一、适用场景
项目工作中，我们会遇到测试环境特别多的情况，例如：n套beta环境，多套预生产环境，多套uat环境等各种测试环境。为保证所有测试环境表结构上的一致性，如果只是单纯地靠人工来检查并更新，未免显得太过吃力且效率低下，还容易在实施的过程中出现遗漏的问题。
因此使用自动化脚本来完成这项工作就显得格外重要了，今天分享的主要内容就是通过自动化脚本协助你找到不同测试环境之间差异化的内容，进而可以避免同步过程中出现的遗漏问题。
二、代码实现
1、前置处理与基础配置
1import pymysql
2from email.mime.multipart import MIMEMultipart
3from email.mime.text import MIMEText
4import smtplib
5import time
6
7#忽略掉的db字典
8ignoreDb={'information_schema': 'information_schema',
9 'mysql': 'mysql',
10 'performance_schema': 'performance_schema',
11 'sys': 'sys'
12 }
13
14#忽略掉的db在查询sql中使用的
15ignoreDbSQL="('information_schema', 'mq_store','performance_schema', 'sys','edsystem')"
16
17#收diff报告的邮箱地址
18emails='[email protected]'
19
20#排除不在diff范围内的表名称列表
21exclude_table = ['tt', 'hurdle_policy_back', 'preferences_0309', 'preferences_0524', 'preferences_0310','t1','t2','mock_data']
2、用来发送diff报告
1def send_mail(receivers, title, content):
2 sender = '[email protected]'
3 mailto = receivers.split(",")
4 try:
5 msg = MIMEMultipart()
6 msg['Subject'] = title
7 to_user = ",".join(mailto)
8
9 print("receivers...", to_user)
10 msg['to'] = to_user
11 msg['From'] = sender
12
13 body = MIMEText(content, _subtype='html', _charset='utf-8')
14 msg.attach(body)
15 smtp = smtplib.SMTP('smtp.office365.com', 587)
16 smtp.starttls()
17 print("sending")
18 smtp.login("[email protected]", "test123456")
19 smtp.sendmail(sender, mailto, msg.as_string())
20 print("send")
21 smtp.quit()
22 except smtplib.SMTPException as e:
23 print(e)
3、查询获取所有的列名数据
1def queryAllColumns(mycursor):
2 sql = " SELECT TABLE_SCHEMA 库名,TABLE_NAME 表名,COLUMN_NAME 列名, COLUMN_TYPE 数据类型, DATA_TYPE 字段类型, " \
3 "CHARACTER_MAXIMUM_LENGTH 长度, IS_NULLABLE 是否为空, COLUMN_DEFAULT 默认值, " \
4 "COLUMN_COMMENT 备注 FROM INFORMATION_SCHEMA.COLUMNS " \
5 "where table_schema not in " + ignoreDbSQL;
6 # print(sql)
7 mycursor.execute(sql)
8 result = mycursor.fetchall()
9
10 d = {};
11 for x in result:
12 r={}
13 r['TABLE_SCHEMA'] = x[0];
14 r['TABLE_NAME'] = x[1];
15 if(x[1] in exclude_table):
16 continue
17 r['COLUMN_NAME'] = x[2];
18 r['COLUMN_TYPE'] = x[3];
19 r['DATA_TYPE'] = x[4];
20 r['CHARACTER_MAXIMUM_LENGTH'] = x[5];
21 r['IS_NULLABLE'] = x[6];
22 r['COLUMN_DEFAULT'] = x[7];
23 r['COLUMN_COMMENT'] = x[8];
24 d[x[0] + "." + x[1] + "." + x[2]] = r;
4、最终d的数据模式如下并将其返回
1 d=
2 {'route_config_meta.entity_sharding_config.create_date':
3 {'TABLE_SCHEMA': 'route_config_meta', 'TABLE_NAME': 'entity_sharding_config', 'COLUMN_NAME': 'create_date',
4 'COLUMN_TYPE': 'datetime', 'DATA_TYPE': 'datetime', 'CHARACTER_MAXIMUM_LENGTH': None, 'IS_NULLABLE': 'NO',
5 'COLUMN_DEFAULT': None, 'COLUMN_COMMENT': '创建时间'},
6 'route_config_meta.entity_sharding_config.update_time':
