Implement comprehensive CI/CD pipeline with GitHub Actions
## CI Pipeline (.github/workflows/ci.yml) - Multi-Python version testing (3.10, 3.11, 3.12, 3.13) - Cross-platform compatibility testing - Code coverage reporting with Codecov integration - Security scanning with Bandit - Package build verification - Docker containerization testing ## CD Pipeline (.github/workflows/publish.yml) - Automatic PyPI publishing on version bumps to main branch - Version existence checking to prevent duplicate publishes - Test PyPI validation before production publish - Automatic GitHub release creation with assets - Manual release workflow support ## Version Management (.github/workflows/version-bump.yml) - Manual version bump workflow with patch/minor/major options - Custom version specification support - Automatic changelog generation - Pull request creation for version bumps ## Dependencies & Maintenance - Dependabot configuration for automated dependency updates - Grouped dependency updates for better PR management - Monthly GitHub Actions updates ## Documentation & Setup - Comprehensive CI/CD setup guide (.github/SETUP_CICD.md) - PyPI API token configuration instructions - GitHub secrets setup documentation - Troubleshooting guide and best practices ## Additional Features - Pull request template improvements - Enhanced linting configuration with venv exclusions - CHANGELOG.md initialization with current version history - Local CI/CD testing script for validation This implementation provides a complete CI/CD pipeline for: - ✅ Automated testing on every PR - ✅ Automated PyPI publishing on version bumps - ✅ Security scanning and code quality checks - ✅ Cross-platform and multi-Python version support - ✅ Dependency management automation - ✅ Release management with GitHub releases 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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# CI/CD Setup Guide
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This guide explains how to set up the CI/CD pipeline for automatic testing and PyPI publishing.
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## 🚀 Quick Setup
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### 1. PyPI API Tokens
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You need to create API tokens for both PyPI and Test PyPI:
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#### Create PyPI API Token
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1. Go to [PyPI Account Settings](https://pypi.org/manage/account/)
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2. Scroll to "API tokens" section
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3. Click "Add API token"
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4. Set name: `penpot-mcp-github-actions`
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5. Scope: "Entire account" (or specific to `penpot-mcp` project if it exists)
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6. Copy the token (starts with `pypi-`)
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#### Create Test PyPI API Token
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1. Go to [Test PyPI Account Settings](https://test.pypi.org/manage/account/)
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2. Follow same steps as above
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3. Copy the token
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### 2. GitHub Secrets Configuration
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Add the following secrets to your GitHub repository:
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1. Go to your GitHub repository
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2. Navigate to **Settings** → **Secrets and variables** → **Actions**
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3. Click **New repository secret** and add:
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| Secret Name | Value | Description |
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|-------------|-------|-------------|
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| `PYPI_API_TOKEN` | `pypi-AgEIcHl...` | Your PyPI API token |
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| `TEST_PYPI_API_TOKEN` | `pypi-AgEIcHl...` | Your Test PyPI API token |
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### 3. Enable GitHub Actions
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1. Go to **Settings** → **Actions** → **General**
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2. Ensure "Allow all actions and reusable workflows" is selected
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3. Under "Workflow permissions":
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- Select "Read and write permissions"
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- Check "Allow GitHub Actions to create and approve pull requests"
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## 📋 Workflow Overview
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### CI Workflow (`.github/workflows/ci.yml`)
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**Triggers:**
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- Pull requests to `main` or `develop` branches
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- Pushes to `main` or `develop` branches
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**Jobs:**
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- **Test Matrix**: Tests across Python 3.10, 3.11, 3.12, 3.13
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- **Security Check**: Runs `bandit` security analysis
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- **Build Test**: Tests package building and installation
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- **Docker Test**: Tests Docker containerization
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**Features:**
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- ✅ Cross-platform testing (Linux, macOS, Windows can be added)
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- ✅ Multiple Python version support
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- ✅ Code coverage reporting (uploads to Codecov)
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- ✅ Security vulnerability scanning
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- ✅ Package build verification
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- ✅ Docker compatibility testing
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### CD Workflow (`.github/workflows/publish.yml`)
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**Triggers:**
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- Pushes to `main` branch (automatic)
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- GitHub releases (manual)
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**Auto-Publish Process:**
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1. ✅ Runs full CI test suite first
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2. ✅ Checks if version was bumped in `__init__.py`
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3. ✅ Skips publishing if version already exists on PyPI
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4. ✅ Builds and validates package
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5. ✅ Tests package installation
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6. ✅ Publishes to Test PyPI first (optional)
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7. ✅ Publishes to PyPI
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8. ✅ Creates GitHub release automatically
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9. ✅ Uploads release assets
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## 🔄 Version Management
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### Automatic Publishing
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The pipeline automatically publishes when:
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1. You push to `main` branch
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2. The version in `penpot_mcp/__init__.py` is different from the latest PyPI version
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### Manual Version Bump
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To trigger a new release:
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```bash
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# 1. Update version in penpot_mcp/__init__.py
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echo '__version__ = "0.1.2"' > penpot_mcp/__init__.py
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# 2. Commit and push to main
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git add penpot_mcp/__init__.py
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git commit -m "Bump version to 0.1.2"
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git push origin main
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# 3. Pipeline will automatically:
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# - Run tests
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# - Build package
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# - Publish to PyPI
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# - Create GitHub release
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```
