Jupyter Notebook install

[alexander-petkov]

Set-up a Jupyter Notebook on a server, so we can more easily interact with the weather forecast data.

[alexander-petkov]

Geonotebook might be of interest--can be configured to connect to a geoserver instance.

About:

GeoNotebook is an application that provides client/server environment with interactive visualization and analysis capabilities using Jupyter, GeoJS and other open source tools. Jointly developed by Kitware and NASA Ames. Documentation for GeoNotebook can be found at http://geonotebook.readthedocs.io.

Docker container files: https://github.com/OpenGeoscience/geonotebook/blob/master/devops/docker

Last update--about 3 years ago.

[alexander-petkov]

Ipyleaflet might be of interest to us. Here is a good blog article about it:

https://blog.jupyter.org/interactive-gis-in-jupyter-with-ipyleaflet-52f9657fa7a

I think our intent of using Jupiter notebooks is beyond displaying maps--such as manipulating data and creating plots. I'll see what I can find.

[alexander-petkov]

JupyTEP IDE looks very much worth exploring and using:

It is built as an extension of Jupyter environment and Docker engine dedicated to working with EO data and it is based on the notebook philosophy of scripting. JupyTEP IDE allows scientists, developers of satellite remote sensing applications and other professional or non-professional users to create their own isolated development environment in an easy way. The users are able to write algorithms choosing various languages (Python, R, etc.) and a wide range of tools and libraries. The results can be presented and shared in the interactive and common Jupyter notebook format.

Here is a paper about it.

[alexander-petkov]

Where should the Jupiter server be installed?

Possibilities are either on Plume, or AWS.

[wmjolly]

Let's do Plume first, that way we can scale to many processors if we need.

On Wed, Dec 9, 2020 at 8:37 AM alexander-petkov notifications@github.com wrote:

Where should the Jupiter server be installed?

Possibilities are either on Plume, or AWS.

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[alexander-petkov]

A gallery of interesting Jupyter Notebooks https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks#data-visualization-and-plotting

[alexander-petkov]

An overview of deploying a Docker-based Jupyter notebook server on ECS https://medium.com/harrys-engineering/an-on-demand-high-powered-jupyter-notebook-server-12ee73d4612a

[alexander-petkov]

The jupyther/datascience-notebook container doesn't have netcdf4, which can be installed with

conda install netcdf4

A web browser terminal session also works, no need to ssh and then login to the container.

[alexander-petkov]

Conda packages installed to date in the Jupyter notebook container:

[alexander-petkov]

I cleaned the conda environment, which pruned caches, tarballs, unuzed packages, etc.

I also removed the census. ipnb example and data, as well as the datashader demos in order to reclaim some space.