Many of the top 50 python libraries are wrapping a lot of code that is actually c, c++ or fortran. So I doubt that there is a lot of performance to be gained. Numpy is a good examples for that.
I have applied for a job at a company where they were switching from Python to Rust, because even though they were using Numpy, there was a lot of overhead in setting the data up to send to Numpy.