7 {'TABLE_SCHEMA': 'route_config_meta', 'TABLE_NAME': 'entity_sharding_config', 'COLUMN_NAME': 'update_time',
8 'COLUMN_TYPE': 'datetime', 'DATA_TYPE': 'datetime', 'CHARACTER_MAXIMUM_LENGTH': None, 'IS_NULLABLE': 'NO',
9 'COLUMN_DEFAULT': 'CURRENT_TIMESTAMP', 'COLUMN_COMMENT': '更新时间'}
10 }
11 return d;
5、查询获取所有的索引数据
1def queryAllIndex(mycursor):
2 sql = "Select TABLE_SCHEMA 库名称,TABLE_NAME 表名称,INDEX_NAME 索引的名称,SEQ_IN_INDEX 索引中的列序列号,COLUMN_NAME 列名称 from INFORMATION_SCHEMA.STATISTICS " \
3 "where TABLE_SCHEMA not in " + ignoreDbSQL;
4
5 sql=
6 Select TABLE_SCHEMA,TABLE_NAME,INDEX_NAME,SEQ_IN_INDEX,COLUMN_NAME from INFORMATION_SCHEMA.STATISTICS where TABLE_SCHEMA
7 not in ('information_schema', 'mq_store', 'mysql', 'performance_schema', 'slow_query_log','repeater',
8 'repeater_console','sys','edsystem','crs_adapter','oxi-adapter')
9
10 mycursor.execute(sql)
11
12 result = mycursor.fetchall()
13 # print(result)
14
15 result=
16 (
17 ('auth', 'authorities', 'PRIMARY', 1, 'id'),
18 ('auth', 'authorities', 'idx_code', 1, 'code')
19 )
20
21 d = {};
22 for x in result:
23 r = {}
24 r['TABLE_SCHEMA'] = x[0];
25 r['TABLE_NAME'] = x[1];
26 if (x[1] in exclude_table):
27 continue
28 r['INDEX_NAME'] = x[2];
29 r['SEQ_IN_INDEX'] = x[3];
30 r['COLUMN_NAME'] = x[4];
31 d[x[0]+"."+x[1]+"."+x[2]]=r;
32
33 d=
34 {
35 'auth.authorities.PRIMARY': {'TABLE_SCHEMA': 'auth', 'TABLE_NAME': 'authorities', 'INDEX_NAME': 'PRIMARY', 'SEQ_IN_INDEX': 1, 'COLUMN_NAME': 'id'},
36 'auth.authorities.idx_code': {'TABLE_SCHEMA': 'auth', 'TABLE_NAME': 'authorities', 'INDEX_NAME': 'idx_code', 'SEQ_IN_INDEX': 1, 'COLUMN_NAME': 'code'}
37 }
38 return d;
6、查询获取数据库实例名称
1def queryDbs(mycursor):
2 sql = 'show databases';
3 mycursor.execute(sql)
4 result = mycursor.fetchall()
5
6 d = {};
7 for x in result:
8 d[x[0]] = x[0];
9 return d;
7、构建成html格式的diff报表出来
1def buildHtml(db1,db2,cst,ist,tip):
2 # tip = db2.get('name') + "(" + db2.get('host') + ")"+ " 对比 " + db1.get('name') + "(" + db1.get('host') + ")"
3 str = '<!DOCTYPE html> <html> <meta charset="utf-8"> <head> <style type="text/css"> table.gridtable {font-family: verdana,arial,sans-serif; font-size:11px; color:#333333; border-width: 1px; border-color: #666666; border-collapse: collapse; } table.gridtable th {border-width: 1px; padding: 8px; border-style: solid; border-color: #666666; background-color: #dedede; } table.gridtable td {border-width: 1px; padding: 8px; border-style: solid; border-color: #666666; background-color: #ffffff; } </style> </head>';
4 str = str+'<body>'
5
6 str = str+' <table class="gridtable">'
7 str = str+ tip+' 缺少字段：'
8 str = str+' <tr> <th>database</th> <th>table</th> <th>column</th> <tr/> '
9
10 for x in cst:
11 xs = x.split('.')
