Development Setup

This guide helps you set up a development environment for DataLab-Kernel.

Clone the Repository

$ git clone https://github.com/DataLab-Platform/DataLab-Kernel.git
$ cd DataLab-Kernel

Create Virtual Environment

$ python -m venv .venv
$ source .venv/bin/activate  # Linux/macOS
$ .venv\Scripts\activate     # Windows

Install in Development Mode

$ pip install -e ".[dev]"

Environment Configuration

Create a .env file for local development:

PYTHONPATH=.

If developing with local Sigima/DataLab clones:

PYTHONPATH=.;../sigima;../DataLab

Running Tests

# Unit and contract tests (no DataLab needed)
$ pytest datalab_kernel/tests/unit datalab_kernel/tests/contract -v

# Integration tests (requires DataLab)
$ pytest --live --start-datalab datalab_kernel/tests/integration -v

# All tests with coverage
$ pytest --cov=datalab_kernel --cov-report=html

Linting

# Format code
$ ruff format datalab_kernel

# Lint and fix
$ ruff check datalab_kernel --fix

Building Documentation

$ pip install sphinx pydata-sphinx-theme myst-nb sphinx-design sphinx-copybutton
$ sphinx-build doc build/doc -b html

VS Code Configuration

The repository includes VS Code configuration:

• .vscode/settings.json: Editor settings

• .vscode/tasks.json: Build tasks (Ruff, Pytest)

• .vscode/launch.json: Debug configurations

Project Structure

DataLab-Kernel/
├── datalab_kernel/
│   ├── __init__.py       # Package entry point
│   ├── workspace.py      # Workspace, backends
│   ├── plotter.py        # Visualization
│   ├── objects.py        # Re-exports from Sigima
│   ├── persistence.py    # HDF5 save/load
│   ├── install.py        # Kernel installation
│   └── tests/
│       ├── unit/         # Unit tests
│       ├── contract/     # API contract tests
│       └── integration/  # Live mode tests
├── doc/                  # Sphinx documentation
├── .github/workflows/    # CI configuration
└── pyproject.toml        # Project configuration