第11章：使用Python打造MySQL专家系统

1.Python语言高级特性

1).深入浅出Python生成器

1).生成器函数：与普通函数定义类似，使用yield语句而不是return语句返回结果。yield语句一次返回一个结果，在每个结果中间挂起函数的状态，以便下次从它离开的地方继续执行
2).生成器表达式：类似于列表推导，但是，生成器返回按需产生结果的一个对象，而不是一次构建一个结果列表
使用生成器的例子，使用生成器返回自然数的平方：
def gensquares(N):
    for i in range(N):
        yield i ** 2

def main():
    for item in gensquares(234):
        print(item)

if __name__ == '__main__':
    main()

使用普通函数实现
def gensquares(N):
    res = []
    for i in range(N):
        res.append(i*i)
    return res

def main():
    for item in gensquares(234):
        print(item)

if __name__ == '__main__':
    main()

2).深入浅出Python装饰器

Python中函数可以赋值给另外一个变量名，函数可以嵌套，以及函数对象可以作为另外一个函数的参数等
1、函数对象
2、嵌套函数
3、装饰器原型
def bread(f):
    def wrapper(*args, **kwargs):
        print("begin")
        f()
        print("end")
    return wrapper

@bread
def say_hi():
    print("Hi")

def main():
    say_hi()

if __name__ == '__main__':
    main()

3).Python上下文管理器

1、with语句形式化定义
2、上下文管理器的应用场景
3、上下文管理器协议

2.MySQL数据库

1).Python连接数据库

import os

if os.getenv('DB', 'MySQL') == 'MySQL':
    import pymysql as db
else:
    import sqlite3 as db

def get_conn(**kwargs):
    if os.getenv('DB', 'MySQL') == 'MySQL':
        return db.connect(host=kwargs.get('host', 'localhost'),
            user=kwargs.get('user'),
            passwd=kwargs.get('passwd'),
            port=kwargs.get('port', 3306),
            db=kwargs.get('db'))
    else:
        return db.connect(database=kwargs.get('db'))

def execute_sql(conn, sql):
    with conn as cur:
        cur.execute(sql)

def create_table(conn):
    sql_drop_table = "DROP TABLE IF EXISTS student"
    sql_create_table = """create table student (sno int(11) not null,sname varchar(20) default null,sage int(11) default null,primary key (sno)) engine=InnoDB default charset=utf8"""
    for sql in [sql_drop_table, sql_create_table]:
        execute_sql(conn, sql)

def insert_data(conn, sno, sname, sage):
    insert_format = "insert into student(sno, sname, sage) values ({0}, '{1}', {2})"
    sql = insert_format.format(sno, sname, sage)
    execute_sql(conn, sql)

def main():
    conn = get_conn(host='127.0.0.1',
               user='root',
               passwd='msds007',
               port=3306,
               db='test')
    try:
        create_table(conn)
        insert_data(conn, 1, 'zhangsan', 20)
        insert_data(conn, 2, 'lisi', 21)
        with conn as cur:
            cur.execute("select * from student")
            rows = cur.fetchall()
            for row in rows:
                print(row)
    finally:
        if conn:
            conn.close()

if __name__ == '__main__':
    main()

2).使用上下文管理器对数据库连接进行管理

import os
from contextlib import contextmanager

if os.getenv('DB', 'MySQL') == 'MySQL':
    import pymysql as db
else:
    import sqlite3 as db

@contextmanager
def get_conn(**kwargs):
    if os.getenv('DB', 'MySQL') == 'MySQL':
        conn = db.connect(host=kwargs.get('host', 'localhost'),
                          user=kwargs.get('user'),
                          passwd=kwargs.get('passwd'),
                          port=kwargs.get('port', 3306),
                          db=kwargs.get('db'))
        try:
            yield conn
        finally:
            if conn:
                conn.close()

def execute_sql(conn, sql):
    with conn as cur:
        cur.execute(sql)

def create_table(conn):
    sql_drop_table = "DROP TABLE IF EXISTS student"
    sql_create_table = """create table student (sno int(11) not null,sname varchar(20) default null,sage int(11) default null,primary key (sno)) engine=InnoDB default charset=utf8"""
    for sql in [sql_drop_table, sql_create_table]:
        execute_sql(conn, sql)

def insert_data(conn, sno, sname, sage):
    insert_format = "insert into student(sno, sname, sage) values ({0}, '{1}', {2})"
    sql = insert_format.format(sno, sname, sage)
    execute_sql(conn, sql)

def main():
    conn_args = dict(host='127.0.0.1',user='root',passwd='msds007',port=3306,db='test')
    with get_conn(**conn_args) as conn:
        create_table(conn)
        insert_data(conn, 1, 'zhangsan', 20)
        insert_data(conn, 2, 'lisi', 21)
        with conn as cur:
            cur.execute("select * from student")
            rows = cur.fetchall()
            for row in rows:
                print(row)

if __name__ == '__main__':
    main()

