[oivey]

I wouldn’t say that Julia is gradually typed in the same way that Cython or Numba is. In my experience you usually improve performance by ensuring that your functions handle different types generically. One example of that is making sure the compiler can infer the types of all your variables to something more specialized than the Any type. Another example is being careful to avoid accidental type changes by e.g. summing a Float32 with a Float64 literal.

As I’ve learned the language it’s become pretty easy to avoid those pitfalls even on initial implementations. That said, providing types in function signatures is still very useful for multiple dispatch and providing a more usable API in libraries.