Re:How Python became the language of choice for data science
by xixi77 on Friday November 22, 2013 @11:37AM
(#6781808)
The syntax is sensible, the language allows real OO and FP abstractions, you have easy access to basic data structures like lists and hashmaps, and there's a huge ecosystem of third-party libraries to build on
Other than the last one, all of these are available in Matlab and R as well; and all three have a huge set of libraries -- the difference is about the focus of those libraries imo. Python does have more general-purpose libraries, just as R has more statistical packages.
I have certainly run a lot Matlab on a cluster, in fact, I'd say safely about 70% of code I see running on clusters around here is Matlab. I've also seen a few production systems in (mostly) R -- I actually suspect that at least on Windows, deploying an R system may be easier, since you just install R and then use internal functionality to get packages you need; python (with all necessary extensions) seems relatively tricky to get running.
All that being said, I do agree that if you are building a production system where most of the code is related to interfacing with other systems, or GUI's etc., and the data analysis is a small and non-interactive part (ie. no data exploration), Python is a very reasonable choice if you can keep the whole project in it.
Other than the last one, all of these are available in Matlab and R as well; and all three have a huge set of libraries -- the difference is about the focus of those libraries imo. Python does have more general-purpose libraries, just as R has more statistical packages.
I have certainly run a lot Matlab on a cluster, in fact, I'd say safely about 70% of code I see running on clusters around here is Matlab. I've also seen a few production systems in (mostly) R -- I actually suspect that at least on Windows, deploying an R system may be easier, since you just install R and then use internal functionality to get packages you need; python (with all necessary extensions) seems relatively tricky to get running.
All that being said, I do agree that if you are building a production system where most of the code is related to interfacing with other systems, or GUI's etc., and the data analysis is a small and non-interactive part (ie. no data exploration), Python is a very reasonable choice if you can keep the whole project in it.