转载——使用Python查询MySQL数据库生成Excel文件发送监控周报

原文：https://blog.51cto.com/5814380/2114314

业务方要求每周发一封周报出来，将过去一周的线上项目的详细信息发送出来，我们的监控用的是zabbix，过去一直是手动填写，非常耗时耗力，而且显得非常不专业，所以我花了几个月时间学习Python，编写如下脚本供大家参考，望大神勿笑。

#!/usr/bin/env python
#-*- coding: utf8 -*-
import MySQLdb
import string
import xlsxwriter
import time,datetime
import sys
reload(sys)
sys.setdefaultencoding('utf-8')

zdbhost = '  '
zdbuser = '  '
zdbpass = '  '
zdbport =  
zdbname = '  '

#时间戳 取当前时间和7天前的时间 
stop_time = int(time.time())
start_time = stop_time - 604800
date = time.strftime("%Y-%m-%d",time.localtime(stop_time))
xlsfilename = '%s业务周报.xlsx' % date

#keys格式：itemname itemid type 格式化 groupid
keys = [
    [
        ['UV/天','167365','max', '%.2f', 1,'48',],
        ['PV/周','167359','max', '%.2f', 1,'48',],
        ['最大并发','167364','max', '%.2f', 1,'48',],
        ['最大并发发生时间','167364','max', '%.2f', 1,'48',],
        ['平均QPS','167361','avg', '%.2f', 1,'48'],
        ['最大QPS','167361','max', '%.2f', 1,'48'],
        ['最大QPS发生时间','167361','max', '%.2f', 1,'48'],
        ['最大带宽(in)','81291','max', '%.2f', '1048576','48'],
        ['平均带宽(in)','81291','avg', '%.2f', '1048576','48'],
        ['最大带宽(out)','81292','max', '%.2f', '1048576','48'],
        ['平均带宽(out)','81292','avg', '%.2f', '1048576','48']
    ],
    [
        ['UV/天','168141','max', '%.2f', 1,'16'],
        ['PV/周','168135','max', '%.2f', 1,'16'],
        ['最大并发','168140','max', '%.2f', 1,'16'],
        ['最大并发发生时间','168140','max', '%.2f', 1,'16',''],
        ['平均QPS','168137','avg', '%.2f', 1,'16'],
        ['最大QPS','168137','max', '%.2f', 1,'16'],
        ['最大QPS发生时间','168137','max', '%.2f', 1,'16'],
        ['最大带宽(in)', '104522','max', '%.2f', '1048576','16'],
        ['平均带宽(in)', '104522','avg', '%.2f', '1048576','16'],
        ['最大带宽(out)', '104523','max', '%.2f', '1048576','16'],
        ['平均带宽(out)', '104523','avg', '%.2f', '1048576','16']
    ],
    [
        ['UV/天', '163672','max', '%.2f', 1,'71'],
        ['PV/周', '163666','max', '%.2f', 1,'71'],
        ['最大并发', '163671','max', '%.2f', 1,'71'],
        ['最大并发发生时间', '163671','max', '%.2f', 1,'71',''],
        ['平均QPS','163668','avg', '%.2f', 1,'71'],
        ['最大QPS','163668','max', '%.2f', 1,'71'],
        ['最大QPS发生时间','163668','max', '%.2f', 1,'71'],
        ['最大带宽(in)', '84942','max', '%.2f', '1048576','71'],
        ['平均带宽(in)', '84942','avg', '%.2f', '1048576','71'],
        ['最大带宽(out)', '84943','max', '%.2f', '1048576','71'],
        ['平均带宽(out)', '84943','avg', '%.2f', '1048576','71']
    ],
    [
        ['UV/天', '154707','max', '%.2f', 1,'132'],
        ['PV/周', '154722','max', '%.2f', 1,'132'],
        ['最大并发', '154706','max', '%.2f', 1,'132'],
        ['最大并发发生时间', '154706','max', '%.2f', 1,'132',''],
        ['平均QPS','154703','avg', '%.2f', 1,'132'],
        ['最大QPS','154703','max', '%.2f', 1,'132'],
        ['最大QPS发生时间','154703','max', '%.2f', 1,'132'],
        ['最大带宽(in)', '152400','max', '%.2f', '1048576','132'],
        ['平均带宽(in)', '152400','avg', '%.2f', '1048576','132'],
        ['最大带宽(out)', '152402','max', '%.2f', '1048576','132'],
        ['平均带宽(out)', '152402','avg', '%.2f', '1048576','132']
    ],
    [
        ['UV/天', '189559','max', '%.2f', 1,'31'],
        ['PV/周', '189553','max', '%.2f', 1,'31'],
        ['最大并发', '189558','max', '%.2f', 1,'31'],
        ['最大并发发生时间', '189558','max', '%.2f', 1,'31',''],
        ['平均QPS','189555','avg', '%.2f', 1,'31'],
        ['最大QPS','189555','max', '%.2f', 1,'31'],
        ['最大QPS发生时间','189555','max', '%.2f', 1,'31'],
        ['最大带宽(in)', '190757','max', '%.2f', '1048576','31'],
        ['平均带宽(in)', '190757','avg', '%.2f', '1048576','31'],
        ['最大带宽(out)', '190758','max', '%.2f', '1048576','31'],
        ['平均带宽(out)', '190758','avg', '%.2f', '1048576','31']
    ],
    [
        ['UV/天','188642','max', '%.2f', 1,'50'],
        ['PV/周','188636','max', '%.2f', 1,'50'],
        ['最大并发','188641','max', '%.2f', 1,'50'],
        ['最大并发发生时间','188641','max', '%.2f', 1,'50',''],
        ['平均QPS','188638','avg', '%.2f', 1,'50'],
        ['最大QPS','188638','max', '%.2f', 1,'50'],
        ['最大QPS发生时间','188638','max', '%.2f', 1,'50'],
        ['最大带宽(in)', '33707','max', '%.2f', '1048576','50'],
        ['平均带宽(in)', '33707','avg', '%.2f', '1048576','50'],
        ['最大带宽(out)', '33712','max', '%.2f', '1048576','50'],
        ['平均带宽(out)', '33712','avg', '%.2f', '1048576','50']
    ]
]

