[Haskell-beginners] Motivation to Learn Haskell

Tim Perry perry2of5 at yahoo.com
Fri Sep 3 19:30:21 EDT 2010

You might find this discussion started by a skeptic interesting (I did):

The topic is different, but the responses tell me:
- Lots of library code that I expect to be written already doesn't exist for 
- This isn't so bad as the code you have write is relatively succinct.
- You still have to write the missing code. Which sucks (tm).

I'm using Haskell for lots of one-off data processing. It is generally quick to 
develop. It generally yields type errors rather than gibberish when I write 
something stupid in my code. I recommend it. But I've never used SciPy so I 
can't comment on the relative depth of the libraries.

With all that said, there are are libraries with the obvious statistical 

If you do jump in, I'd recommend the Real World Haskell book or the The Haskell 
School of Expression book.

Good luck,

----- Original Message ----
From: Lorenzo Isella <lorenzo.isella at gmail.com>
To: beginners at haskell.org
Sent: Fri, September 3, 2010 3:57:26 PM
Subject: [Haskell-beginners] Motivation to Learn Haskell

Dear All,
It is my first post to this list and please do not take it as an attempt to 
start any flamewar.
>From time to time, I try to find the motivation to learn at least the 
fundamentals of another programming language.
I normally use R and Python on a daily basis (but I am not that much into OO 
programming) and have a good knowledge of Fortran and a rather superficial one 
of C.
Beside learning a new language as a sort of mind expanding exercise, I try to 
figure out how and if it can save me some time in my work and how it measures up 
against other languages.
These days I tend to rely on R for data analysis and visualization whereas I use 
Python (in particular Numpy+SciPy) for number crunching (it is very convenient 
to use scipy/numpy to solve ODE's, manipulate arrays and so on).
Now, I wonder what benefit I would gain from learning Haskell since I mainly 
write codes for numerical simulations/data analysis.
I know Haskell is gaining momentum e.g. in the financial environment (I happened 
to see Haskell knowledge as a specification in some quant jobs) hence it must be 
more than suitable for numerical work and, by the little I have understood so 
far, it allows one to write code really resembling mathematical expressions (I 
was impressed by guards and curried functions).
However, it also looks to me (correct me if I am mistaken) that Haskell is a far 
cry from the wealth of standard and contributed scientific modules you have in 
Python or R and thanks to which you do not re-implement the wheel yourself.
Any thoughts/suggestions are really appreciated.

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