Nice, I haven't gone through all details. That's a nice new "missing" feature, maybe all instances where we can't find a conversion should be "nan". A few comments:
1. The "load_search" functions contains all memory/performance overhead that we wanted to avoid with the fromiter function. Does this mean that you no longer have large text-files that change sting representation in the columns (aka "0" floats) ? 2. ident=" "*4 This has the same spelling error as in my first compile try .. it was meant to be "indent" 3. types = list((i,j) for i, j in zip(varnm, types2)) Isn't this the same as "types = zip(varnm, types2)" ? 4. return N.fromiter(iter(reader),dtype = types) Isn't "reader" an iterator already? What does the "iter()" operator do in this case? Best regards, //Torgil On 7/18/07, Vincent Nijs <[EMAIL PROTECTED]> wrote: > > I combined some of the very useful comments/code from Tim and Torgil and > came-up with the attached program to read csv files and convert the data > into a recarray. I couldn't use all of their suggestions because, frankly, I > didn't understand all of them :) > > The program use variable names if provided in the csv-file and can > auto-detect data types. However, I also wanted to make it easy to specify > data types and/or variables names if so desired. Examples are at the bottom > of the file. Comments are very welcome. > > Thanks, > > Vincent > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > > > _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
