python框架---->pymysql的使用
這里面學習一下python中操作mysql的第三方庫pymysql的使用。很多我們以為一輩子都不會忘掉的事情，就在我們念念不忘的日子里．被我們遺忘了．
pymysql的簡單使用
我們創建一張表來進行下述案例的測試。創建表的語句：
CREATE TABLE `springlearn`.`user` ( `user_id` INT NOT NULL AUTO_INCREMENT, `username` VARCHAR(45) NULL, `password` VARCHAR(45) NULL, PRIMARY KEY (`user_id`));
一、pymysql的簡單使用
pymysql的安裝：pip install PyMySQL。下面我們對官方文檔的例子做一些修改，代碼如下
import pymysql.cursors
# Connect to the database
connection = pymysql.connect(host='localhost',
user='root',
password='chenhui',
db='springlearn',
charset='utf8mb4',
cursorclass=pymysql.cursors.DictCursor)
try:
with connection.cursor() as cursor:
# Create a new record
sql = "INSERT INTO `user` (`username`, `password`) VALUES (%s, %s)"
effect_count = cursor.execute(sql, ('huhx', '123456'))
print('effect counts = %d.' % effect_count)
# connection is not autocommit by default. So you must commit to save your changes.
connection.commit()
with connection.cursor() as cursor:
# Read a single record
sql = "SELECT `user_id`, `password` FROM `user` WHERE `username`=%s"
cursor.execute(sql, ('huhx',))
result = cursor.fetchone()
print(result)
finally:
connection.close()
# effect counts = 1.
# {'user_id': 1, 'password': '123456'}
首先我們創建數據庫的連接：pymysql.connect()。connect的參數可以在http://pymysql.readthedocs.io/en/latest/modules/connections.html里面看到詳細的介紹。connect方法里面指定的cursorclass，python中有以下的幾種Cursor提供我們使用。詳細文檔可以參考：http://pymysql.readthedocs.io/en/latest/modules/cursors.html。以下是關于Cursor的一些簡單介紹。
Cursor：class pymysql.cursors.Cursor(connection)
調用存儲過程：callproc
callproc(procname, args=())
Execute stored procedure procname with args procname – string, name of procedure to execute on server args – Sequence of parameters to use with procedure Returns the original args.
游標的關閉： close()
Closing a cursor just exhausts all remaining data.
普通執行：execute()
execute(query, args=None)
Execute a query
Parameters:
query (str) – Query to execute.
args (tuple, list or dict) – parameters used with query. (optional)
Returns:
Number of affected rows
Return type:
int
If args is a list or tuple, %s can be used as a placeholder in the query. If args is a dict, %(name)s can be used as a placeholder in the query.
批量執行：executemany()
executemany(query, args)
Run several data against one query
Parameters:
query – query to execute on server
args – Sequence of sequences or mappings. It is used as parameter.
Returns:
Number of rows affected, if any.
This method improves performance on multiple-row INSERT and REPLACE. Otherwise it is equivalent to looping over args with execute().
獲取記錄數據的方法：
fetchall()：獲取所有的記錄
Fetch all the rows fetchmany(size=None)：獲取指定數目的記錄
Fetch several rows fetchone()：獲取一條記錄
Fetch the next row
class pymysql.cursors.SSCursor(connection)
Unbuffered Cursor, mainly useful for queries that return a lot of data, or for connections to remote servers over a slow network.
Instead of copying every row of data into a buffer, this will fetch rows as needed. The upside of this is the client uses much less memory, and rows are returned much faster when traveling over a slow network or if the result set is very big.
There are limitations, though. The MySQL protocol doesn’t support returning the total number of rows, so the only way to tell how many rows there are is to iterate over every row returned. Also, it currently isn’t possible to scroll backwards, as only the current row is held in memory.
