feat: add support for pd.DataFrame, np.ndarray and np.recarray to random_sample

[hollandjg]

No description provided.

[younesStrittmatter]

This makes a lot of sense, but it begs the question, what do we do with all the other experimentalists? I think we should not require them to be coded in the same way. Especially for outside contributors. Maybe there is a way to build wrappers that convert input to the input necesarry for the experimentalist and then back, so that other experimentalists also support all these datatypes?

[hollandjg]

This makes a lot of sense, but it begs the question, what do we do with all the other experimentalists? I think we should not require them to be coded in the same way. Especially for outside contributors. Maybe there is a way to build wrappers that convert input to the input necesarry for the experimentalist and then back, so that other experimentalists also support all these datatypes?

Yes, that's a really good point. I'm not sure the best way to do that – what the overarching method should be to do that. I've done an additional example – the random_experimentalist using the state mechanism.

- #21

We can look for the common code between those two, or see a better way to wrap them. Any ideas on what a good interface would look like? If we have a good interface (i.e. how the wrapper function should feel, and how the wrapped function should act) then we can work out how to implement it.

[hollandjg]

superseded by #28