Data Lab

Sandbox for mini experiments and practice with data tools and techniques.

Requirements

• Docker >= 4.63

Local Installation

$ docker build --t datalab .

Usage

$ docker run -p 8888:8888 datalab:latest

Contributing

Requirements

• uv >= 0.10

Installation

$ uv python install 3.12 # if necessary
$ uv sync
$ uv run pre-commit autoupdate
$ uv run pre-commit install

Deep learning dependencies are kept separate to reduce installation size and prevent conflicts. To install Tensorflow, use uv sync --group tf. To install Pytorch, use uv sync --group pytorch. Remember to adjust the Dockerfile to include the relevant dependency groups.

Usage

$ uv run jupyter lab

Guidelines

• Write self-documenting code
• Manage dependencies with uv (e.g., uv add polars)
• Verify types with ty (e.g., uv run ty check)
• Use pytest for tests (e.g., uv run pytest)
• Ensure style compliance with ruff (e.g., uv run ruff check --fix, uv run ruff format)
• Containerize releases with Docker
• Submit pull requests to dev