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@PeterDaveHello PeterDaveHello commented Feb 1, 2025

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This will help minimize the Docker image size, as below:

REPOSITORY    TAG       IMAGE ID         CREATED        SIZE
pr-agent      after     caed11a1ed9c     2 hours ago    1.48GB
pr-agent      before    d6f12eb987b8     3 hours ago    1.59GB

PR Type

enhancement


Description

  • Added --no-cache-dir to pip install commands in Dockerfiles.

  • Reduced Docker image size by avoiding pip cache.

  • Updated multiple Dockerfiles for consistent optimization.


Changes walkthrough 📝

Relevant files
Enhancement
Dockerfile
Optimize Dockerfile with `--no-cache-dir` for pip               

docker/Dockerfile

  • Added --no-cache-dir to pip install commands.
  • Optimized Docker image size by avoiding pip cache.
  • Updated multiple stages in the Dockerfile for consistency.
  • +2/-2     
    Dockerfile.lambda
    Optimize Lambda Dockerfile with `--no-cache-dir`                 

    docker/Dockerfile.lambda

  • Added --no-cache-dir to pip install commands.
  • Reduced Docker image size by avoiding pip cache.
  • Ensured consistent optimization in Lambda-specific Dockerfile.
  • +2/-2     

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  • This will help minimize the Docker image size, as below:
    
    ```
    REPOSITORY    TAG       IMAGE ID         CREATED        SIZE
    pr-agent      after     caed11a1ed9c     2 hours ago    1.48GB
    pr-agent      before    d6f12eb987b8     3 hours ago    1.59GB
    ```
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    PR Reviewer Guide 🔍

    Here are some key observations to aid the review process:

    ⏱️ Estimated effort to review: 1 🔵⚪⚪⚪⚪
    🧪 No relevant tests
    🔒 No security concerns identified
    ⚡ Recommended focus areas for review

    Cleanup

    The requirements.txt file is added but never removed, unlike pyproject.toml. This could leave unnecessary files in the image.

    ADD pyproject.toml requirements.txt .
    RUN pip install --no-cache-dir . && rm pyproject.toml

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    PR Code Suggestions ✨

    Explore these optional code suggestions:

    CategorySuggestion                                                                                                                                    Score
    General
    Optimize Docker layer count

    Combine both pip install commands into a single RUN instruction to reduce Docker
    layers

    docker/Dockerfile.lambda [8-9]

    -RUN pip install --no-cache-dir . && rm pyproject.toml
    -RUN pip install --no-cache-dir mangum==0.17.0
    +RUN pip install --no-cache-dir . mangum==0.17.0 && rm pyproject.toml
    • Apply this suggestion
    Suggestion importance[1-10]: 8

    Why: Combining multiple RUN commands into a single instruction is a Docker best practice that significantly reduces the final image size by minimizing the number of layers. This optimization is particularly relevant for container deployments.

    8
    Clean up unused installation files

    Remove requirements.txt after installation to reduce image size, similar to how
    pyproject.toml is removed

    docker/Dockerfile.lambda [7-8]

     ADD pyproject.toml requirements.txt .
    -RUN pip install --no-cache-dir . && rm pyproject.toml
    +RUN pip install --no-cache-dir . && rm pyproject.toml requirements.txt
    • Apply this suggestion
    Suggestion importance[1-10]: 7

    Why: Removing requirements.txt after installation is a good practice for reducing Docker image size, consistent with how pyproject.toml is handled. This suggestion follows Docker best practices for minimizing image footprint.

    7
    Learned
    best practice
    Avoid hardcoding dependency versions by using build arguments or environment variables

    The mangum package version is hardcoded to 0.17.0. Consider moving this version
    number to a build argument or environment variable to make it easier to update in
    the future.

    docker/Dockerfile.lambda [9]

    -RUN pip install --no-cache-dir mangum==0.17.0
    +ARG MANGUM_VERSION=0.17.0
    +RUN pip install --no-cache-dir mangum==${MANGUM_VERSION}
    • Apply this suggestion
    6
    • Author self-review: I have reviewed the PR code suggestions, and addressed the relevant ones.

    @mrT23
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    mrT23 commented Feb 2, 2025

    thanks

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    2 participants