Overview

Run a Datadog Static Analysis job in your GitHub Action workflows.

Setup

To use Datadog Static Analysis, you need to add a static-analysis.datadog.yml file to your repository’s root directory to specify which rulesets to use.

rulesets:
  - <ruleset-name>
  - <ruleset-name>

Example for Python

You can see an example for Python-based repositories:

rulesets:
  - python-code-style
  - python-best-practices
  - python-inclusive

Workflow

Create a file in .github/workflows to run a Datadog Static Analysis job.

The following is a sample workflow file.

on: [push]

jobs:
  check-quality:
    runs-on: ubuntu-latest
    name: Datadog Static Analyzer
    steps:
      - name: Checkout
        uses: actions/checkout@v4
      - name: Check code meets quality standards
        id: datadog-static-analysis
        uses: DataDog/datadog-static-analyzer-github-action@v1
        with:
          dd_app_key: ${{ secrets.DD_APP_KEY }}
          dd_api_key: ${{ secrets.DD_API_KEY }}
          dd_service: "my-service"
          dd_env: "ci"
          dd_site: 
          cpu_count: 2
          enable_performance_statistics: false

You must set your Datadog API and application keys as secrets in your GitHub repository whether at the organization or repository level. For more information, see API and Application Keys.

Inputs

You can set the following parameters for Static Analysis.

Note: Diff-aware scanning only scans the files modified by a commit when analyzing feature branches. Diff-aware is enabled by default. To disable diff-aware scanning, set the GitHub action diff_aware parameter to false.

Further Reading

Additional helpful documentation, links, and articles:

• Learn about Code Analysis