Question

使用如下文本处理日志文件的程序。请帮助您了解如何打印组件列表（在日期和时间之后），根据日志中消息的重要性（第一个单词）排列它们。

例如，组件A应该在组件B之前的列表中，如果它有更多具有最重要级别的消息。

   ERROR - 2015 Dec 28 14:48:30 - unfulminating_deacon - 55 - airtightly unintelligently appropriable arlen
   INFO - 2015 Dec 28 02:02:56 - mangiest_ima - 144 - overrealistically decadently unfierce edris
   CRITICAL - 2015 Dec 27 20:04:02 - unanticipated_konnor - 44 - amusively sensationally turbanlike rico
   INFO - 2015 Dec 28 08:12:06 - unfulminating_deacon - 123 - eruptively nonmodally sebacic shavonda
   CRITICAL - 2015 Dec 28 08:04:27 - unanticipated_konnor - 1213 - unchastely priorly monophyletic cullen
   ERROR - 2015 Dec 28 07:39:36 - furnacelike_marlene - 1414 - healthfully flinchingly unbombastic slyvia
   DEBUG - 2015 Dec 27 16:44:47 - mangiest_ima - 144 - questingly substitutionally uncompensative jen
   ERROR - 2015 Dec 26 17:49:26 - furnacelike_marlene - 1414 - healthfully flinchingly unbombastic slyvia

EXPECTED OUTPUT:
unanticipated_konnor 
furnacelike_marlene 
unfulminating_deacon 
mangiest_ima

我已经制作了一些代码来计算组件的消息频率，但我不确定它是否有用：

from collections import Counter
file = open('C:\\Users\\User\\Downloads\\tasks\\logs\\1.txt', "r+")
warnList = []
for line in file:
    warnList.append(line.split(' - ')[2])
res1 = dict(Counter(warnList))
print "Frequency of messages for components: {} \n".format(res1)
file.close()

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希望得到您的帮助或建议，

提前致谢，

此致

Answer 1

我不太确定我是否正确理解了您的问题，但如果您想按重要性排序日志文件，请尝试以下操作：

from __future__ import print_function

import re
import operator
import collections
import pprint as pp

importance = {
    'CRITICAL': 0,
    'ERROR': 100,
    'INFO': 200,
    'DEBUG': 300
}

with open('log.log', 'r') as f:
    data = f.read().splitlines() 

parsed = collections.OrderedDict()

for line in data:
    cols = re.split(r'\s+\-\s+', line)
    parsed[line] = importance[cols[0]]

for k,v in sorted(parsed.items(), key=operator.itemgetter(1)):
    print(k)

输出：

CRITICAL - 2015 Dec 27 20:04:02 - unanticipated_konnor - 44 - amusively sensationally turbanlike rico
CRITICAL - 2015 Dec 28 08:04:27 - unanticipated_konnor - 1213 - unchastely priorly monophyletic cullen
ERROR - 2015 Dec 28 14:48:30 - unfulminating_deacon - 55 - airtightly unintelligently appropriable arlen
ERROR - 2015 Dec 28 07:39:36 - furnacelike_marlene - 1414 - healthfully flinchingly unbombastic slyvia
ERROR - 2015 Dec 26 17:49:26 - furnacelike_marlene - 1414 - healthfully flinchingly unbombastic slyvia
INFO - 2015 Dec 28 02:02:56 - mangiest_ima - 144 - overrealistically decadently unfierce edris
INFO - 2015 Dec 28 08:12:06 - unfulminating_deacon - 123 - eruptively nonmodally sebacic shavonda
DEBUG - 2015 Dec 27 16:44:47 - mangiest_ima - 144 - questingly substitutionally uncompensative jen

如果不是您想要的，请说明您需要什么。

如果您只需要第三列：

from __future__ import print_function

import re
import operator
import collections
import pprint as pp

importance = {
    'CRITICAL': 0,
    'ERROR': 100,
    'INFO': 200,
    'DEBUG': 300
}

with open('log.log', 'r') as f:
    data = f.read().splitlines() 

parsed = collections.OrderedDict()

for line in data:
    cols = re.split(r'\s+\-\s+', line)
    parsed[cols[2]] = importance[cols[0]]

for k,v in sorted(parsed.items(), key=operator.itemgetter(1)):
    print(k)

输出：

unanticipated_konnor
furnacelike_marlene
unfulminating_deacon
mangiest_ima

按分词排序字符串

1 个答案: