How can I estimate the goodness of fit of a nonlinear model in Python?

I have some data that I have fitted to a Weibull distribution and now I want to calculate the goodness of fit.

At first I tried using the Kolmogorov-Smirnov test but I have read that this doesn't give a valid result when the parameters that I consider for the distribution are obtained from the data. Then I considered calculation the $R^2$ coefficient but then I also read that this can't be used to asses the goodness of a nonlinear fit.

More or less those are the statistical tests that I know how to use and remember from my last course in statistics. Which test could I run in this case to assess the goodness of fit of the Weibull distribution to my data?

It would be even better if that test was already a well established Python function.