Installation

We recommend uv for managing the Python environment.

Quick start (unit tests / development)

git clone git@github.com:jameslehoux/datalab-app-xrayct
cd datalab-app-xrayct
uv sync --locked --dev
uv run pytest

This installs the plugin and its scientific dependencies (nexusformat, tifffile, pydantic v2, etc.) but does not install pydatalab. The unit tests do not require it.

Running the plugin inside a live datalab server

The currently published datalab-server on PyPI pins pydantic<2, which is incompatible with this plugin's pydantic v2 schema. Until a v2-compatible release lands, install pydatalab directly from git into the same virtual environment as the plugin:

# In the same venv where you installed datalab-app-xrayct
pip install "git+https://github.com/datalab-org/datalab.git#subdirectory=pydatalab"
pip install -e .

# (Re)start the datalab server. The "X-ray CT dataset" block should now appear
# in the "Add block" menu.

If you are running the datalab server somewhere the Diamond filesystem is not mounted at /dls (e.g. a Greenwich box with the data mirrored elsewhere), export the mount prefix:

export DATALAB_DIAMOND_MOUNT=/mnt/dls-mirror

Development

uv run pre-commit install

This installs the pre-commit hooks so style checks run on every commit.