/[thuban]/branches/WIP-pyshapelib-bramz/Thuban/Model/table.py
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revision 1370 by bh, Wed May 28 09:07:30 2003 UTC revision 1371 by bh, Fri Jul 4 18:19:16 2003 UTC
# Line 413  class MemoryTable(TitledObject, OldTable Line 413  class MemoryTable(TitledObject, OldTable
413          self.data[record] = values          self.data[record] = values
414    
415    
416    
417    def _find_dbf_column_names(names):
418        """Determine the column names to use in a DBF file
419    
420        DBF files have a length limit of 10 characters on the column names
421        so when writing an arbitrary Thuban table to a DBF file we may have
422        we may have to rename some of the columns making sure that they're
423        unique in the DBF file too.
424    
425        Names that are already short enough will stay the same. Longer names
426        will be truncated to 10 characters or if that isn't unique it will
427        be truncated more and filled up with digits.
428    
429        The parameter names should be a list of the column names. The return
430        value will be a dictionary mapping the names in the input list to
431        the names to use in the DBF file.
432        """
433        # mapping from the original names in table to the names in the DBF
434        # file
435        name_map = {}
436    
437        # First, we keep all names that are already short enough
438        for i in range(len(names) - 1, -1, -1):
439            if len(names[i]) <= 10:
440                name_map[names[i]] = names[i]
441                del names[i]
442    
443        # dict used as a set of all names already used as DBF column names
444        used = name_map.copy()
445    
446        # Go through all longer names. If the name truncated to 10
447        # characters is not used already, we use that. Otherwise we truncate
448        # it more and append numbers until we get an unused name
449        for name in names:
450            truncated = name[:10]
451            num = 0; numstr = ""
452            #print "truncated", truncated, num
453            while truncated in used and len(numstr) < 10:
454                num += 1
455                numstr = str(num)
456                truncated = name[:10 - len(numstr)] + numstr
457                #print "truncated", truncated, num
458            if len(numstr) >= 10:
459                # This case should never happen in practice as tables with
460                # 10^10 columns seem very unlikely :)
461                raise ValueError("Can't find unique dbf column name")
462    
463            name_map[name] = truncated
464            used[truncated] = 1
465    
466        return name_map
467    
468  def table_to_dbf(table, filename):  def table_to_dbf(table, filename):
469      """Create the dbf file filename from the table"""      """Create the dbf file filename from the table"""
470      dbf = dbflib.create(filename)      dbf = dbflib.create(filename)
# Line 421  def table_to_dbf(table, filename): Line 473  def table_to_dbf(table, filename):
473                           FIELDTYPE_INT: dbflib.FTInteger,                           FIELDTYPE_INT: dbflib.FTInteger,
474                           FIELDTYPE_DOUBLE: dbflib.FTDouble}                           FIELDTYPE_DOUBLE: dbflib.FTDouble}
475    
476    
477        name_map = _find_dbf_column_names([col.name for col in table.Columns()])
478    
479      # Initialise the header. Distinguish between DBFTable and others.      # Initialise the header. Distinguish between DBFTable and others.
480      for col in table.Columns():      for col in table.Columns():
481          width = table.Width(col.name)          width = table.Width(col.name)
# Line 428  def table_to_dbf(table, filename): Line 483  def table_to_dbf(table, filename):
483              prec = getattr(col, "prec", 12)              prec = getattr(col, "prec", 12)
484          else:          else:
485              prec = 0              prec = 0
486          dbf.add_field(col.name, dbflib_fieldtypes[col.type], width, prec)          dbf.add_field(name_map[col.name], dbflib_fieldtypes[col.type],
487                          width, prec)
488    
489      for i in range(table.NumRows()):      for i in range(table.NumRows()):
490          record = table.ReadRowAsDict(i)          record = {}
491            for key, value in table.ReadRowAsDict(i).items():
492                record[name_map[key]] = value
493          dbf.write_record(i, record)          dbf.write_record(i, record)
494      dbf.close()      dbf.close()
495    

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