I have a list of many float numbers, representing the length of an operation made several times. 

For each type of operation, I have a different trend in numbers.

I'm aware of many random generators presented in some python modules, like in numpy.random

For example, I have `binomial`, `exponencial`, `normal`, `weibul`, and so on...

I'd like to know if there's a way to find the best `random generator`, given a list of values, that best fit each list of numbers that I have. 

I.e, the generator (with its params) that best fit the trend of the numbers on the list

That's because I'd like to automatize the generation of time lengths, of each operation, so that I can simulate it during `n` years, without having to find by hand what method fits best what list of numbers.

**EDIT:** In other words, trying to clarify the problem:

I have a list of numbers. I'm trying to find the probability distribution that best fit the array of numbers I already have. The only problem I see is that each probability distribution has input params that may interfer on the result. So I'll have to figure out how to enter this params automatically, trying to best fit the list.

Any idea?