Parallelization support via future.apply

[ck37]

Hello,

Here is a small patch to support parallel processing for test_consequences_data_frame(). When it takes longer to calculate those stats, such as larger dataframes, more granular thresholds, and/or more models, this can have a nice speedup and I think the extra complexity is pretty minimal. For my current dataset this lets me go from 7 minutes to 45 seconds to run a dca(), so pretty helpful.

Happy to make any additional changes as preferred.

Cheers,
Chris

[ddsjoberg]

HI @ck37 ! Thanks for the post!

I am not sure when I'll get to this. I certainly see the benefit (quite obvious in this case). I need to consider deeply adding additional dependencies, particularly for functionality I have not used/not familiar with. (Well, I think I used it in grad school, but quickly forgot it!) I am sure you know, by accepting the PR, I am also signing up for maintaining the new code...forever.

[ddsjoberg]

Hi @ck37 , I am making a maintenance release of this package soon, which got me thinking again about your PR. Unfortunately, I don't think I want to take on the maintenance burden of the parallelization because I will find it difficult to continue to support into the future. I hope you understand.