3).案例：从csv文件导入数据到MySQL

import os
import csv
from collections import namedtuple
from contextlib import contextmanager

if os.getenv('DB', 'MySQL') == 'MySQL':
    import pymysql as db
else:
    import sqlite3 as db

@contextmanager
def get_conn(**kwargs):
    if os.getenv('DB', 'MySQL') == 'MySQL':
        conn = db.connect(host=kwargs.get('host', 'localhost'),
                          user=kwargs.get('user'),
                          passwd=kwargs.get('passwd'),
                          port=kwargs.get('port', 3306),
                          db=kwargs.get('db'))
        try:
            yield conn
        finally:
            if conn:
                conn.close()

def execute_sql(conn, sql):
    with conn as cur:
        cur.execute(sql)

def get_data(file_name):
    with open(file_name) as f:
        f_csv = csv.reader(f)
        headings = next(f_csv)
        Row = namedtuple('Row', headings)
        for r in f_csv:
            yield Row(*r)

def main():
    conn_args = dict(host='127.0.0.1',user='root',passwd='msds007',port=3306,db='test')
    with get_conn(**conn_args) as conn:
        SQL_FORMAT = """insert into student(sno,sname,sage) values({0},'{1}',{2})"""
        for t in get_data('data.csv'):
            sql = SQL_FORMAT.format(t.sno, t.sname, t.sage)
            execute_sql(conn, sql)

if __name__ == '__main__':
    main()

3.Python并发编程

1).Python中的多线程

Python默认的解释器，由于全局解释器锁的存在，确实在任意时刻都只有一个线程在执行Python代码，致使多线程不能充分利用机器多核的特性
Python由于GIL(Global Interpreter Lock)锁的原因，并没有真正的并发
Python标准库提供了两个与线程相关的模块，分别是thread和threading
thread是低级模块，threading是高级模块，threading对thread进行了封装
1、创建线程
2、如何给线程传递参数
3、线程的常用方法
4、通过继承创建线程

2).线程同步与互斥锁

在Python标准库的threading模块中有一个名为Lock的工厂函数，会返回一个thread.LockType对象
该对象的acquire方法用来获取锁，release方法用来释放锁
try:
    lock.acquire()
    #do something
finally:
    lock.release()
使用上下文管理器：
with lock:
    #do something

使用互斥锁例子：
import threading

lock = threading.Lock()
num = 0

def incre(count):
    global num
    while count > 0:
        with lock:
            num += 1
        count -= 1

def main():
    threads = []
    for i in range(10):
        thread = threading.Thread(target=incre, args=(100000,))
        thread.start()
        threads.append(thread)

    for thread  in threads:
        thread.join()

    print("expected value is ", 10 * 100000, ", real value is ", num)

if __name__ == '__main__':
    main()

3).线程安全队列Queue

队列是线程间最常用的交换数据的形式，Queue模块实现了线程安全的队列，尤其适合多线程编程
简单例子：
import Queue

q = Queue.Queue()

for i in range(3):
    q.put(i)

while not q.empty():
    print(q.get())

Python官方给出的多线程模型：
def worker():
    while True:
        item = q.get()
        do_work(item)
        q.task_done()

q = Queue()
for i in range(num_worker_threads):
    t = Thread(target=worker)
    t.daemon =True
    t.start()

for item in source():
    q.put(item)

q.join()     # block until all tasks are done

4).案例：使用Python打造一个MySQL压测工具

import string
import argparse
import random
import threading
import time
import datetime
import pymysql
from contextlib import contextmanager

DB_NAME = 'test_insert_data_db'
TABLE_NAME = 'test_insert_data_table'
CREATE_TABLE_STATEMENT = """create table {0} (id int(11) not null auto_increment, name varchar(255) not null, birthday datetime not null, primary key (id))""".format(TABLE_NAME)

