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A Jupyter Notebook server extension which crawls a thredds catalog

Project description

# jupyterlab_thredds

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JupyterLab dataset browser for [THREDDS catalog](https://www.unidata.ucar.edu/software/thredds/v4.6/tds/catalog/index.html)

Can inject [iris](http://scitools.org.uk/iris/docs/latest/index.html)/[xarray](https://xarray.pydata.org)/[leaflet](https://github.com/jupyter-widgets/ipyleaflet) code cells into a Python notebook of a selected dataset to further process/visualize the dataset.

![screenshot](https://github.com/eWaterCycle/jupyterlab_thredds/blob/master/jupyterlab_thredds.gif “Screenshot”)

## 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](http://scitools.org.uk/iris/docs/latest/index.html), 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](http://scitools.org.uk/iris/docs/latest/index.html) Python package.
  7. Press a dataset to insert code into a notebook

## Development

For a development install (requires npm version 4 or later), do the following in the repository directory:

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

To rebuild the package and the JupyterLab app:

`bash npm run build jupyter lab build `

Watch mode `bash # shell 1 npm run 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 and jupyterlab_thredds/version.py 2. Make sure tests pass by running npm test and pytest 3. Publish lab extension to npmjs with npm run build and npm publish –access=public 4. Publish server extension to pypi with python setup.py sdist bdist_wheel and twine upload dist/*

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