比较阵列的所有相邻元素

Question

我有一个日志文件，其中包含不同行中的不同Mac地址。

我可以提取包含给定Mac地址的行，然后我可以修剪该行以仅获取时间戳（例如15:48:55）然后我将此时间戳添加到数组中。

我想要的是;

如果时间戳减法大于2秒，如何比较数组的所有相邻元素？

日志文件示例：

info: 02-03-2018, 15:48:55.730, 192.168.1.4, 33826, 5C-CF-7F-29-AB-73, 22496
info: 02-03-2018, 15:48:55.894, 192.168.1.6, 17948, A0-20-A6-0A-F2-AB, 22475
info: 02-03-2018, 15:48:56.031, 192.168.1.3, 32538, A0-20-A6-0A-2F-D5, 22510
info: 02-03-2018, 15:48:56.742, 192.168.1.7, 40596, 60-01-94-16-05-96, 22490
info: 02-03-2018, 15:48:57.475, 192.168.1.5, 30646, 5C-CF-7F-DA-5B-77, 22668
info: 02-03-2018, 15:48:57.780, 192.168.1.4, 39592, 5C-CF-7F-29-AB-73, 22497
info: 02-03-2018, 15:48:57.922, 192.168.1.6, 21467, A0-20-A6-0A-F2-AB, 22476
info: 02-03-2018, 15:48:58.055, 192.168.1.3, 13001, A0-20-A6-0A-2F-D5, 22511
info: 02-03-2018, 15:48:58.760, 192.168.1.7, 31030, 60-01-94-16-05-96, 22491
info: 02-03-2018, 15:48:59.487, 192.168.1.5, 46505, 5C-CF-7F-DA-5B-77, 22669

到目前为止我得到了什么：

from datetime import datetime
import os
import re

# Regex used to match relevant loglines (in this case, a specific MAC address)
line_regex = re.compile(r'A0-20-A6-0A-F2-AB')

with open("info.log", "r") as in_file:

    # Loop over each log line
    for line in in_file:

        # If log line matches our regex
        if (line_regex.search(line)):

            #Extract the timestamp as 15:48:55
            asd = line[18:26]

            #Convert to datetime_object
            datetime_object = datetime.strptime(asd, '%H:%M:%S')

            #Trim begining of the datetime object
            dsa = datetime_object.strftime ('%H:%M:%S')

            #Add to an array as a timestamp
            for j in range(1):
                    array1=[]
                    for i in range(1):
                        array1.append(dsa)
                        print array1

Answer 1

你真的不需要额外的模块，你只需要使用datetime对象，而不是字符串。

from datetime import datetime
import os
import re

line_regex = re.compile(r'A0-20-A6-0A-F2-AB')

prev_dsa = None
with open("info.log", "r") as in_file:
    for line in in_file:
        if (line_regex.search(line)):
            asd = line[6:26]
            dsa = datetime.strptime(asd, '%m-%d-%Y, %H:%M:%S')
            if (prev_dsa != None):
                if abs((dsa - prev_dsa).seconds) >= 2:
                    print dsa
            prev_dsa = dsa

Answer 2

你可以使用pandas。注意：这可以很容易地进行调整以考虑日期，但就目前而言，它只考虑时间组件。

df = pd.read_csv('file.csv', header=None, delimiter=', ')
df['Diff'] = pd.to_datetime(df[1], format='%H:%M:%S.%f').diff().dt.microseconds / 10**6

# greater than half a second differences
res = df[df['Diff'] > 0.5]

#                   0             1            2      3                  4  \
# 3  info: 02-03-2018  15:48:56.742  192.168.1.7  40596  60-01-94-16-05-96   
# 4  info: 02-03-2018  15:48:57.475  192.168.1.5  30646  5C-CF-7F-DA-5B-77   
# 8  info: 02-03-2018  15:48:58.760  192.168.1.7  31030  60-01-94-16-05-96   
# 9  info: 02-03-2018  15:48:59.487  192.168.1.5  46505  5C-CF-7F-DA-5B-77   

#        5   Diff  
# 3  22490  0.711  
# 4  22668  0.733  
# 8  22491  0.705  
# 9  22669  0.727