file_path_from_db_id.py

def file_path_from_db_id(db_id, pattern="blah_%d.png", top="/path/to/imgs"):
    """Return file path /top/yyy/xx/blah_zzzxxyyy.png for db_id zzzxxyyy.
    
      The idea is to hash into 1k top level dirs, 000 - 999, then 100
      second level dirs, 00-99, so that the following database ids
      result in the associated file paths:
    
      1234567     /path/to/imgs/567/34/blah_1234567.png
          432     /path/to/imgs/432/00/blah_432.png
        29847     /path/to/imgs/847/29/blah_29847.png
         1432     /path/to/imgs/432/01/blah_1432.png

      Notice that changing pattern to pattern="blah_%09d.png" and
      top="" would result in:

      1234567     567/34/blah_001234567.png
          432     432/00/blah_000000432.png
        29847     847/29/blah_000029847.png
         1432     432/01/blah_000001432.png

      In general, this will give a decent spread for up to 100 million images.

      If you have more than 100 million images, or your database ids are
      higher, then this function is easily modified.
    """
    s = '%09d' % db_id
    return os.path.join(top, s[-3:], s[-5:-3], pattern % db_id)