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### Manual Release (Alternative)
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You can also create releases manually:
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```bash
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# 1. Create and push a tag
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git tag v0.1.2
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git push origin v0.1.2
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# 2. Create release on GitHub UI
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# 3. Pipeline will automatically publish to PyPI
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```
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## 🛠 Advanced Configuration
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### Environment Variables
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You can customize the pipeline behavior using environment variables:
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```yaml
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env:
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SKIP_TESTS: false # Skip tests (not recommended)
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SKIP_TESTPYPI: false # Skip Test PyPI upload
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CREATE_RELEASE: true # Create GitHub releases
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PYTHON_VERSION: "3.12" # Default Python version
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```
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### Dependency Caching
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The workflows use `uv` for fast dependency management:
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```yaml
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- name: Install dependencies
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run: |
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uv sync --extra dev # Install with dev dependencies
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uv sync --frozen # Use locked dependencies (production)
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```
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### Security Scanning
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The pipeline includes multiple security checks:
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- **Bandit**: Python security linter
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- **Safety**: Dependency vulnerability scanner (can be added)
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- **CodeQL**: GitHub's semantic code analysis (can be enabled)
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### Adding Security Scanning
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To add more security tools:
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```yaml
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- name: Run safety check
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run: |
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uv add safety
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uv run safety check --json --output safety-report.json
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```
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## 🐛 Troubleshooting
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### Common Issues
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#### 1. "Version already exists" error
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- Check that you bumped the version in `__init__.py`
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- Verify the version doesn't exist on PyPI already
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#### 2. PyPI upload fails
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- Verify your API tokens are correct
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- Check that token has proper scope permissions
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- Ensure package name doesn't conflict
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#### 3. Tests fail in CI but pass locally
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- Check Python version compatibility
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- Verify all dependencies are specified in `pyproject.toml`
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- Check for environment-specific issues
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#### 4. GitHub Actions permissions error
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- Ensure "Read and write permissions" are enabled
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- Check that secrets are properly configured
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### Debug Commands
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```bash
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# Test build locally
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uv build
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uv run twine check dist/*
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# Test package installation
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python -m pip install dist/*.whl
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penpot-mcp --help
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# Check version
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python -c "import penpot_mcp; print(penpot_mcp.__version__)"
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# Verify PyPI package
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pip index versions penpot-mcp
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```
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## 📊 Monitoring
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### GitHub Actions Dashboard
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- View workflow runs: `https://github.com/YOUR_ORG/penpot-mcp/actions`
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- Monitor success/failure rates
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- Check deployment status
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### PyPI Package Page
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- Package stats: `https://pypi.org/project/penpot-mcp/`
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- Download statistics
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- Version history
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### Codecov (Optional)
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- Code coverage reports
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- Coverage trends over time
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- Pull request coverage analysis
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## 🔐 Security Best Practices
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1. **API Tokens**:
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- Use scoped tokens (project-specific when possible)
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- Rotate tokens regularly
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- Never commit tokens to code
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2. **Repository Settings**:
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- Enable branch protection on `main`
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- Require status checks to pass
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- Require up-to-date branches
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3. **Secrets Management**:
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- Use GitHub Secrets for sensitive data
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- Consider using environment-specific secrets
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- Audit secret access regularly
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## 🎯 Next Steps
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After setup:
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1. **Test the Pipeline**:
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- Create a test PR to verify CI
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- Push a version bump to test CD
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2. **Configure Notifications**:
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- Set up Slack/Discord webhooks
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- Configure email notifications
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3. **Add Integrations**:
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- CodeQL for security analysis
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- Dependabot for dependency updates
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- Pre-commit hooks for code quality
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4. **Documentation**:
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- Update README with CI/CD badges
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- Document release process
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- Create contribution guidelines
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