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* Initial commit for Python 3.13
* Initial commit for Python 3.13
* Initial commit for Python 3.13
* Make mypy happy
* Constructor initial changes
* Constructor initial changes
* Docker folder
* More changes
* More changes
* More changes
* Merging from develop
* CDK 2.167.0
* Should not run CDK tests with all python version
* Should not run CDK tests with all python version - Python 3.12
Copy file name to clipboardExpand all lines: .github/workflows/reusable_deploy_v3_sar.yml
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#
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# 1. This workflow starts after the layer artifact is produced on `publish_v3_layer`
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# 2. We use the same layer artifact to ensure the SAR app is consistent with the published Lambda Layer
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# 3. We publish the SAR for 3.8 to 3.12 Python runtime and both x86_64 and arm64 (see `matrix` section)
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# 3. We publish the SAR for 3.8 to 3.13 Python runtime and both x86_64 and arm64 (see `matrix` section)
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# 4. We use `sam package` and `sam publish` to publish the SAR app
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# 5. We remove the previous Canary stack (if present) and deploy a new one to test the SAR App. We retain the Canary in the account for debugging purposes
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# 6. Finally the published SAR app is made public on the PROD environment
Copy file name to clipboardExpand all lines: docs/automation.md
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To build and deploy the Lambda Layers, we run a pipeline with the following steps:
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* We fetch the latest PyPi release and use it as the source for our layer.
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* We build Python versions ranging from **3.8 to 3.12** for x86_64 and arm64 architectures. This is necessary because we use pre-compiled libraries like **Pydantic** and **Cryptography**, which require specific Python versions for each layer.
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* We build Python versions ranging from **3.8 to 3.13** for x86_64 and arm64 architectures. This is necessary because we use pre-compiled libraries like **Pydantic** and **Cryptography**, which require specific Python versions for each layer.
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* We provide layer distributions for both the **x86_64** and **arm64** architectures.
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* For each Python version, we create a single CDK package containing both x86_64 and arm64 assets to optimize deployment performance.
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