使用python提取iperf数据并绘制吞吐率曲线

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Server listening on TCP port 9009

TCP window size: 85.3 KByte (default)

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[  6] local 10.0.0.10 port 9009 connected with 10.0.0.11 port 39328

[ ID] Interval       Transfer     Bandwidth

[  6]  0.0- 1.0 sec  10.2 MBytes  85.3 Mbits/sec

[  6]  1.0- 2.0 sec  11.4 MBytes  95.7 Mbits/sec

[  6]  2.0- 3.0 sec  11.4 MBytes  95.6 Mbits/sec

[  6]  3.0- 4.0 sec  11.4 MBytes  95.7 Mbits/sec

[  6]  4.0- 5.0 sec  11.4 MBytes  95.6 Mbits/sec

[  6]  5.0- 6.0 sec  11.4 MBytes  95.7 Mbits/sec

[  6]  6.0- 7.0 sec  11.4 MBytes  95.6 Mbits/sec

[  6]  7.0- 8.0 sec  11.4 MBytes  95.6 Mbits/sec

[  6]  8.0- 9.0 sec  11.4 MBytes  95.6 Mbits/sec

[  6]  9.0-10.0 sec  11.4 MBytes  95.7 Mbits/sec

[  6] 10.0-11.0 sec  11.4 MBytes  95.6 Mbits/sec

[  6] 11.0-12.0 sec  11.4 MBytes  95.7 Mbits/sec

[  6] 12.0-13.0 sec  11.4 MBytes  95.6 Mbits/sec

[  6] 13.0-14.0 sec  11.4 MBytes  95.7 Mbits/sec

[  6] 14.0-15.0 sec  11.4 MBytes  95.6 Mbits/sec

[  6] 15.0-16.0 sec  11.4 MBytes  95.6 Mbits/sec

[  6] 16.0-17.0 sec  11.4 MBytes  95.7 Mbits/sec

[  6] 17.0-18.0 sec  11.4 MBytes  95.6 Mbits/sec

[  6] 18.0-19.0 sec  11.4 MBytes  95.6 Mbits/sec

[  6] 19.0-20.0 sec  11.4 MBytes  95.7 Mbits/sec

[  6]  0.0-20.6 sec   234 MBytes  95.1 Mbits/sec

import re

import matplotlib.pyplot as plt

import numpy as np



time_list = []

rate_list = []



with open('./iperf-log.txt','r') as f:# iperf-log.txt为iperf日志文件名

    row_data = f.readlines() # 读取iperf日志文件的每一行至一个list中

    for line in row_data:    # 利用正则表达式进行匹配，可根据实际情况更改匹配内容

        time = re.findall(r"-(.*) sec", line)

        rate = re.findall(r"MBytes  (.*) Mbits", line)

        if(len(time)>0):     # 当前行中有吞吐和时间数据时对数据进行存储

            print(time)

            time_list.append(float(time[0]))

            rate_list.append(float(rate[0]))



plt.figure()

plt.plot(time_list, rate_list)

plt.xlabel('Time(sec)')

plt.ylabel('Bandwidth(Mbits/sec)')

plt.grid()

plt.show()