This library will be used to write an excel file
with BMP values. Developed by the Academy of
Natural Sciences. Source:

https://github.com/TheAcademyofNaturalSciences/BMPxlsx

This will be available at /api/modeling/worksheet/,
the first modeling method available in the public API.
This is done for future compatibility, where we expect
all modeling methods to migrate to eventually. Also
because the input this takes (just a shape) is closer
to an Analyze method than the existing Modeling methods.

The input shape is intersected with HUC-12s, and for as many
it intersects, we make a pair of the HUC-12 with the clipping
of the shape to that HUC-12.

For every such pair, we will calculate a dictionary of values
used to generate an Excel sheet.

This is also available in https://github.com/WikiWatershed/MMW-BMP-spreadsheet-tool/,
although the version there is older than the one we are
supposed to use, so the newer version is added directly
to the repo.

From a runtime perspective, it is better to have the template
available immediately on disk for dynamic generation, rather
than downloading it from GitHub every time. This protects us
from GitHub outages.

This does cause some redundancy, and the need to keep the two
versions in sync. An alternative to this direct inclusion is
to include the source repo as a pinned submodule, and update
the submodule SHA reference when that repo is updated.

However, given that the original repo has an older version
of the file, I'm including the new version here for now. The
strategy for maintenance going forward is a policy decision
that should be made by the team.

The /api/modeling/worksheet endpoint will be used to
generate a JSON blob of values, which will then be
submitted to this endpoint to generate the actual
spreadsheets.

The expected input is still to be clarified, but will
be something along the lines of this:

[
	{
		"huc12": { ... },
		"aoi": { ... },
	},
	{
		"huc12": { ... },
		"aoi": { ... },
	},
]

For every pair of values, we copy the worksheet template
and fill in the values, save the new files in a temporary
directory, zip them all up in memory, delete the directory,
and return the zip file.