Question

我已将Wireshark pcap文件导出到csv。我需要根据时间间隔拆分这些csv文件。在csv文件中，有一个“时间”列。我想将这些文件分成1秒的时间间隔。因此，在前1秒到达的前几个数据包将被写入一个文件，在后1秒到达的下一个数据包将被写入另一个文件，依此类推。如果输入文件名为AAA.csv，则拆分文件将获得相同的名称，并在末尾附加一个数字。 AAA1.csv，..... AAA5.csv等。我是编程新手，所以不太确定如何从这一点着手。请帮忙。谢谢https://fil.email/8wSH9ohq

import os
startdir='.'
suffix='.csv'
for root, dirs, files in os.walk(startdir):
  for name in files:
    if name.endswith(suffix):
      filename=os.path.join(root,name)

这是一个csv文件的摘录，其中包含连续2秒钟的行：

"No.","Time","Time delta from previous displayed frame","Length","Source","Destination","Protocol","Info"
"100","23:39:52.634388","0.000502000","28","HuaweiTe_3a:d0:1a (8c:15:c7:3a:d0:1a) (TA)","Htc_9b:92:24 (ac:37:43:9b:92:24) (RA)","802.11","802.11 Block Ack, Flags=........"
"101","23:39:52.634393","0.000005000","102","Htc_9b:92:24","HuaweiTe_3a:d0:16","802.11","QoS Data, SN=45, FN=0, Flags=.p.....T"
"102","23:39:52.695277","0.060884000","28","Microsof_d2:8b:4f (30:59:b7:d2:8b:4f) (TA)","Sagemcom_28:38:64 (d0:6e:de:28:38:64) (RA)","802.11","802.11 Block Ack, Flags=........"
"103","23:39:52.695278","0.000001000","10","","Sagemcom_28:38:64 (d0:6e:de:28:38:64) (RA)","802.11","Clear-to-send, Flags=........"
"104","23:39:52.717845","0.022567000","16","HuaweiTe_3a:d0:1a (8c:15:c7:3a:d0:1a) (TA)","Htc_9b:92:24 (ac:37:43:9b:92:24) (RA)","802.11","Request-to-send, Flags=........"
"105","23:39:52.717845","0.000000000","406","HuaweiTe_3a:d0:16","Htc_9b:92:24","802.11","QoS Data, SN=3446, FN=0, Flags=.p....F."
"106","23:39:52.717852","0.000007000","28","Htc_9b:92:24 (ac:37:43:9b:92:24) (TA)","HuaweiTe_3a:d0:1a (8c:15:c7:3a:d0:1a) (RA)","802.11","802.11 Block Ack, Flags=........"
"107","23:39:52.717853","0.000001000","10","","HuaweiTe_3a:d0:1a (8c:15:c7:3a:d0:1a) (RA)","802.11","Clear-to-send, Flags=........"
"108","23:39:52.719380","0.001527000","28","HuaweiTe_3a:d0:1a (8c:15:c7:3a:d0:1a) (TA)","Htc_9b:92:24 (ac:37:43:9b:92:24) (RA)","802.11","802.11 Block Ack, Flags=........"
"109","23:39:52.719384","0.000004000","102","Htc_9b:92:24","HuaweiTe_3a:d0:16","802.11","QoS Data, SN=46, FN=0, Flags=.p.....T"
"110","23:39:52.719389","0.000005000","10","","Htc_9b:92:24 (ac:37:43:9b:92:24) (RA)","802.11","Clear-to-send, Flags=........"
"111","23:39:53.109091","0.389702000","24","Htc_9b:92:24","HuaweiTe_3a:d0:1a","802.11","Null function (No data), SN=4069, FN=0, Flags=...P...T"
"112","23:39:53.109586","0.000495000","10","","Htc_9b:92:24 (ac:37:43:9b:92:24) (RA)","802.11","Acknowledgement, Flags=........"
"113","23:39:53.149481","0.039895000","28","Sagemcom_28:38:64 (d0:6e:de:28:38:64) (TA)","Microsof_a0:a4:2c (58:82:a8:a0:a4:2c) (RA)","802.11","802.11 Block Ack, Flags=........"
"114","23:39:53.157218","0.007737000","24","Htc_9b:92:24","HuaweiTe_3a:d0:1a","802.11","Null function (No data), SN=4070, FN=0, Flags=.......T"
"115","23:39:53.159251","0.002033000","10","","Htc_9b:92:24 (ac:37:43:9b:92:24) (RA)","802.11","Acknowledgement, Flags=........"
"116","23:39:53.159252","0.000001000","16","HuaweiTe_3a:d0:1a (8c:15:c7:3a:d0:1a) (TA)","Htc_9b:92:24 (ac:37:43:9b:92:24) (RA)","802.11","Request-to-send, Flags=........"
"117","23:39:53.159267","0.000015000","10","","HuaweiTe_3a:d0:1a (8c:15:c7:3a:d0:1a) (RA)","802.11","Clear-to-send, Flags=........"
"118","23:39:53.160276","0.001009000","16","HuaweiTe_3a:d0:1a (8c:15:c7:3a:d0:1a) (TA)","Htc_9b:92:24 (ac:37:43:9b:92:24) (RA)","802.11","Request-to-send, Flags=........"
"119","23:39:53.160277","0.000001000","1500","HuaweiTe_3a:d0:16","Htc_9b:92:24","802.11","QoS Data, SN=3447, FN=0, Flags=.p....F."
"120","23:39:53.160290","0.000013000","28","Htc_9b:92:24 (ac:37:43:9b:92:24) (TA)","HuaweiTe_3a:d0:1a (8c:15:c7:3a:d0:1a) (RA)","802.11","802.11 Block Ack, Flags=........"

