jupyterlab_thredds

JupyterLab dataset browser for THREDDS catalog

Can inject iris/xarray/leaflet code cells into a Python notebook of a selected dataset to further process/visualize the dataset.

Prerequisites

• JupyterLab, pip install jupyterlab
• ipywidgets, jupyter labextension install @jupyter-widgets/jupyterlab-manager, requirement for ipyleaflet
• ipyleaflet, jupyter labextension install jupyter-leaflet, to load a WMS layer
• iris, conda install -c conda-forge iris

Installation

bash pip install jupyterlab_thredds jupyter labextension install @ewatercycle/jupyterlab_thredds

Usage

1. Start Jupyter lab with jupyter lab
2. In Jupyter lab open a notebook
3. Open the THREDDS tab on the left side.
4. Fill the catalog url
5. Press search button
6. Select how you would like to open the dataset, by default it uses iris Python package.
7. Press a dataset to insert code into a notebook

Development

For a development install (requires yarn), do the following in the repository directory:

bash yarn install yarn build jupyter labextension link . python setup.py develop jupyter serverextension enable --sys-prefix jupyterlab_thredds

To rebuild the package and the JupyterLab app:

bash yarn build jupyter lab build

Watch mode ```bash

shell 1

yarn watch

shell 2

jupyter lab --ip=0.0.0.0 --no-browser --watch ```

Release

To make a new release perform the following steps: 1. Update version in package.json, CITATION.cff and jupyterlab_thredds/version.py 2. Make sure tests pass by running yarn test and pytest 3. Publish lab extension to npmjs with yarn build and yarn publish --access=public 4. Publish server extension to pypi with python setup.py sdist bdist_wheel and twine upload dist/* 5. Create GitHub release 6. Update DOI in README.md and CITATION.cff