conn.commit()
在每个数据库更改之后,是否在过程结束时调用一次取决于几个因素。
这是每个人乍一看的想法:提交对数据库的更改后,该更改对于其他连接变为可见。除非提交,否则更改仅在本地可见。由于的有限并发功能sqlite
,只能在打开事务时读取数据库。
import os
import sqlite3
_DBPATH = "./q6996603.sqlite"
def fresh_db():
if os.path.isfile(_DBPATH):
os.remove(_DBPATH)
with sqlite3.connect(_DBPATH) as conn:
cur = conn.cursor().executescript("""
CREATE TABLE "mytable" (
"id" INTEGER PRIMARY KEY AUTOINCREMENT, -- rowid
"data" INTEGER
);
""")
print "created %s" % _DBPATH
# functions are syntactic sugar only and use global conn, cur, rowid
def select():
sql = 'select * from "mytable"'
rows = cur.execute(sql).fetchall()
print " same connection sees", rows
# simulate another script accessing tha database concurrently
with sqlite3.connect(_DBPATH) as conn2:
rows = conn2.cursor().execute(sql).fetchall()
print " other connection sees", rows
def count():
print "counting up"
cur.execute('update "mytable" set data = data + 1 where "id" = ?', (rowid,))
def commit():
print "commit"
conn.commit()
# Now the script
fresh_db()
with sqlite3.connect(_DBPATH) as conn:
print "--- prepare test case"
sql = 'insert into "mytable"(data) values(17)'
print sql
cur = conn.cursor().execute(sql)
rowid = cur.lastrowid
print "rowid =", rowid
commit()
select()
print "--- two consecutive w/o commit"
count()
select()
count()
select()
commit()
select()
print "--- two consecutive with commit"
count()
select()
commit()
select()
count()
select()
commit()
select()
输出:
$ python try.py
created ./q6996603.sqlite
--- prepare test case
insert into "mytable"(data) values(17)
rowid = 1
commit
same connection sees [(1, 17)]
other connection sees [(1, 17)]
--- two consecutive w/o commit
counting up
same connection sees [(1, 18)]
other connection sees [(1, 17)]
counting up
same connection sees [(1, 19)]
other connection sees [(1, 17)]
commit
same connection sees [(1, 19)]
other connection sees [(1, 19)]
--- two consecutive with commit
counting up
same connection sees [(1, 20)]
other connection sees [(1, 19)]
commit
same connection sees [(1, 20)]
other connection sees [(1, 20)]
counting up
same connection sees [(1, 21)]
other connection sees [(1, 20)]
commit
same connection sees [(1, 21)]
other connection sees [(1, 21)]
$
因此,这取决于您是否可以忍受这样的情况:同一个读者(无论是在同一脚本中还是在另一个程序中)有时会减少两个。
当要进行大量更改时,其他两个方面进入了场景:
数据库更改的性能在很大程度上取决于您执行更改的方式。它已经作为常见问题解答指出:
实际上,在普通的台式计算机上,sqlite每秒可以轻松地执行50,000个或更多的INSERT语句。但是它每秒只能进行几十笔交易。[…]
在这里了解详细信息绝对有帮助,因此请不要犹豫,点击链接并深入研究。另请参见此令人敬畏的分析。它是用C编写的,但结果将是相似的,而在Python中也是如此。
注意:虽然两个资源都引用INSERT
,但是UPDATE
对于相同的参数,情况将非常相似。
如上所述,一个打开的(未提交的)事务将阻止并发连接的更改。因此,通过执行更改并联合提交全部更改,将对数据库的许多更改捆绑到单个事务中是很有意义的。
不幸的是,有时计算更改可能需要一些时间。当并发访问成为问题时,您将不需要锁定数据库那么长时间。因为它可以成为相当棘手收集挂起UPDATE
和INSERT
语句不知何故,这通常会留给你的性能和独特的锁定之间的权衡。