本脚本可以用于有性能测试监控需求的人使用，用于tcp连接数的监控# -*- coding: UTF-8 -*-
# author=baird_xiang
import os
import sys
import time
import re
import copy
new_content = [] #去掉\n的浮点型连接数
nums = [] #连接数
connect_times = [] #连接数的时间
d_nums = [] #新增连接数
add_connect_times = [] #新增连接数的时间
new_connects = [] #加入了时间的连接数 格式'2018-05-02 16:50:18 || 2.0'
#获取tcp连接数
def get_connects(ras_ip,end_time):
while True:
search_command = 'netstat -nat|grep "%s" |wc -l'%ras_ip
num_connects = os.popen(search_command).read()
print num_connects
nums.append(num_connects)
time.sleep(1)
#avg_num = sum(nums)/len(nums)
now_time = get_time()
txt_time = get_time()
connect_times.append(txt_time)
if now_time == end_time:
sys.exit()
else:
pass
#数据输入文本保存并导出
def in_out_txt():
now_pwd = os.getcwd()
file_name_time = get_time()
file_name = now_pwd + '/tcp_connect_numbers_%s.txt'%file_name_time#tcp连接数的文本
file_name_avage = now_pwd + '/avage_tcp_connects_%s.txt'%file_name_time #平均连接数的文本
#写入文本
file1 = open(file_name,'w')
for i in nums:
i_num= re.findall('\d+', i)
file1.write(i_num[0] + '\n')
file1.close()
#读出文本
file2 = open(file_name,'r')
content = file2.readlines()
for i in range(len(content)):
content[i] = content[i][:len(content[i])-1]
file2.close()
#获得每秒新增连接数
get_add_file = open(file_name,'r')
add_conn_content = get_add_file.readlines()
for i in range(0,len(add_conn_content)):
j = i+1
if j < len(add_conn_content):
d_value = int(add_conn_content[j]) - int(add_conn_content[i])
d_nums.append(d_value)
#将nums中' 2\n'转化为浮点数'2' 保存在new_content 中
for i in content:
ii = float(i)
new_content.append(ii)
#计算平均连接数
avg_number = round(sum(new_content)/len(new_content),4)
#加入时间
print len(nums)
print len(connect_times)
for i in range(0,len(nums)):
new_connects_data = str(connect_times[i]) + ' || ' + str(new_content[i])
new_connects.append(new_connects_data)
file3 = open(file_name,'w')
for i in range(0,len(new_connects)):
file3.write(new_connects[i] + '\n')
file3.close()
#平均连接数写入avage_tcp_connects.txt文本
file_avage = open(file_name_avage,'w')
file_avage.write(str(avg_number) + '\n')
file_avage.close()
return avg_number
#获取当前时间不split
def get_time():
this_time = time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(time.time()))
return this_time
#split时间
def split_time(input_time):
times = re.split("[a-z\-]|[a-z\:]|\s", input_time)
out_time = times
return out_time
if __name__ == '__main__':
ras_ip = 'com.apple.net.utun_control' #获取连接数的进程或者端口
end_time = '2018-05-18 18:20:00' #脚本停止时间
try :
get_connects(ras_ip, end_time)
except :
avg_number = in_out_txt()
print avg_numbe以上脚本实习了对mac，liux指定进程或端口的连接数监控，并按时间对应保存到txt每一行，并且计算出平均值，txt格式按end_time为后缀保存
以下脚本可以运行在有gui的系统之上，对上面脚本产生的txt进行粗略绘图，以end_time来进行读取名字获取txt
# -*- coding: UTF-8 -*-
# author=baird_xiang
import os
import sys
import time
import re
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib.ticker as ticker
import copy
d_nums = [] #新增连接数
nums = [] #连接数
connect_times = [] #连接数的时间
add_connect_times = [] #新增连接数的时间
tick_spacing = 3 #绘图横坐标显示间隔
#数据输入文本保存并导出
def in_out_txt(file_name):
#tcp连接数的文本
#平均连接数的文本
#读出文本
file2 = open(file_name,'r')
content = file2.readlines()
for i in range(len(content)):
content[i] = content[i][:len(content[i])-1]
file2.close()
#读出文本，将时间和连接数分开到nums和connect——times两个列表
for i in content:
