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Many packages? Yes! The core design philosophy is that things should be easy to maintain, easy to upgrade, and should not break. Although the toolkit is currently seven packages, there are only three hard dependencies. The rest is all methods overloading, and well-documented interfaces.

But one of my favorite things that the package can do is explanations: I collected a lot of functions I wrote to teach data science into a small package to do simple SDMs, and it's sort of bare bones but very easy to use, so learners can experiment with it.

We are using this package as part of @geobon.org BON in a Box project, and the ability to iterate extremely rapidly by adding functionalities with minimal risk of something else breaking was life changing.

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