12 str=str + '<tr> <td>'+xs[0]+'</td> <td>'+xs[1]+'</td> <td>'+xs[2]+'</td> <tr/>'
13 str = str + ' </table>'
14
15
16 str = str + ' <table class="gridtable">'
17 str = str + tip + ' 缺少索引：'
18 str = str + ' <tr> <th>database</th> <th>table</th> <th>index</th> <tr/> <tr>'
19
20 for x in ist:
21 xs = x.split('.')
22 str = str + '<tr> <td>' + xs[0] + '</td> <td>' + xs[1] + '</td> <td>' + xs[2] + '</td> <tr/>'
23
24 str = str + ' </table>'
25 str = str+'</body> </html>';
26 return str;
8、数据库的字段与索引diff 对比，并生成diff报告，发送邮件
1def diff(db1,db2):
2 mydb1 = pymysql.connect(
3 host=db1.get('host'),
4 user=db1.get('user'),
5 passwd=db1.get('password')
6 );
7
8 mydb2 = pymysql.connect(
9 host=db2.get('host'),
10 user=db2.get('user'),
11 passwd=db2.get('password')
12 )
13
14 mycursor1 = mydb1.cursor()
15 mycursor2 = mydb2.cursor()
16
17 #获取两个库里面的所有字段相关值
18 all_columns1 = queryAllColumns(mycursor1)
19 all_columns2 = queryAllColumns(mycursor2)
20
21 #获取两个库里面的所有索引相关值
22 all_index1 = queryAllIndex(mycursor1)
23 all_index2 = queryAllIndex(mycursor2)
24
25 mycursor1.close()
26 mycursor2.close()
27 mydb1.close()
28 mydb2.close()
29
30 #定义了一个提示信息标题头
31 tip = db2.get('name') +" 对比 " + db1.get('name') + "--(" + db2.get('host') + " 对比 "+ db1.get('host') + ")"
32
33 all_columns1的数据格式与如下all_index1雷同（{key:value}），但是数据值上是有差异的。
34
35 cs1 = set(all_columns1)
36 cs2 = set(all_columns2)
37 cst = cs1.difference(cs2)
9、索引的示例数据如下
1 all_index1=
2 {
3 'auth.authorities.PRIMARY': {'TABLE_SCHEMA': 'auth', 'TABLE_NAME': 'authorities', 'INDEX_NAME': 'PRIMARY', 'SEQ_IN_INDEX': 1, 'COLUMN_NAME': 'id'},
4 'auth.authorities.idx_code': {'TABLE_SCHEMA': 'auth', 'TABLE_NAME': 'authorities', 'INDEX_NAME': 'idx_code', 'SEQ_IN_INDEX': 1, 'COLUMN_NAME': 'code'}
5 }
10、使用set做去重处理,只留下唯一的key
1 is1 = set(all_index1)
2 is2 = set(all_index2)
3 #
4 ist = is1.difference(is2)
5
6 ist=
7 {'rate.tt.PRIMARY', 'entity_storage_1.reservation_log_0.transaction_id', 'rate.rate_header.idx_tcode_tax_include'}
8
9 content = buildHtml(db1,db2,sorted(cst),sorted(ist),tip)
10
11 fmt = '%Y-%m-%d %a %H:%M:%S' # 定义时间显示格式
12 nowtime = time.strftime(fmt, time.localtime(time.time())) # 把传入的元组按照格式，输出字符串
13 print ('当前的时间：', nowtime)
14
15 if len(ist) >= 0 or len(cst) >0:
16 send_mail(emails,'DBDIFF:'+tip ,content)
17
18if __name__ == '__main__':
19 beta1 = {'name': 'beta1', 'host': '10.7.36.34', 'user': 'root', 'password': '123456'}
20 beta2 = {'name': 'beta2', 'host': '10.7.36.2', 'user': 'root', 'password': '123456'}
21
22 diff(beta1, beta2)
11、输出的邮件内容如下
beta2 对比 beta1--(10.7.36.2 对比 10.7.36.34) 缺少字段：
database table column
db1 task_statistic create_date
db1 task_statistic execute_task_count
beta2 对比 beta1--(10.7.36.2 对比 10.7.36.34) 缺少索引：
database table index
db1 award_test idx_membership_related_id
db2 record_flow idx_related_member_id
三、总结
今天分享的内容实操性比较强，Python 实现代码都是干货，建议动手实操更有助于加深理解哟~
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