#_argparse的唯一作用就是使用标准库的argparse模块解析民工行参数并生成帮助信息
def _argparse():
    parser = argparse.ArgumentParser(description='benchmark tool for MySQL database')
    parser.add_argument('--host', action='store', dest='host', required=True, help='connect to host')
    parser.add_argument('--user', action='store', dest='user', required=True, help='user for login')
    parser.add_argument('--password', action='store', dest='password', required=True, help='password to use when connecting to server')
    parser.add_argument('--port', action='store', dest='port', default=3306, type=int, help='port number to use for connection or 3306 for default')
    parser.add_argument('--thread_size', action='store', dest='thread_size', default=5, type=int, help='how much connection for database usage')
    parser.add_argument('--row_size', action='store', dest='row_size', default=5000, type=int, help='how mucch rows')
    parser.add_argument('-v', '--version', action='version', version='%(prog)s 0.1')
    return parser.parse_args()

@contextmanager
def get_conn(**kwargs):
    conn = pymysql.connect(**kwargs)
    try:
        yield conn
    finally:
        conn.close()

def create_db_and_table(conn):
    with conn as cur:
        for sql in ["drop database if exists {0}".format(DB_NAME), "create database {0}".format(DB_NAME), "use {0}".format(DB_NAME), CREATE_TABLE_STATEMENT]:
            print(sql)
            cur.execute(sql)

def random_string(length=10):
    s = string.letters + string.digits
    return "".join(random.sample(s, length)) 

def add_row(cursor):
    SQL_FORMAT = "INSERT INTO {0}(name, birthday) values ('{1}','{2}')"
    sql = SQL_FORMAT.format(TABLE_NAME, random_string(), datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
    cursor.execute(sql) 

def insert_data(conn_args, row_size):
    with get_conn(**conn_args) as conn:
        with conn as c:
            c.execute('use {0}'.format(DB_NAME))
        with conn as c:
            for i in range(row_size):
                add_row(c)
                conn.commit()

def main():
    parser = _argparse()
    conn_args = dict(host=parser.host, user=parser.user, password=parser.password, port=parser.port)
    with get_conn(**conn_args) as conn:
        create_db_and_table(conn)
    threads = []
    for i in range(parser.thread_size):
        t = threading.Thread(target=insert_data, args=(conn_args, parser.row_size))
        threads.append(t)
        t.start()
    for t in threads:
        t.join()

if __name__ == '__main__':
    main()

4.专家系统设计

专家系统检查内容

1)服务器相关：包括cpu,io,内存,磁盘,网络等方面的检查

2)数据库相关：包括数据库的参数配置，主从复制性能等

3)业务相关：表结构,索引和SQL语句

索引检查：

主键索引检查，无效索引检查，冗余索引检查，索引区分度检查

容量规划：

cpu利用率检查，io能力检查，网络带宽检查，存储空间检查，内存占用检查

用户访问：

死锁统计，慢日志统计

安全检查：

弱密码检查，网络检查，权限检查

参数检查：

内存参数检查，重做日志配置检查，二进制日志检查，连接数配置检查

主从复制：

复制性能检查，数据安全检查

5.MySQL专家系统整体架构

1).作为平台服务的MySQL数据库健康检查系统

2).作为数据库工具的MySQL数据库健康检查系统

专家系统文件组织

# tree health_checker

health_checker

├── client

│ ├── action

│ │ ├── check_binary_logs.py

│ │ ├── check_connections.py

│ │ ├── check_redo_log.py

│ │ ├── check_safe_replication.py

│ │ └── __init__.py

│ ├── client.py

│ ├── database

│ │ ├── connection_pool.py

│ │ ├── __init__.py

│ │ └── mysql.py

│ ├── env.py

│ ├── handler.py

│ ├── __init__.py

│ ├── response.py

│ └── util.py

├── __init__.py

├── main.py

├── server

│ ├── health_checker_server.py

│ ├── __init__.py

│ ├── util.py

│ └── worker

│ ├── advise.py

│ ├── check_binary_logs.py

│ ├── check_connections.py

│ ├── check_redo_log.py

│ ├── check_safe_replication.py

│ ├── generic_worker.py

│ ├── health_checker_item.py

│ └── __init__.py

└── test.py