将ansible执行结果进行处理，变成excel，ansibleexcel

将ansible执行结果进行处理，变成excel，ansibleexcel

ansible输出结果，统计起来很麻烦，将结果变为excel，并且按照结果统计汇总，可读性会强很多

ansible输出结果：

ansible输出结果
192.168.250. 250| SUCCESS | rc=0 >>
Selinux check success!This gbase01's selinux is Disabled and selinux config is SELINUX=disabled.
Swappiness check failed! This gbase01's swappiness is 60.
Ulimit check success! This gbase01's ulimit is 655360.
Hugepage check failed! This gbase01's hugepage status is never.
Timezone check success! This gbase01's timezone is +0800.
This gbase01's kernel is 2.6.32-431.el6.x86_64.
This gbase01's openssl is openssl-1.0.1e-30.el6.x86_64.
CPU check success! This gbase01's CPU number is 4.
Mem check success! This gbase01's Mem size is 16GB.
Hostname check success! This gbase01 is right.
192.168.152.222 | UNREACHABLE! => {
    "changed": false, 
    "msg": "mkdir: cannot create directory `/root/.ansible/tmp/ansible-tmp-1536203934.77-45972825051570': No space left on device\n", 
    "unreachable": true
}

使用代码将ansible输出结果进行处理

import pandas as pd
import re
import numpy as np
#打开文件
with open(r'F:\python教程\练手程序\a.txt','r') as f:
    text=f.read()
    data = text.strip()
    data=data.replace("|","\n").replace(">>","\n").replace("{","\n").replace("}","\n").replace(r"\r\n","\n")#处理文本中的特殊字符

    data1 =data.split("\n")
    data2 = [i for i in data1 if i != '']


rs = []
#将ip匹配出来，放在列表中
ip = ""
state=['SUCCESS','FAILED','UNREACHABLE']
status=''
result=''
info=''
for d in data2:
    if re.findall('\d+\.\d+\.\d+\.\d', d):#如果在行中找到ip地址
        ip = d
        #print(d)
    elif d.strip() in state:#输出状态值
        status=d
    else:
        if len(d.split('!'))==2:
            result=d.split('!')[0]
            info=d.split('!')[1]
            rs.append((ip,status, result,info))#以ip,每行内容，作为元素加到列表中
        else:
            result=d
            info=''
            rs.append((ip,status, result,info))
df = pd.DataFrame(rs, columns=["ip","status","result", "info"])#从列表创建DataFrame，指定data和columns
df = df.groupby(["ip","status"]).apply(lambda x: x["info"])#apply函数 会自动遍历每一行DataFrame的数据，最后将所有结果组合成一个Series数据结构并返回。
df.to_excel("test2.xlsx")#将结果输出变成excel

输出结果手动调整一下，如上，over