Answer 1

csv模块在这里就足够了。您只需要一次读取每个文件一行。如果“时间”字段的前8个字符（第二个）与上一行相同，则将该行复制到同一输出文件中，否则创建一个新的输出文件。

它可以编码为：

import os
import csv
startdir='.'
suffix='.csv'
for root, dirs, files in os.walk(startdir):
    for name in files:
        if name.endswith(suffix):
            filename=os.path.join(root,name)
            with open(filename) as fd:        # open the csv file
                rd = csv.reader(fd)           #  as a csv input file
                old = None                    # no previous line
                i = 0                         # we will start numbering output files with 1
                header = next(rd)             # store the header line
                for row in rd:
                    if row[1][:8] != old:     # we have a different second (or the first one...)
                        old = row[1][:8]      # store current time for next rows
                        i += 1                # increase output file number
                        if old is not None:   # eventually close previous output file
                            fdout.close()
                        fdout = open(filename[:-4] + str(i) + filename[-4:],
                                 'w', newline='')     # open a new output file
                        wr = csv.writer(fdout, quoting=csv.QUOTE_ALL)  # with expected csv params
                        _ = wr.writerow(header)   # write the header
                    _ = wr.writerow(row)      # copy the row to the current output file
                fdout.close()

以上代码使用的事实是，无需直接在Time字符串中进行解析即可确定秒。如果需要可变的持续时间最终小于秒，则需要解析时间字符串并将其转换为十进制（更精确地是浮点数）秒，然后将其除以以秒为单位的所选持续时间：

...
sec_duration=0.5     # for half a second
                ...
                for row in rd:
                    # convert the Time field to a total number of seconds in day
                    #  as a flot
                    cur = datetime.datetime.strptime(row[1], "%H:%M:%S.%f")
                    cur -= cur.replace(hour=0, minute=0, second=0, microsecond=0)
                    # make it a number of periods of sec_duration
                    cur = int(cur.total_seconds() / sec_duration)
                    if cur != old:     # we have a different period (or the first one...)
                        if old is not None:   # eventually close previous output file
                            fdout.close()
                        old = cur      # store current time for next rows
                        i += 1                # increase output file number
                ...

Answer 2

这应该使您入门。这会将您的示例csv分为11个不同的文件。我建议创建一个测试目录，并使用下面的代码进行测试，如果它符合您的期望。

import os
# pandas to read / write csv and process the data
import pandas as pd
startdir='.'
suffix='.csv'
for root, dirs, files in os.walk(startdir):
  for name in files:
    if name.endswith(suffix):
      filename=os.path.join(root,name)
      #print(filename)
      df = pd.read_csv(filename) 
      # Extract the time for grouping
      col_time = pd.to_datetime(dat1['Time'])
      # Group the values according to second(minute might be not needed)
      df2 = df.groupby([col_time.dt.second,col_time.dt.minute]) 
      # now split the data frame according to group and put them in a list
      list_of_df = [df2.get_group(x) for x in df2.groups]
      # get the data frame from the list and write them 
      for i in range(len(list_of_df)):
        list_of_df[i].to_csv(file_nme[:-4]+str(i)+".csv")

根据时间间隔分割CSV文件

2 个答案: