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Python Open Source United States

Finance, Scientific Users Get ActivePython Updates 131

jcasman sends along this clip from PCWorld: "ActiveState has added three open source mathematics libraries to its ActivePython Python distribution that might interest financial and scientific computing markets, the company announced Thursday. The packages are being added, in part, to anticipate the demand that may arise from new proposed rules for the US financial community brought about by the US Securities and Exchange Commission. ... In April, the government agency posted a set of proposed rules for handling asset-backed securities that called for financial firms to disclose, along with their prospectus filings, the source code of the programs that generated the filings, as rendered in Python. The government agency will be accepting input about the proposed rule until August 2. The three libraries that are being added to the ActivePython package are NumPy, SciPy, and matplotlib."
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Finance, Scientific Users Get ActivePython Updates

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  • Re:Great! (Score:4, Interesting)

    by eldavojohn ( 898314 ) * <(eldavojohn) (at) (> on Friday June 25, 2010 @11:54AM (#32691594) Journal

    For about an average of half the lines of code they might use in C, scientists ...

    Scientists?! You're probably joking but I've been over to accounting and they're using Excel and *shudder* Access for all their heavy data lifting. Sometimes they need help and if they're kind enough I don't lie about how much I know about those ancient products. Most importantly they're not scientists. They're accountants and business people ... they don't care if they have to wait five minutes for Excel to open a worksheet containing the entire set of order histories of our company.

    I don't think these packages are intended for NASA space mission flight certified calculations. Just something to really help you out if you want to comply with the SEC. Side bonus, I'll bet that when you submit this code, you're going to achieve compliance a lot faster when the SEC only has to check half the lines of code and not analyze your memory management ...

    Software development is about trade-offs. Why aren't you complaining that it's not in some targeted processor specific machine language?

  • Re:Great! (Score:3, Interesting)

    by kidtexas ( 525194 ) on Friday June 25, 2010 @12:03PM (#32691710)

    I know bonafide scientists who use Excel for analysis. Scary.

    I also know quite a few who use numpy, scipy, matplotlib, and python for real science. In fact, I think the astro community specifically was an early supporter of some of these packages. I myself have been using them in science for 5 or 6 years.

  • Re:Great! (Score:5, Interesting)

    by Nyeerrmm ( 940927 ) on Friday June 25, 2010 @12:12PM (#32691822)
    Actually, NASA JPL does most of their mission design work using Python (combining compiled C modules of course, just like NumPy and SciPy).
  • Good stuff (Score:4, Interesting)

    by stokessd ( 89903 ) on Friday June 25, 2010 @12:15PM (#32691850) Homepage

    Those packages are fantastic and really 90% of what I use in python are in those packages. I have been using enthought edition python rather than active-state (many reasons), and this tips the scales a bit more toward recommending active-state to others.

    FYI: Matplotlib makes 2D and 3D presentation quality plots of data (even an absurd quantity of data). Numpy and scipy provide scientific and matrix functions that pretty much cut matlab off at the knees unless you are a simulink user. Matlab is many thousands of dollars, python is free, and they are both remarkable similar, except matlab chokes on large data sets where python doesn't.


  • Re:Why not R? (Score:5, Interesting)

    by Daniel Dvorkin ( 106857 ) * on Friday June 25, 2010 @12:39PM (#32692254) Homepage Journal

    Speaking as someone who uses both R and Python all the time, I'd say that while R is very very good at a lot of what it does, it's just not as good as a general-purpose language as Python. I find myself doing as much preprocessing in Python as possible, then saving the results in DB tables and having R finish the analysis. And yes, I know about RPy, but the programming overhead of representing data structures in both languages, and making sure that they're talking to each other correctly, can be considerable; so is the runtime overhead of passing really big data sets back and forth. (Note that it's been a while since I used RPy for anything big, and a lot has been improved in that time, so it may be time for me to give it another shot.) Python code is just cleaner and easier to write for most tasks. I like both languages for their strengths, but overall, if you can do a particular analysis in Python then that's usually the easier choice.

  • by Anonymous Coward on Friday June 25, 2010 @12:41PM (#32692308)

    I don't know how it's moderated Flamebait. As a matter of fact Python is faster at number crunching if you use the appriate libraries (scipy,numpy). These are highly optimized C libraries, and they don't treat numbers as objects. (And you don't use the builtin operators on them either.) And as a matter of fact when Python calls C libs, it has less an overhead than when Java does it. (However, by now Java has some similar scientific packages as well, but they aren't as high profile as numpy and scipy.)

    I can't find a benchmark to prove my point, but this is the common knowledge in most forums.

  • Re:Why not R? (Score:4, Interesting)

    by GlobalEcho ( 26240 ) on Friday June 25, 2010 @01:45PM (#32693514)

    Mod parent up!

    I also use both, quite heavily. Rpy2 is a real improvement over RPy, but I share your preference for allocating tasks to the two languages according to their strengths, and the rpy/rpy2 data structure representations are much trickier than I like.

    I find myself gravitating to R when the builtins are useful (robust estimation, smoothing kernels), where I need to split and analyze data subsets (using by() and its cousins) or where I want to plot things. Python is the ticket for interfacing with C, talking to the outside world, parsing, and expression of simple mathematical models.

  • Re:Great! (Score:2, Interesting)

    by WeatherGod ( 1726770 ) on Friday June 25, 2010 @03:01PM (#32694610)
    You know, it is still possible to write bad code in Python... I use these packages on a daily basis, and while I wouldn't use them for production-level numerical weather prediction system, I do use it for data processing and such. There have been times when I wrote the code poorly and the code ran slowly, but as I learned Python and embraced the language (weaning myself away from C), I found myself writing faster programs. Which high-level language features do you think are lacking? I particularly like list comprehensions and the function argument syntax (positional and keyword-based).

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