown appuser:appgroup /app
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# Copy project metadata and source
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COPY --chown=appuser:appgroup pyproject.toml .
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COPY --chown=appuser:appgroup uv.lock .
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COPY --chown=appuser:appgroup src/ ./src/
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# uv environment knobs:
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# UV_COMPILE_BYTECODE → disable .pyc precompile to reduce image size
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# UV_LINK_MODE=copy → copy files instead of symlinks (required in Docker layers)
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# UV_SYSTEM_PYTHON=1 → install into the system Python (no extra venv needed)
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ENV UV_COMPILE_BYTECODE=0
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ENV UV_LINK_MODE=copy
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ENV UV_SYSTEM_PYTHON=1
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# Install the project and all dependencies, respecting [tool.uv.sources]
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# (git source for util-services and pytorch-cpu index for torch)
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# BuildKit cache mount keeps the uv package cache across builds
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USER appuser
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RUN --mount=type=cache,target=/home/appuser/.cache/uv,uid=1000,gid=1000 \
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uv sync --frozen --no-dev --no-install-package torch
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# Put the project's venv on PATH (matches WORKDIR)
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ENV PATH="/app/.venv/bin:${PATH}"
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ENV PYTHONPATH="/app/src"
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ENV HOME=/home/appuser
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# Sanity-check: fail the build early if the dagster CLI is missing
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RUN dagster --version
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EXPOSE 4000
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CMD ["dagster", "code-server", "start", "-h", "0.0.0.0", "-p", "4000", "-f", "src/template_code_location/repository.py"]
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