class pymysql.cursors.DictCursor(connection)
A cursor which returns results as a dictionary
class pymysql.cursors.SSDictCursor(connection)
An unbuffered cursor, which returns results as a dictionary
我們在下面開始我們對上述方法的測試。
pymysql的詳細使用
我們的數據庫數據現在有三條記錄，如下：
| 1 | huhx | 123456 |
| 2 | linux | 234567 |
| 3 | tomhu | 345678 |
一、fetchall，fetchone和fetchmany方法
查詢的sql是：sql = "select * from USER"。以下的方法不是同時執行的結果，因為cursor會向后移動的。
for item in cursor.fetchmany(2):
print(item)
# {'user_id': 1, 'username': 'huhx', 'password': '123456'}
# {'user_id': 2, 'username': 'linux', 'password': '234567'}
print(cursor.fetchone())
print(cursor.fetchone())
# {'user_id': 1, 'username': 'huhx', 'password': '123456'}
# {'user_id': 2, 'username': 'linux', 'password': '234567'}
for item in cursor.fetchall():
print(item)
# {'user_id': 1, 'username': 'huhx', 'password': '123456'}
# {'user_id': 2, 'username': 'linux', 'password': '234567'}
# {'user_id': 3, 'username': 'tomhu', 'password': '345678'}
二、我們重點說一下executemany方法
executemany對于批量的插入是有效的，對于其它的調用這個方法。是循環的執行而不是批量的插入。
批量的數據可以是一個dict：
sql = "insert into user(username, password) VALUES (%(username)s, %(password)s)"
dict1 = {'username': 'liu', 'password': 'ling'}
dict2 = {'username': 'chen', 'password': 'hui'}
data_list = [dict1, dict2]
cursor.executemany(sql, data_list)
connection.commit()
批量的數據可以是一個元祖：
sql = "insert into user(username, password) VALUES (%s, %s)"
data1 = ('chen', 'hui')
data2 = ('liu', 'ling')
data_list = [data1, data2]
cursor.executemany(sql, data_list)
connection.commit()
下面我們對executemany方法的源碼做一些分析：
RE_INSERT_VALUES = re.compile(
r"s*((?:INSERT|REPLACE)s.+sVALUES?s+)" +
r"((s*(?:%s|%(.+)s)s*(?:,s*(?:%s|%(.+)s)s*)*))" +
r"(s*(?:ON DUPLICATE.*)?);?s*",
re.IGNORECASE | re.DOTALL)
def executemany(self, query, args): # type: (str, list) -> int """Run several data against one query :param query: query to execute on server :param args: Sequence of sequences or mappings. It is used as parameter. :return: Number of rows affected, if any. This method improves performance on multiple-row INSERT and REPLACE. Otherwise it is equivalent to looping over args with execute(). """ if not args: return m = RE_INSERT_VALUES.match(query) if m: q_prefix = m.group(1) % () q_values = m.group(2).rstrip() q_postfix = m.group(3) or '' assert q_values[0] == '(' and q_values[-1] == ')' return self._do_execute_many(q_prefix, q_values, q_postfix, args, self.max_stmt_length, self._get_db().encoding) self.rowcount = sum(self.execute(query, arg) for arg in args) return self.rowcount
首先對我們的sql做正則的判斷，如果不是insert或者replace，那么就是循環的執行execute方法。而不是批量的執行，下面我們重點看一下批量的執行流程：_do_execute_many方法
def _do_execute_many(self, prefix, values, postfix, args, max_stmt_length, encoding):
conn = self._get_db()
escape = self._escape_args
if isinstance(prefix, text_type):
prefix = prefix.encode(encoding)
if PY2 and isinstance(values, text_type):
values = values.encode(encoding)
if isinstance(postfix, text_type):
postfix = postfix.encode(encoding)
sql = bytearray(prefix)
args = iter(args)
v = values % escape(next(args), conn)
if isinstance(v, text_type):
if PY2:
v = v.encode(encoding)
else:
v = v.encode(encoding, 'surrogateescape')
sql += v
rows = 0
for arg in args:
v = values % escape(arg, conn)
if isinstance(v, text_type):
if PY2:
v = v.encode(encoding)
else:
v = v.encode(encoding, 'surrogateescape')
if len(sql) + len(v) + len(postfix) + 1 > max_stmt_length:
rows += self.execute(sql + postfix)
sql = bytearray(prefix)
else:
sql += b','
sql += v
rows += self.execute(sql + postfix)
self.rowcount = rows
return rows
以上的操作其實就是根據cursor.executemany(sql, data_list)的參數sql和data_list，拼接成一條sql語句。例如：
INSERT INTO `springlearn`.`user` (`username`, `password`) VALUES ('liu', 'ling'),('chen', 'hui');
當然這種語法并不是所有的數據庫都支持的，oracle就不支持這種的批量插入。executemany方法返回生效的行數。
友情鏈接
connect的參數可以在http://pymysql.readthedocs.io/en/latest/modules/connections.html
詳細文檔可以參考：http://pymysql.readthedocs.io/en/latest/modules/cursors.html
總結
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