目录
前言
每次版本迭代需要测试音频的传输耗时，或者比较唇音不同步的时候也需要计算耗时。纯以人工计算显得很麻烦，因此写了该脚本根据日志信息计算传输耗时，并绘制散点图。
主要思路就是通过读取终端配置信息，telnet连接上去，通过命令开启日志打印，对日志信息使用正则过滤，计算出传输的时间信息，计算差值。
配置文件
[RemoteInfo]
host = 127.0.0.1
port = xxxx
username =
password =
音频延时测算
# encoding=utf-8
# 终端自动升级脚本
# --杨靖杰，2020/12/5
# 环境: python2
import re
import telnetlib
import time
import ConfigParser
import os
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
file_path = 'file_created_by_running\\'
def path_check(file_path):
if not os.path.exists(file_path):
os.makedirs(file_path)
def do_telnet(config, commands, filename):
'''Telnet远程登录，并根据预置命令抓取打印保存'''
filename1 = file_path + filename
ff = open(filename1, 'w')
# 连接Telnet服务器
tn = telnetlib.Telnet(config[0], int(config[1]), timeout=10)
# tn.set_debuglevel(2)
# 输入登录用户名
tn.read_until('Username:')
# Windows程序 使用'\n\r'代表换行
tn.write(config[2] + '\n\r')
# 输入登录密码
tn.read_until('Password:')
tn.write(config[3] + '\n\r')
# 登录完毕后执行命令
for command in commands:
tn.write(command + '\n\r')
# 执行完毕后，终止Telnet连接（或输入exit退出）
# tn.close() # tn.write('exit\n')
count = 0
# 不应该实时读取解析
# 写入文件进行分析
while True:
time.sleep(1)
if count == 10:
break
count = count + 1
# cmd编码格式gbk
raw_file = tn.read_very_eager().decode('gbk').strip()
ff.write(raw_file.encode('gbk'))
ff.close()
tn.write('xxxx' + '\n\r')
tn.close()
def file_anyls(filename):
'''根据传入的日志文件，过滤出hook1和hook4的timestamp以及对应的时间'''
ff = open(file_path + filename, 'r')
filename1 = filename + '_' + 'hook1'
ff1 = open(file_path + filename1, 'w')
filename2 = filename + '_' + 'hook4'
ff2 = open(file_path + filename2, 'w')
tt = ff.readlines()
pat1 = re.compile(', ts[=].*?[,]')
pat2 = re.compile('layer_ts[=].*?[ ]')
pat3 = re.compile('capture_ts[=].*?[,]')
pat4 = re.compile('now[=].*?[ ]')
for lines in tt:
if 'hook[1][RTP]' in lines:
line1 = lines
str1 = re.findall(pat1, line1)
str2 = re.findall(pat2, line1)
str3 = str1[0].strip(', ts=').strip(',') + ' ' + str2[0].strip('layer_ts=').strip(',') + '\n'
ff1.write(str3)
if 'hook[4][Frame]' in lines:
line4 = lines.strip()
str4 = re.findall(pat3, line4)
str5 = re.findall(pat4, line4)
str6 = str4[0].strip('capture_ts=').strip(',') + ' ' + str5[0].strip('now=').strip(',') + '\n'
ff2.write(str6)
ff.close()
ff1.close()
ff2.close()
filenamelist = [filename, filename1, filename2]
return filenamelist
def compare_join(filenamelist):
'''实现类似linux join功能'''
ff1 = open(file_path + filenamelist[1], 'r')
ff2 = open(file_path + filenamelist[2], 'r')
filename3 = 'compare_join'
ff3 = open(file_path + filename3, 'w')
tt1 = ff1.readlines()
tt2 = ff2.readlines()
for line2 in tt2:
k2 = line2.strip('\n\r').split()
for line1 in tt1:
k1 = line1.strip('\n\r').split()
if len(k2) != 0 and len(k1) != 0 and k1[0] == k2[0]:
line3 = line1.strip('\n\r') + k2[1] + '\n'
ff3.write(line3)
break
ff1.close()
ff2.close()
ff3.close()
return filename3
def createList(filename):
'''根据传入的过滤好的文件，计算第二列和第三列的差值，并返回一个list'''
numlist = []
count = 0
ff = open(file_path + filename, 'r')
tt = ff.readlines()
ff.close()
ff1 = open(file_path + 'numlist', 'w')
for line in tt:
count = count + 1
if count == 1:
continue
en = line.strip().split(' ')
if len(en) == 3:
dd = int(en[2], 10) - int(en[1], 10)
numlist.append(dd)
ff1.write(str(dd) + '\n')
ff1.close()
return numlist
def numAlys(numlist):
'''计算传入list的max, min, avg的值'''
print "max:", max(numlist), "min:", min(numlist), "avg:", (sum(numlist)/len(numlist))
def generate_statistical_graph(numlist):
'''绘制传入list的散点图'''
y = numlist
x = np.arange(1, len(numlist) + 1)
plt.figure()
plt.scatter(x,y,label='mnet_delay_1_4')
plt.legend()
plt.savefig(file_path + 'scatter.png')
plt.show()
if __name__ == '__main__':
# 配置选项
cf = ConfigParser.ConfigParser()
cf.read("Config.ini")
Host = cf.get('RemoteInfo', 'host') # Telnet服务器IP
Port = cf.get('RemoteInfo', 'port')
Username = cf.get('RemoteInfo', 'username') # 登录用户名
Password = cf.get('RemoteInfo', 'password') # 登录密码
config = [Host, Port, Username, Password]
commands = ['commands']
filename = 'mylog'
path_check(file_path)
do_telnet(config, commands, filename)
filenamelist = file_anyls(filename)
filename = compare_join(filenamelist)
list1 = createList(filename)
numAlys(list1)
generate_statistical_graph(list1)