Installation from Source

Installation from Source#

This guide installs both packages from the repository in editable (development) mode. The repository is a uv workspace monorepo, so a single make sync installs the grader-service and grader-labextension packages together with all development, test, and documentation dependencies.

Warning

This setup runs student code with the local autograding executors, which have full access to the service database and filesystem. A malicious submission could read or alter grades and other students’ work. It is for local development and testing only - use the Kubernetes installation with KubeAutogradeExecutor for any deployment that grades untrusted student code.

Prerequisites#

  • Python 3.9+

  • uv - Python package manager

  • Node.js 20+ (required to build the labextension frontend)

  • Git

1. Clone the repository#

git clone https://github.com/TU-Wien-dataLAB/grader.git
cd grader

The monorepo contains both packages, so you no longer need to clone the service and labextension repositories separately:

  • packages/service/ - grader-service backend

  • packages/labextension/ - grader-labextension JupyterLab extension

2. Install dependencies#

make sync

This runs uv sync --all-packages --all-groups and creates a single virtual environment with both packages installed in editable mode. Because the repository is configured as a uv workspace, the labextension’s dependency on grader-service is resolved from the local package (see tool.uv.sources in packages/labextension/pyproject.toml).

3. Create the database#

The repository ships example configuration files in dev/local/token/. Create the database schema by running the migration against the service config:

uv run grader-service-migrate -f dev/local/token/grader_service_config.py

The default config uses an embedded SQLite database and runs autograding tasks eagerly, so no external database or message broker is required for local testing.

4. Start Grader Service and JupyterHub#

Start the Grader Service:

make run-service

Grader Service runs at http://127.0.0.1:4010.

In a separate terminal, start JupyterHub:

make run-hub

JupyterHub will be running at http://127.0.0.1:8080.

Note

Start the Grader Service before JupyterHub.

5. Developing the labextension#

The labextension is installed in editable mode, so Python server-extension changes are picked up automatically. The TypeScript frontend, however, must be rebuilt to be visible in JupyterLab.

To rebuild the frontend once:

jlpm build

To watch the source directory and rebuild automatically on every change:

make watch-labextension

With the watch command running, every saved change is rebuilt and made available in your running JupyterLab after a browser refresh. Note that it may take several seconds for the extension to rebuild. Keep in mind that make watch-labextension continues running until you stop it and can consume significant system resources, so jlpm build is preferable for one-off changes.

Next steps#