python - Improve loop efficiency -

i have 21,000 rows i'm pulling sqlite3 database, , need put dictionary appended array. loop takes 1.531 seconds, , i'm trying minimize as can. what's faster way can this? (i using python 2.7.3)

results = cursor.fetchall() array = [] row in results:     = {}     b = row[11]     c = str(row[8])     d = str(row[9]) + " ? " + str(row[10])     e = row[3]     f = row[4]     key = e + " - " + f      rowtoadd = { 'aaa': row[3],                 'bbb' : row[0],                 'ccc' : row[1],                  'ddd' : row[12],                 'eee' : row[2],                 'fff' : row[9],                 'ggg' : row[1],                 'hhh' : str(row[6]) + " (" + str(row[5]) + ")",                 'iii' : e,                 'jjj' : d,                 'kkk' : f     }      rowtoadd.append(array) 

is there way directly map cursors output list of dictionaries custom keys?

is there more pythonic way speed up?

leave concatenations sqlite instead, , use sqlite3.row row factory instead, gives object can used both tuple , dictionary.

have query name keys using column aliases:

cursor.execute('''     select          col3 aaa, col9 bbb,         col6 || ' (' || col5 || ')' hhh,         col9 || ' ? ' || col10 jjj     some_table ''') 

then use result instead of building new list. if must have list these can use:

array = cursor.fetchall() 

or

array = list(cursor) 

but better of iterating on results need have access rows.