Thank's for the quick response. Here are some thought's around it that might make my context clearer. Dan Serban schrieb am 22.07.2014 11:16:
Like you said, Haskell is a platform, and people don't use a specific platform for the sake of using *that* platform. They use it because of what we call a "killer app".
That might be a reason sometimes but I don't think it's the only one. In my case – I tried to describe this a little bit – it is the platform that I want to use because the platform, or better programming language makes me approach a problem in a certain way (makes me think and code in that way). My interest in using Haskell is because it is, in my very limited view on this, the most convincing expression of functional programming paradigms and what I read about functional programing in Python was not really convincing. So it is not a specific library but the design of the language that makes me consider learning Haskell. And further more it is the general idea that a functional style of coding has important advantages for complying to to certain best practice rules of scientific communication when "speaking code" in the context of multi-modal publications, like for example published IPython Notebooks or (outside of science) in data stories of data driven journalism.
I'm not really clear what "topic modeling" entails, but it sounds like something Haskell's type system might be well suited for. Sophisticated visualizations? D3.JS is the answer. (Diagrams has the wrong power-to-weight ratio here, IMO, especially if you're new to Haskell.)
thx for the overview D3 is exactly what I use already and when there is an easy way to integrate it with Haskell that's awesome.
If you're dealing with dirty data, it sounds like a good idea to attempt to discover the invariants your data is subject to. Learn how to extract synthetic key indicators from your data, then use Haskell's QuickCheck to either discover those subtle universal properties hidden within the data, or make assertions about them, in order to verify the consistency of a data set.
thx aslo for the mentioning these general strategies.
Finally, I'd say don't look at this as a black and white decision. If you can get away with it, make it a hybrid Python/Haskell project and leverage the best of each world.
I thin the reason why I am framing this in a way of a black/white problem is the fact that it means a certain effort to experience the limits of the ecosystem for a certain programming language and that time resources are limited (I work half-time, do my PhD halftime and have two kids, so always something to do ;-)) So I try to evaluate before. Second reason for a black/white attitude is exactly the argument that the background for the decision is not so much about using this and that library but about think, code and publish in an environment of functional programming, the decision to spent the rare time to get deeper into the Python ecosystem which makes many things easier but but has the general disadvantages I tried to address or spent it to make myself familiar with Haskell the design of a programming language where I am 100% convinced but which make things a little bit harder to get because the community is smaller and not related to DH. By the way, how easy is it to interface python or C libraries from within Haskell – this possibility would be a good argument or did you mean something like this when talking about a hybrid approach? best Niels-Oliver
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