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Create cml1.yaml#1

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onsSK-patch-1
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Create cml1.yaml#1
onsSK wants to merge 1 commit into
mainfrom
onsSK-patch-1

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@onsSK

@onsSK onsSK commented Aug 30, 2024

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Summary by Sourcery

Introduce a new GitHub Actions workflow to automate machine learning operations by adding a 'cml1.yaml' file.

CI:

  • Add a new GitHub Actions workflow 'mlops' triggered on push events to automate machine learning operations.

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sourcery-ai Bot commented Aug 30, 2024

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Reviewer's Guide by Sourcery

This pull request adds a new GitHub Actions workflow file named 'cml1.yaml' to set up a basic MLOps pipeline using Continuous Machine Learning (CML). The workflow is triggered on every push and runs on the latest Ubuntu environment.

File-Level Changes

Change Details Files
Implement a new GitHub Actions workflow for MLOps
  • Define the workflow name as 'mlops'
  • Set the workflow to trigger on push events
  • Specify the job to run on the latest Ubuntu environment
  • Use the actions/checkout@v3 action to fetch the repository
  • Set up CML using the iterative/setup-cml@v1 action
  • Include a 'Train model' step that installs requirements and runs a Python script
.github/workflows/cml1.yaml

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Hey @onsSK - I've reviewed your changes - here's some feedback:

Overall Comments:

  • Consider replacing the Jupyter notebook (stage.ipynb) with a plain Python script for better version control and reproducibility in the CI/CD pipeline.
  • It's recommended to pin the Ubuntu runner to a specific version (e.g., ubuntu-20.04) to ensure consistency across workflow runs.
  • Review the commented-out Node.js and Python setup steps. If these are needed, consider including them explicitly to ensure the correct versions are used.
Here's what I looked at during the review
  • 🟡 General issues: 1 issue found
  • 🟢 Security: all looks good
  • 🟢 Testing: all looks good
  • 🟢 Complexity: all looks good
  • 🟢 Documentation: all looks good

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Help me be more useful! Please click 👍 or 👎 on each comment to tell me if it was helpful.

@@ -0,0 +1,23 @@
name: mlops
on: [push]

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suggestion (performance): Consider more specific trigger conditions

Triggering the workflow on every push might be inefficient, especially if the ML workflow is computationally intensive. Consider using more specific conditions, such as pushes to certain branches or changes to specific files.

on:
  push:
    branches:
      - main
      - develop
    paths:
      - 'src/**'
      - 'models/**'
      - 'data/**'

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