zabbix获取一周内各个等级告警的次数

  1 # encoding:UTF-8
  2 import xlsxwriter
  3 import datetime
  4 import pymysql
  5 import numpy as np
  6 import pandas
  7 
  8 __author__ = 'sanjing'
  9 __data__ = '2019/06/14'
 10 
 11 
 12 averagesql = """
 13     select from_unixtime(clock,'%Y-%m-%d') as time,
 14         count(DISTINCT eventid) as id    
 15         from alerts 
 16         WHERE mediatypeid = 5 
 17         AND message LIKE '%告警等级: Average%'
 18         AND SUBJECT  LIKE '%PROBLEM%'
 19         AND clock BETWEEN UNIX_TIMESTAMP(DATE_SUB(NOW(), INTERVAL 7 DAY)) AND UNIX_TIMESTAMP(DATE_SUB(NOW(), INTERVAL 1 DAY))
 20         group by time
 21         order by time asc
 22 
 23 """
 24 
 25 highsql = """
 26     select from_unixtime(clock,'%Y-%m-%d') as time,
 27         count(DISTINCT eventid) as id    
 28         from alerts 
 29         WHERE mediatypeid = 5 
 30         AND message LIKE '%告警等级: High%'
 31         AND SUBJECT  LIKE '%PROBLEM%'
 32         AND clock BETWEEN UNIX_TIMESTAMP(DATE_SUB(NOW(), INTERVAL 7 DAY)) AND UNIX_TIMESTAMP(DATE_SUB(NOW(), INTERVAL 1 DAY))
 33         group by time
 34         order by time asc
 35 """
 36 
 37 warningsql = """
 38     select from_unixtime(clock,'%Y-%m-%d') as time,
 39         count(DISTINCT eventid) as id    
 40         from alerts 
 41         WHERE mediatypeid = 5 
 42         AND message LIKE '%告警等级: Warning%'
 43         AND SUBJECT  LIKE '%PROBLEM%'
 44         AND clock BETWEEN UNIX_TIMESTAMP(DATE_SUB(NOW(), INTERVAL 7 DAY)) AND UNIX_TIMESTAMP(DATE_SUB(NOW(), INTERVAL 1 DAY))
 45         group by time
 46         order by time asc
 47 """
 48 
 49 informationsql = """
 50     select from_unixtime(clock,'%Y-%m-%d') as time,
 51         count(DISTINCT eventid) as id    
 52         from alerts 
 53         WHERE mediatypeid = 5 
 54         AND message LIKE '%告警等级: Information%'
 55         AND SUBJECT  LIKE '%PROBLEM%'
 56         AND clock BETWEEN UNIX_TIMESTAMP(DATE_SUB(NOW(), INTERVAL 7 DAY)) AND UNIX_TIMESTAMP(DATE_SUB(NOW(), INTERVAL 1 DAY))
 57         group by time
 58         order by time asc
 59 """
 60 
 61 disastersql = """
 62     select from_unixtime(clock,'%Y-%m-%d') as time,
 63         count(DISTINCT eventid) as id    
 64         from alerts 
 65         WHERE mediatypeid = 5 
 66         AND message LIKE '%告警等级: Diasater%'
 67         AND SUBJECT  LIKE '%PROBLEM%'
 68         AND clock BETWEEN UNIX_TIMESTAMP(DATE_SUB(NOW(), INTERVAL 7 DAY)) AND UNIX_TIMESTAMP(DATE_SUB(NOW(), INTERVAL 1 DAY))
 69         group by time
 70         order by time asc
 71 """
 72 
 73 
 74 #连接MySQL数据库
 75 def get_count(sql):
 76     conn=pymysql.connect("xx.xx.xx.xx", "readonly", "xxxx", "zabbix", charset='utf8')
 77     cursor = conn.cursor()
 78     cursor.execute(sql)
 79     count = cursor.fetchall()
 80     # 将rows转化为数组
 81     rows = np.array(count)
 82     conn.close()
 83     return count
 84 
 85 
 86 def coloum(data, weekendtime):
 87 #创建一个excel文件
 88     workbook = xlsxwriter.Workbook(weekendtime +".xlsx")
 89 #创建一个工作表，默认sheet1
 90     worksheet = workbook.add_worksheet()
 91     bold = workbook.add_format({'bold': 1})
 92 #表头
 93 
 94     title = ['告警级别', '星期一','星期二','星期三','星期四','星期五','星期六','星期日']
 95 #列名
