@ewatercycle/jupyterlab_thredds
v0.5.0
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JupyterLab viewer for Thredds catalog and ESGF
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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
pip install jupyterlab_thredds
jupyter labextension install @ewatercycle/jupyterlab_thredds
Usage
- Start Jupyter lab with
jupyter lab
- In Jupyter lab open a notebook
- Open the
THREDDS
tab on the left side. - Fill the catalog url
- Press search button
- Select how you would like to open the dataset, by default it uses iris Python package.
- Press a dataset to insert code into a notebook
Development
For a development install, do the following in the repository directory:
pip install -r requirements.txt
jlpm
jlpm build
jupyter labextension link .
jupyter serverextension enable --sys-prefix jupyterlab_thredds
(jlpm
command is JupyterLab's pinned version of yarn that is installed with JupyterLab.)
To rebuild the package and the JupyterLab app:
jlpm build
jupyter lab build
Watch mode
# shell 1
jlpm watch
# shell 2
jupyter lab --ip=0.0.0.0 --no-browser --watch
Release
To make a new release perform the following steps:
- Update version in
package.json
andjupyterlab_thredds/version.py
- Record changes in
CHANGELOG.md
- Make sure tests pass by running
jlpm test
andpytest
- Commit and push all changes
- Publish lab extension to npmjs with
jlpm build
andjlpm publish --access=public
- Publish server extension to pypi with
python setup.py sdist bdist_wheel
andtwine upload dist/*
- Create GitHub release
- Update DOI in
README.md
andCITATION.cff