Conversation
- Removed local bundling fallback in CDK stack to enforce Linux builds - Appended --platform manylinux2014_x86_64 to pip install to guarantee AWS compatibility for lxml C-extensions - Updated README.md to list Docker Desktop as a prerequisite
Summary of ChangesHello, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request enhances the deployment process for Python AWS Lambda functions by integrating Docker-based bundling. This change addresses potential inconsistencies in dependency resolution, particularly for Python packages with C-extensions, by ensuring that all dependencies are built in an environment that mirrors the AWS Lambda runtime. The Highlights
🧠 New Feature in Public Preview: You can now enable Memory to help Gemini Code Assist learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. Click here to enable Memory in your admin console. Changelog
Activity
Using Gemini Code AssistThe full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips. Invoking Gemini You can request assistance from Gemini at any point by creating a comment using either
Customization To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a Limitations & Feedback Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here. You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension. Footnotes
|
There was a problem hiding this comment.
Code Review
This pull request refactors the Python Lambda function's deployment package creation to use Docker for bundling. This is a significant improvement, as it ensures that dependencies with C-extensions are compiled for the correct Lambda execution environment, resolving potential cross-platform issues. The README has also been updated to include Docker as a prerequisite. My review includes a suggestion to align the Lambda function's architecture with other functions in the stack for consistency and potential performance improvements.
| runtime: lambda.Runtime.PYTHON_3_12, | ||
| handler: 'process_run.handler', | ||
| code: lambda.Code.fromAsset(path.join(__dirname, '../../backend/python/src/handlers'), { | ||
| code: lambda.Code.fromAsset(path.join(__dirname, '../../backend/python'), { | ||
| bundling: { | ||
| image: lambda.Runtime.PYTHON_3_12.bundlingImage, | ||
| local: { | ||
| tryBundle(outputDir: string) { | ||
| try { | ||
| // Install dependencies into the output directory | ||
| execSync( | ||
| `pip3 install -r ${path.join(__dirname, '../../backend/python/requirements.txt')} -t ${outputDir}`, | ||
| ); | ||
| // Copy the handler code into the output directory | ||
| execSync( | ||
| `cp -R ${path.join(__dirname, '../../backend/python/src/handlers/process_run.py')} ${outputDir}`, | ||
| ); | ||
| return true; | ||
| } catch (e) { | ||
| console.warn('Local Python bundling failed:', e); | ||
| return false; | ||
| } | ||
| }, | ||
| }, | ||
| command: [ | ||
| 'bash', | ||
| '-c', | ||
| 'pip install -r requirements.txt -t /asset-output --platform manylinux2014_x86_64 --only-binary=:all: && cp -R src/handlers/* /asset-output/', | ||
| ], | ||
| }, | ||
| }), |
There was a problem hiding this comment.
For consistency with the Go Lambda functions in this stack which use ARM64, consider specifying the architecture for this Python function as well. ARM-based Lambdas can also provide better price/performance.
If you switch to ARM64, you'll need to update the bundling command to install the correct platform-specific wheels for your dependencies.
runtime: lambda.Runtime.PYTHON_3_12,
architecture: lambda.Architecture.ARM_64,
handler: 'process_run.handler',
code: lambda.Code.fromAsset(path.join(__dirname, '../../backend/python'), {
bundling: {
image: lambda.Runtime.PYTHON_3_12.bundlingImage,
command: [
'bash',
'-c',
'pip install -r requirements.txt -t /asset-output --platform manylinux2014_aarch64 --only-binary=:all: && cp -R src/handlers/* /asset-output/',
],
},
}),- Set python lambda architecture to ARM_64 for better price/performance - Updated pip build platform target to manylinux2014_aarch64
No description provided.