Summary
In this chapter, we went through the basics of building a simple catastrophe model. We then broke down the logic and converted it into steps so that we could build the catastrophe model in Rust. This included taking in paths, loading data from files, including data in our package, and building a Python interface so that our users do not have to know about what is going on under the hood when constructing a model. After all of this, we tested our module and ensured that we kept increasing the data size of the test to see how it scales. We saw that, initially, our Rust solution was faster because Rust is faster than Python and pandas. However, our implementation did not scale well, as we did a loop within a loop for our merge.
As the data size increased, our Rust code ended up being slower. In previous chapters, we have shown multiple times that Rust implementations are generally faster. However, this does not counteract the effects of bad code implementation. If you are relying...
