Jupyter Notebook archetypes
---------------------------

The Jupyter Notebook archetypes are Ellip Workflow templates that allow using a Jupyter Notebook as a streaming executable, and thus such archetypes provide the functionalities to:

* Use a Jupyter Notebook to process and plot EO data using toolboxes such as GDAL, OTB and SNAP
* Using notebooks as streaming executables in processing services to systematically generate higher-level EO based products

The notebook can be written using any of the supported kernels. Today these are:

* Python 2
* R

The archetypes based on Jupyter Notebook are split into two groups:

* Stage-in: EO data references are staged-in locally, before instantiating and executing the streaming notebook. Two templates: n-to-n and m-to-1

* No Stage-in: It implies doing the stage-in within the streaming notebook (it only provides the references). Two templates: n-to-n and m-to-1

The Jupyter Notebook archetypes include: 

No data stage-in, one-to-one
^^^^^^^^^^^^^^^^^^^^^^^^^^^^

This template requires doing the stage-in in the streaming notebook and is meant for processing one EO product during the notebook execution (n to n).

No data stage-in, many-to-one 
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

This template this template requires doing the stage-in in the streaming notebook and is meant for processing all EO products during the notebook execution (m to 1).

One-to-one
^^^^^^^^^^^

This template is meant for processing one EO product during the notebook execution (n to n).

Many-to-one
^^^^^^^^^^^

This template is meant for processing all EO products during the notebook execution (m to 1).