the point of using swift is to be faster than Python. if your computations are using numpy and most of your time is spent in these computations, passing through the python interpreter every time, it's going to have performance similar Python
> the point of using swift is to be faster than Python
There are plenty of other compelling reasons to prefer Swift over Python such as its type system or its easy, somewhat native, integration with existing Swift, Objective-C, and C frameworks available for macOS, iOS, watchOS, and tvOS.
Speed isn't the only driver, and I'm sure not it's not "the [only] point".
no I meant for data science applications specifically, sorry
You can alternatively import Python and use NumPy directly, as well as any other C library, or you can define numeric operations in Swift. (On the other hand, if you are using fixed-size 3x3 or 4x4 matrices, the simd_floatNxN types deliver vastly better performance than NumPy can. So it depends on what your goals are.)