我试图在Linux <div class="form-group" autocomplete="new-password">
@Html.LabelFor(m => m.Password, new { @class = "col-md-5 control-label" })
<div class="col-md-5">
@Html.PasswordFor(m => m.Password, new { @Title = Password, @class = "form-control", @autocomplete = "new-password" })
</div>
</div>
<div class="form-group" autocomplete="new-password">
@Html.LabelFor(m => m.ConfirmPassword, new { @class = "col-md-5 control-label" })
<div class="col-md-5">
@Html.PasswordFor(m => m.ConfirmPassword, new { @class = "form-control", @autocomplete = "new-password" })
</div>
</div>
<div class="form-group">
<div class="col-md-offset-2 col-md-5">
<input type="submit" class="btn btn-default" value="Confirmer" />
</div>
</div>
中读取一个具有特殊字符串模式的行,我在下面给出了这一点。从这个行模式我查看用户的电子邮件地址,例如/var/log/messages
并使用rajeshm@noi-rajeshm.fox.com
方法将其分成两部分作为列表索引,然后进一步将第一个拆分为一个列表,以便于获取最后一个索引值,即用户ID,并且工作正常。
说我能够获取用户列表和总计数,但我需要计算每个用户的出现次数并打印str.partition()
,因此键和值。
11月28日09:00:08 foxopt210 rshd [6157]:pam_rhosts(rsh:auth):允许 访问rajeshm@noi-rajeshm.fox.com作为rajeshm
user_name: Count
目前的代码如下:
#!/usr/bin/python3
f= open("/var/log/messages")
count = 0
for line in f:
if "allowed access" in line:
count+=1
user_id = line.partition('@')[0]
user_id = user_id.split()[-1]
print(user_id)
f.close()
print("--------------------")
print("Total Count :" ,count)
在谷歌搜索时,我想到了为此使用字典 目的和它按预期工作:
bash-4.1$ ./log.py | tail
navit
akaul
akaul
pankaja
vishalm
vishalm
rajeshm
rajeshm
--------------------
Total Count : 790
我的输出符合要求:
#!/usr/bin/python3
from collections import Counter
f= open("/var/log/messages")
count = 0
dictionary = {}
for line in f:
if "allowed access" in line:
user_id = line.partition('@')[0]
user_count = user_id.split()[-1]
if user_count in dictionary:
dictionary[user_count] += 1
else:
dictionary[user_count] = 1
for user_count, occurences in dictionary.items():
print(user_count, ':', occurences)
我只是想看看是否有更好的方法来进行这项练习。
答案 0 :(得分:4)
在计算内容时,使用collections.Counter()
class会更容易。我将这些行解析为生成器:
def users_accessed(fileobj):
for line in fileobj:
if 'allowed access' in line:
yield line.partition('@')[0].rsplit(None, 1)[-1]
并将其传递给Counter()
对象:
from collections import Counter
with open("/var/log/messages") as f:
access_counts = Counter(users_accessed(f))
for userid, count in access_counts.most_common():
print(userid, count, sep=':')
这使用Counter.most_common()
method来提供排序输出(最常见的是最少)。
答案 1 :(得分:1)
您可以尝试使用正则表达式,并且可以执行此操作:
import re
pattern=r'(?<=as\s)\w.+'
occurrence={}
with open("/var/log/messages") as f:
for line in f:
search=re.search(pattern,line).group()
if search not in occurrence:
occurrence[search]=1
else:
occurrence[search]=occurrence.get(search)+1
print(occurrence)
只是为了好玩的一线逻辑:
import re
pattern=r'(?<=as\s)\w.+'
new={}
[new.__setitem__(re.search(pattern, line).group(), 1) if re.search(pattern, line).group() not in new else new.__setitem__(re.search(pattern, line).group(), new.get(re.search(pattern, line).group()) + 1) for line in open('legend.txt','r')]
print(new)