Hi, I am new to SqlAlchemy and like it very much.
I want to use it on a pretty acient database schema, wich has prefixed all column names with a unique prefix for that table. E.g.: address_table = Table('a_address', metadata, Column('A_ID', Integer, primary_key=True), Column('A_VAT_ID', Integer), # TODO: link entries Column('A_C_ID', Integer), Column('A_Company_A_ID', Integer), Column('A_P_ID', Integer), Column('A_LOC_ID', Integer, ForeignKey('loc_location.LOC_ID')), Column('A_VC_ID', Integer), Column('A_Descr', String(50)), Column('A_Name', String(100)), Column('A_Name2', String(100)), Column('A_Department', String), Column('A_Street', String), Column('A_ZipCode', String(20)), Column('A_City', String(50)), Column('A_State', String(50)), Column('A_PObox', String(20)), Column('A_POboxZipCode', String(20)), Column('A_POboxCity', String(50)), Column('A_TelPrefix', String(30)), Column('A_TelExt', String(10)), Column('A_Tel2', String(50)), Column('A_FaxPrefix', String(30)), Column('A_FaxExt', String(10)), Column('A_Fax2', String(50)), Column('A_Mobile', String(50)), Column('A_EMail', String(80)), Column('A_VATID', String(30)), Column('A_LastSeen', Date), Column('A_Timestamp', DateTime), ) When I now map a class to the table like: class Address(object): pass mapper(Address, address_table) It now does the expected and maps all the 'A_*' fields into the class. My question now is, whether it is possible, to automatically remove (or create additional properties) the 'A_' prefix of the created properties and transform the all to lowercase. So that e.g. a city or street property would be available and be mapped to the correspoinding databasefields. Sorry, if this question seems noobish, but I just want to avoid redundant typing of all the fields... cheers Richard -- You received this message because you are subscribed to the Google Groups "sqlalchemy" group. To post to this group, send email to sqlalch...@googlegroups.com. To unsubscribe from this group, send email to sqlalchemy+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/sqlalchemy?hl=en.