Talk:Open writing projects/Python all a scientist needs: Difference between revisions
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[[User:Adrian Del Maestro|Adrian Del Maestro]] 15:04, 24 February 2008 (EST): Very nice article on the scientific uses of python. Using python to produce publication quality plots via matplotlib has saved me hours of time as the scope and results of a project evolve. I also enjoyed your comments on data provenance, which is an very important topic that many scientists doing numerics are somewhat cavalier about. | |||
My usual approach to large numerical projects is to use python as a scripting glue for analysis, provenance and plotting of data produced using large scale c++ codes. After reading the article, I think that I will attempt to do all my prototyping, coding and profiling completely in python, then use SWIG where appropriate for my next numerical project. | |||
One thing that might be helpful for scientists that are new to python would be some more elaborate discussion on the confusion surrounding the various array packages (i.e. numarray vs. numpy etc.) | |||
Great work, keep the articles coming! | |||
Revision as of 13:04, 24 February 2008
Please Leave A Comment
Adrian Del Maestro 15:04, 24 February 2008 (EST): Very nice article on the scientific uses of python. Using python to produce publication quality plots via matplotlib has saved me hours of time as the scope and results of a project evolve. I also enjoyed your comments on data provenance, which is an very important topic that many scientists doing numerics are somewhat cavalier about.
My usual approach to large numerical projects is to use python as a scripting glue for analysis, provenance and plotting of data produced using large scale c++ codes. After reading the article, I think that I will attempt to do all my prototyping, coding and profiling completely in python, then use SWIG where appropriate for my next numerical project.
One thing that might be helpful for scientists that are new to python would be some more elaborate discussion on the confusion surrounding the various array packages (i.e. numarray vs. numpy etc.)
Great work, keep the articles coming!
