Imported from jeremylongshore/tons-of-skills-marketplace (skills/.curated/palantir-ci-integration/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill palantir-ci-integration. Copyright stays with the author (MIT).

Palantir CI Integration

Overview

Set up GitHub Actions CI pipelines for Foundry integrations. Covers running transform unit tests with PySpark, SDK integration tests with mocked APIs, and linting Foundry-specific patterns.

Prerequisites

• GitHub repository with Foundry integration code
• foundry-platform-sdk in requirements
• pytest test suite

Instructions

Step 1: GitHub Actions Workflow

# .github/workflows/foundry-ci.yml
name: Foundry CI
on:
  push:
    branches: [main]
  pull_request:

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: "3.11"
          cache: pip

      - name: Set up Java (for PySpark)
        uses: actions/setup-java@v4
        with:
          distribution: temurin
          java-version: "11"

      - name: Install dependencies
        run: pip install -r requirements.txt

      - name: Run unit tests
        run: pytest tests/ -v --tb=short --junitxml=test-results.xml

      - name: Upload test results
        if: always()
        uses: actions/upload-artifact@v4
        with:
          name: test-results
          path: test-results.xml

  lint:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: "3.11"
      - run: pip install ruff
      - run: ruff check src/ tests/

  integration:
    runs-on: ubuntu-latest
    if: github.event_name == 'push' && github.ref == 'refs/heads/main'
    needs: [test, lint]
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: "3.11"
      - run: pip install -r requirements.txt
      - name: Run integration smoke test
        env:
          FOUNDRY_HOSTNAME: ${{ secrets.FOUNDRY_HOSTNAME }}
          FOUNDRY_CLIENT_ID: ${{ secrets.FOUNDRY_CLIENT_ID }}
          FOUNDRY_CLIENT_SECRET: ${{ secrets.FOUNDRY_CLIENT_SECRET }}
        run: python scripts/smoke_test.py

Step 2: Secret Configuration

# Add secrets to GitHub repository
gh secret set FOUNDRY_HOSTNAME --body "mycompany.palantirfoundry.com"
gh secret set FOUNDRY_CLIENT_ID --body "your-client-id"
gh secret set FOUNDRY_CLIENT_SECRET --body "your-client-secret"

Step 3: Custom Linting Rules for Foundry

# scripts/lint_foundry.py — catch common Foundry mistakes
import ast, sys

class FoundryLinter(ast.NodeVisitor):
    def visit_Str(self, node):
        # Flag hardcoded Foundry hostnames
        if "palantirfoundry.com" in node.s:
            print(f"  Line {node.lineno}: Hardcoded Foundry hostname — use env var")
        # Flag hardcoded RIDs
        if node.s.startswith("ri.foundry.main"):
            print(f"  Line {node.lineno}: Hardcoded RID — use config/env var")

for path in sys.argv[1:]:
    tree = ast.parse(open(path).read())
    FoundryLinter().visit(tree)

Output

• GitHub Actions workflow with unit tests, linting, and integration tests
• PySpark tests running in CI with JDK setup
• Secrets configured securely in GitHub
• Custom linting for Foundry-specific patterns

Error Handling

Resources

• GitHub Actions
• PySpark Testing

Next Steps

For deployment pipelines, see palantir-deploy-integration.