Hi, During my implementation of support for numpy in PyTables, I've concluded that the current support for object flavor (you know, the additional conversion that can automatically make PyTables from native numarray objects to other objects) is getting a bit messy.
Hereby is a proposal for reducing the number of different flavors in PyTables to a bare minimum. Current FLAVOR values: "NumArray" - Homogeneous numerical numarray objects "CharArray" - Multidimensional strings numarray objects "Numeric" - Numeric object "List" - Python list of objects "Tuple" - Python tuple of objects "String" - Python string "Int" - Python integer "Float" - Python float Proposed FLAVOR values: "numarray" - All kind of numarray objects, i.e. homog., heter., strings "numpy" - All kind of numpy objects, i.e. homog., heter., strings "numeric" - Homogeneous Numeric objects "python" - Python objects (list or scalars) I think that this simplification can be made because the metadata about the objects on disk can inform about what kind of data they are (scalar/multidimensional, character-based, homogeneous/heterogeneous) so, in the end, with just the four of aforementioned flavors would be more than enough to deal with the different object conversions. If I get no objections/suggestions on the new schema, I'll proceed to implement it right now and update the documentation accordingly. This will imply that if any of you are making extensive use of the flavor mechanism, then chances are that you should update your source files. This is the price to pay for the simplification. I'll try, however, to make the change as backward compatible as possible, so that files with old values of flavors can properly be read in the new version of PyTables. Cheers, -- >0,0< Francesc Altet http://www.carabos.com/ V V Cárabos Coop. V. Enjoy Data "-" ------------------------------------------------------- This SF.net email is sponsored by: Splunk Inc. Do you grep through log files for problems? Stop! Download the new AJAX search engine that makes searching your log files as easy as surfing the web. DOWNLOAD SPLUNK! http://sel.as-us.falkag.net/sel?cmd=lnk&kid3432&bid#0486&dat1642 _______________________________________________ Pytables-users mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/pytables-users