 96     buname = ['information', 'warning','average', 'high', 'disaster']
 97 # 定义数据formatter格式对象，设置边框加粗1像素
 98     formatter = workbook.add_format()
 99     formatter.set_border(1)
100 #定义格式：# 定义标题栏格式对象：边框加粗1像素，背景色为灰色，单元格内容居中、加粗
101     title_formatter = workbook.add_format()
102     title_formatter.set_border(1)
103     title_formatter.set_bg_color('#cccccc')
104     title_formatter.set_align('center')
105     title_formatter.set_bold()
106     chart_col = workbook.add_chart({'type': 'column'})
107     def chart_series(row):
108         chart_col.add_series(
109             {
110                 'categories': '=Sheet1!$B$1:$H$1',
111                 'values': '=Sheet1!$B${}:$H${}'.format(row, row),
112                 'line': {'color': 'black'},
113 #                'name': '=Sheet1!$A${}'.format(row)
114                 'name': '=Sheet1!$A$' + row
115             }
116         )
117 # 下面分别以行和列的方式将标题栏、业务名称、流量数据写入单元格，并引用不同的格式对象
118     worksheet.write_row('A1',title,title_formatter)
119     worksheet.write_column('A2',buname,formatter)
120     for i in range (2,7):
121         worksheet.write_row('B{}'.format(i),data[i-2],formatter)
122         print (i)
123         chart_series(str(i))
124 
125 
126     # 设置图表的title 和 x，y轴信息
127     chart_col.set_title({'name': '告警统计/周'})
128     chart_col.set_x_axis({'name': '告警级别'})
129     chart_col.set_y_axis({'name': '告警次数'})
130     # 设置图表的风格
131 #    chart_col.set_style(37)
132 
133     # 把图表插入到worksheet以及偏移
134     worksheet.insert_chart('A10', chart_col, {'x_offset': 25, 'y_offset': 10})
135     workbook.close()
136 #判断二维元组是否为空，长度是否满足要求，不满足则补0.
137 #输入为一个字典，判断是否为空，空则添加数据
138 def covertdata(jsondata,weektime):
139 
140     listkey = list(jsondata.keys())
141     for i in weektime:
142         j = i.strftime("%Y-%m-%d")
143         if listkey:
144             if j not in listkey:
145                 jsondata[j] = "0"
146         else:
147             jsondata[j] = "0"
148 #    print (jsondata)
149 #按照时间对字典进行排序
150     sort = sorted(jsondata.items(), key=lambda d: d[0])
151 #将第二列取出来并转为列表
152     array = np.array(sort)
153     array2 = array[:, 1]
154     list2 = array2.tolist()
155     list3 = list(map(lambda x: float(x), list2))
156     return list3
157 #    print (list2)
158 
159 
160 if __name__ == '__main__':
161     yesterday = (datetime.date.today() + datetime.timedelta(days=-1)).strftime("%Y-%m-%d")
162     weeklist = pandas.date_range(end=yesterday, periods=7)
163     informationdata = get_count(informationsql)
164     informationlist = covertdata(dict(informationdata),weeklist)
165     warningdata = get_count(warningsql)
166     warninglist = covertdata(dict(warningdata),weeklist)
167     averagedata = get_count(averagesql)
168     averagelist = covertdata(dict(averagedata),weeklist)
169     highdata = get_count(highsql)
170     highlist = covertdata(dict(highdata),weeklist)
171     disasterdata = get_count(disastersql)
172     disasterlist = covertdata(dict(disasterdata),weeklist)
173 #    print (informationlist)
174 #    print (warninglist)
175 #    print (averagelist)
176 #    print (highlist)
177 #    print (disasterlist)
178     data1 = [informationlist, warninglist, averagelist, highlist, disasterlist]
179     coloum(data1,yesterday)

结果如图：