On 05 Feb 2002 05:31:41 -0800 rossini@blindglobe.net (A.J. Rossini) wrote:
"RB" == Ragnar Beer <rbeer@uni-goettingen.de> writes:
RB> Thanks a lot! RSPython seems to be the most likely candidate RB> for my purposes. I actually don't need R's interactive RB> features in this case. What I need is a Python script that RB> accesses an SQL database, unpickles data that is stored in a RB> blob, and then generates an image (a rather large GIF) with a RB> predefined style or calculates a couple of coefficients. RB> Generating images seems to be the hardest part. How are you RB> handling temporary files with more than one concurrent thread RB> and possible security issues? I've never used temporary files RB> so far.
If you want this to really work, I'd go one further than Seb's "critical" comments (remember, I'm an academic, I can afford crashes, especially of the "crash early, crash often" in research projects :-), and suggest using Python, PIL, or GDchart for this, NOT R. Really, "right tools for the job", "stability", and all that stuff.
Instead, for numerics, I'd suggest NumPy or SciPy (both excellent, though lacking some (all!) of S/R's better features for data analysis and annotation), for the computations.
I've done just as well with Python's SQL methods as I've done with R's (maybe better), and there are a number of Zope products for doing what you are proposing.
Python seems to be a better choice -- I've been doing Flow Cytometry analysis in both R and Python (flow cyt files are like the files you are describing) and Python definitely has better behaviour (not to mention that you'll have a 1-2 second start-up cost server-side for getting R "fired up").
Now if you are looking at incorporating R for a "lab workbench/notebook" style project, that would be a another story...
Hmm, do you mean RSPython shouldn't be used in a production environment because RSPython *itself* isn't ready for production or would it rather be *my* code that'd crash for trial-and-error reasons? Cheers, Ragnar