One of the difficulties we ran into here though was that "lambdify" was built for simplicity and not for speed. You can see this in how it doesn't support thing

One of the difficulties we ran into here though was that "lambdify" was built for simplicity and not for speed. You can see this in how it doesn't support things like lamdification on sparse matrix types. A lot of our applications started with SymPy/SymEngine under the hood, but when push came to shove we had to write a pre Julia symbolic engine (ModelingToolkit) so we could more easily generate fast multithreaded sparse non-allocating functions from symbolic equations (https://mtk.sciml.ai/dev/tutorials/symbolic_functions/#Building-Non-Allocating-Parallel-Functions-for-Sparse-Matrices-1 https://mtk.sciml.ai/dev/tutorials/symbolic_functions/#Build...). SymPy is great though, it's just if you try using it on a million equations, oof haha.