sql >> Databasteknik >  >> RDS >> Mysql

Hur jämför man två listor och slår ihop dem i Python/MySQL?

Okej, låt oss ha lite kul...

mysql> create table so (a int, b char, c char, d char, e char, f char, `key` int, dupe char);
Query OK, 0 rows affected (0.05 sec)

mysql> insert into so values (1, 'd', 'c', 'f', 'k', 'l', 1, 'x'), (2, 'g', null, 'h', null, 'j', 1, null), (3, 'i', null, 'h', 'u', 'u', 2, null), (4, 'u', 'r', null, null, 't', 2, 'x');
Query OK, 4 rows affected (0.00 sec)
Records: 4  Duplicates: 0  Warnings: 0

mysql> select * from so order by a;
+------+------+------+------+------+------+------+------+
| a    | b    | c    | d    | e    | f    | key  | dupe |
+------+------+------+------+------+------+------+------+
|    1 | d    | c    | f    | k    | l    |    1 | x    |
|    2 | g    | NULL | h    | NULL | j    |    1 | NULL |
|    3 | i    | NULL | h    | u    | u    |    2 | NULL |
|    4 | u    | r    | NULL | NULL | t    |    2 | x    |
+------+------+------+------+------+------+------+------+
4 rows in set (0.00 sec)
Python 2.6.5 (r265:79063, Mar 26 2010, 22:43:05) 
[GCC 4.2.1 (Apple Inc. build 5646) (dot 1)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import MySQLdb
>>> db = MySQLdb.connect(host="127.0.0.1", db="test")
>>> c = db.cursor()
>>> c.execute("SELECT a, b, c, d, e, f, `key`, dupe FROM so")
4L
>>> rows = c.fetchall()
>>> rows
((1L, 'd', 'c', 'f', 'k', 'l', 1L, 'x'), (4L, 'u', 'r', None, None, 't', 2L, 'x'), (2L, 'g', None, 'h', None, 'j', 1L, None), (3L, 'i', None, 'h', 'u', 'u', 2L, None))
>>> data = dict()
>>> for row in rows:
...  key, isDupe = row[-2], row[-1]
...  if key not in data:
...   data[key] = list(row[:-1])
...  else:
...   for i in range(len(row)-1):
...    if data[key][i] is None or (not isDupe and row[i] is not None):
...     data[key][i] = row[i]
... 
>>> data
{1L: [2L, 'g', 'c', 'h', 'k', 'j', 1L], 2L: [3L, 'i', 'r', 'h', 'u', 'u', 2L]}



  1. Få flera värden i SQL Server Cursor

  2. Hur man tar bort lagrad procedur i MySQL

  3. Använder Geekbench 3.2 för att testa stora databasservrar

  4. Sphinx Search / MySQL hitta de vanligaste orden