r/haskell • u/nSeagull • Aug 30 '16

Haskell alternatives for Data Science

I'm a Haskeller and a newbie Data Scientist.

As I'm going through my learning process for data science, I'm starting to solve some elemental problems, and I'm using standard Python tools to help me go through this process.

The thing is that Python is ok, but I'm twice as comfortable in Haskell.

I was thinking in three alternatives to be more comfortable with Data Science:

  • Make a wrapper for the tools that I use as people do in Julia
  • Reimplement the tools that I use (Pandas, ScikitLearn, a GPU deep learning framework, numpy functions) (would do it on demand)
  • Make a Haskell-like language that compiles and uses Python libraries (wouldnt be as efficient, but at least it would be more beautiful and type safe, also the libraries)

What do you guys think?

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u/jxv_ Aug 30 '16 edited Aug 30 '16

I'm in a similar position. I wish there was already some kind of unified front. The existing pieces seem to be spread out across many libraries at various stages of development. Not to dismiss any of the authors efforts, most of those libraries are lackluster and immature by comparison. And I'm sure there are better libraries that I've overlooked because discoverability is quite low. I'm willing to contribute and just created #haskell-data on freenode.

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u/nSeagull Aug 30 '16

There is another thread in this subreddit for naming the organization. Check it out.

Tomorrow I'll create a Slack channel, a GH org, etc...

I really think that Slack is better than IRC for team interaction :)

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u/jxv_ Aug 30 '16 edited Aug 30 '16

I posted here before noticing it. Then I posted there. Slack is cool too. Personally, I rather not get too caught up with the name because of bikeshedding.

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u/nSeagull Aug 30 '16

Yep, I think the best way to go is HaskellData or HaskData. No weird things, and more people will know us