Minimal Python library for SkogAI tool execution and automation.

pip install skoglib

from skoglib import run_executable

# Execute a command and get structured results
result = run_executable("echo", ["Hello, World!"])
print(f"Output: {result.stdout}")
print(f"Exit code: {result.return_code}")

• Batteries included but minimal approach to running external executables
• Proper error handling with structured exception hierarchy
• Output capture and logging integration
• Performance monitoring and debugging support
• Python 3.8+ compatibility

This project uses a comprehensive CI/CD pipeline with multiple quality gates:

• Multi-platform testing: Linux, macOS, Windows
• Python version matrix: 3.8, 3.9, 3.10, 3.11, 3.12, 3.13
• Quality checks: Ruff linting, MyPy type checking
• Performance benchmarks: Import time < 50ms, execution overhead monitoring
• Code coverage: Automated coverage reporting with Codecov

• SAST: Static application security testing with Bandit
• Dependency scanning: Vulnerability detection with pip-audit
• Supply chain security: Package integrity verification
• Secrets detection: TruffleHog for credential leak prevention
• Automated updates: Dependabot for security patches

• Automated publishing: PyPI publishing with OIDC trusted publishing
• Package verification: Wheel and source distribution validation
• Release validation: Post-publish functionality testing

# Setup development environment
pip install uv
uv sync --dev

# Run quality checks
uv run ruff check .          # Linting
uv run ruff format --check . # Format checking
uv run mypy src/            # Type checking
uv run bandit -r src/       # Security scanning

# Run tests
uv run pytest              # All tests
uv run pytest --cov=src/skoglib --cov-report=term-missing  # With coverage

# Build package
uv build

The library maintains strict performance standards:

• Import time: < 50ms
• Execution overhead: Minimal subprocess overhead
• Memory usage: Lightweight footprint

MIT License - see LICENSE file for details.