def report():
    '''打开数据库连接'''
    conn = MySQLdb.connect(host=zdbhost,user=zdbuser,passwd=zdbpass,port=zdbport,db=zdbname,charset='utf8')
    cursor = conn.cursor(cursorclass=MySQLdb.cursors.DictCursor)

    i = 2
    group = {"132":"微信公众号", "71":"微信电视", "16":"chiq3音视频", "48":"launcher", "50":"个性化推荐", "31":"语义云"}
    value1 = {}
    value = {}
    #创建文件
    workbook = xlsxwriter.Workbook(xlsfilename)
            #定义Excel中的格式，参考http://xlsxwriter.readthedocs.io/
    merge_format = workbook.add_format({
        'bold':     True,
        'border':   True,
        'align':    'center',
        'valign':   'vcenter',
        'fg_color': '#D7E4BC',
    })
    merge_format1 = workbook.add_format({
        'border':   True,
        'align':    'center',
        'valign':   'vcenter',
        'text_wrap':   True,
    })

    #创建工作薄
    worksheet = workbook.add_worksheet()
    worksheet.set_column('A:L',11)
            #写入第一行
    worksheet.merge_range('A1:L1', '业务监控周报(%s)'.decode('utf-8') % date, merge_format) 
            #写入其他行
    worksheet.write(1,0,'项目名称'.decode('utf-8'),merge_format1)
    for targets in keys:
        groupid = targets[0][5]
        worksheet.write(i,0,group[groupid].decode('utf-8'),merge_format1)
        j = 1

        for target in targets:
            item = target[0]
            itemid = target[1]
            sql2 = '''select %s(value_%s) as result from trends_uint where itemid = %s and clock >= %s''' % (target[2], target[2], itemid, start_time)
            try:
                cursor.execute(sql2)
                result2 = cursor.fetchone()['result']
            except MySQLdb.OperationalError:
                result2 = "Not monitored"

            if target[0] in ['最大QPS发生时间','最大并发发生时间']:
                #sql3 = '''select clock from trends_uint where itemid = %s and value_%s = %s  and clock >= %s and clock <= %s ''' % (target[1], target[2], result2, start_time, stop_time)
                sql3 = '''select clock from trends_uint where itemid = %s and value_%s = %s  and clock >= %s limit 1''' % (target[1], target[2], result2, start_time)
                try:
                    cursor.execute(sql3)
                    result3 = cursor.fetchone()['clock']
                    result2 = time.strftime("%Y-%m-%d %H:%M:%S",time.localtime(result3)) 
                except MySQLdb.OperationalError:
                    result2 = "Not monitored"
            #处理数据
            if not result2:
                result2 = "Not monitored"
            if type(result2) is str:
                result = result2
            else:
                if result2 > 1000:
                    if result2 > 1000000:
                        if result2 > 1000000000:
                            result = str('%.2f' %(float(result2)/1000000000)) + 'G'
                        else:
                            result = str('%.2f' %(float(result2)/1000000)) + 'M'
                    else:
                        result = str('%.2f' %(float(result2)/1000)) + 'K'
                else:
                    result = result2
            value1.update({itemid:result})
            value.update({groupid:value1})
            worksheet.write(1,j,item.decode('utf-8'),merge_format1)
            worksheet.write(i,j,value[groupid][itemid],merge_format1)
            j += 1
        i += 1

    workbook.close()
    cursor.close()
    conn.close()
if __name__ == "__main__":
   report()

最终效果，每周由脚本发送邮件

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原文地址：https://www.cnblogs.com/bravesunforever/p/13191190.html