Local PySpark dev environment

This repo provides a self-contained, local PySpark development environment that runs on your laptop with Docker, VS Code, and Dev Containers.

It uses Visual Studio Code and the Dev Containers feature to run Spark and JupyterLab in Docker while keeping the workspace mounted in your editor.

Requirements

• Install Docker Desktop
• Install Visual Studio Code
• Install the Dev Containers extension

Setup

1. Clone this repository to your laptop.
2. Open the repo folder in VS Code.
3. Run the VS Code command palette command Dev Containers: Reopen in Container.
4. Wait for the container to build. The postCreateCommand installs the project and development tools from pyproject.toml.
5. Open test.ipynb in VS Code.
6. Use the JupyterLab interface at http://localhost:8888.
7. If the notebook asks for a kernel, select the vscode_pyspark kernel.
8. Run the cells in order to explore the local Spark session.

Development tooling

The project now includes modern Python tooling for local checks and CI:

• ruff for linting
• black for formatting
• pytest for tests
• pre-commit for consistent hooks

You can run the checks locally with:

python -m pip install -e '.[dev]'
ruff check .
black --check .
pytest

Notes

• The devcontainer now uses a pinned base image (jupyter/pyspark-notebook:spark-3.5.0) for reproducible builds.
• The Spark UI is exposed on port 4040 for debugging and monitoring.