ll = re.split('\|\|',i)
connect_times.append(ll[0])
nums.append(float(ll[1]))
#获得每秒新增连接数
for i in range(0,len(nums)):
j = i+1
if j < len(nums):
d_value = float(nums[j]) - float(nums[i])
d_nums.append(d_value)
print 'd_nums ',d_nums
#获取当前时间不split
def get_time():
this_time = time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(time.time()))
return this_time
#split时间
def split_time(input_time):
times = re.split("[a-z\-]|[a-z\:]|\s", input_time)
out_time = times
return out_time
#连接数绘图
def print_img1(end_time,cut_time,cut_tcpConn):
now_pwd = os.getcwd()
img_path = now_pwd + '/img_%s_tcpconn.png'%end_time#保存绘制好的图形到当前路径
#连接数绘图
plt.figure()
ax1 = plt.subplot(1,1,1)
ax1.plot(cut_time,cut_tcpConn)
ax1.set_title('TCP Connects')
ax1.xaxis.set_major_locator(ticker.MultipleLocator(tick_spacing))
plt.gcf().autofmt_xdate()
plt.savefig(img_path)#保存图片
plt.show()
#新增连接数绘图
def print_img2(end_time,cut_add_time,cut_tcpAddConn):
now_pwd = os.getcwd()
img_path = now_pwd + '/img_%s_addconn.png'%end_time#保存绘制好的图形到当前路径
plt.figure()
ax2 = plt.subplot(1,1,1)
ax2.plot(cut_add_time,cut_tcpAddConn)
ax2.set_title('Add TCP Connects per s')
ax2.xaxis.set_major_locator(ticker.MultipleLocator(tick_spacing))
plt.gcf().autofmt_xdate()
plt.savefig(img_path)#保存图片
plt.show()
def cut_Conn_time(end_time):
cut_tcpConn = [] #缩略的连接数
cut_tcpAddConn = [] #缩略的新增连接数
cut_time = [] #缩略的连接数时间
cut_add_time = [] #缩略的新增连接数时间
split_end_time = split_time(end_time) #split结束时间
split_start_time = connect_times[0] #获取开始时间
split_start_time = split_time(split_start_time) #split 开始时间
for i in range(1,len(connect_times)):
add_connect_times.append(connect_times[i])
print 'add_connect_times',add_connect_times
#大于一天，10分钟采样一次
if float(split_end_time[2]) - float(split_start_time[2]) >= 1: #运行时间大于一天
for i in range(0,len(nums),600):
try:#处理越界
avage_tcpConn = (nums[i] + nums[i+600])/2
cut_tcpConn.append(avage_tcpConn)
except:
break
for i in range(0,len(d_nums),600):
try:#处理越界
avage_addConn = (d_nums[i] + d_nums[i+600])/2
cut_tcpAddConn.append(avage_addConn)
except:
break
for i in range(0,len(add_connect_times),600): #处理新增连接数时间
avage_add_ConnTime = add_connect_times[i]
cut_add_time.append(avage_add_ConnTime)
for i in range(0,len(connect_times),600):#处理连接数时间
avage_ConnTime = connect_times[i]
cut_time.append(avage_ConnTime)
list_pop1=cut_add_time.pop(-1)
list_pop2=cut_time.pop(-1)
return cut_tcpConn,cut_tcpAddConn,cut_time,cut_add_time
#大于一小时，3分钟采样一次
elif float(split_end_time[3]) - float(split_start_time[3]) >=1 :
for i in range(0,len(nums),180):
try:#处理越界
avage_tcpConn = (nums[i] + nums[i+180])/2
cut_tcpConn.append(avage_tcpConn)
except:
break
for i in range(0,len(d_nums),180):
try:#处理越界
avage_addConn = (d_nums[i] + d_nums[i+180])/2
cut_tcpAddConn.append(avage_addConn)
except:
break
for i in range(0,len(add_connect_times),180): #处理新增连接数时间
avage_add_ConnTime = add_connect_times[i]
cut_add_time.append(avage_add_ConnTime)
for i in range(0,len(connect_times),180):#处理连接数时间
avage_ConnTime = connect_times[i]
cut_time.append(avage_ConnTime)
list_pop=cut_add_time.pop(-1)
list_pop2=cut_time.pop(-1)
return cut_tcpConn,cut_tcpAddConn,cut_time,cut_add_time
#3分钟以上，一小时以下
elif float(split_end_time[4]) - float(split_start_time[4]) >= 3 :
for i in range(0,len(nums),60):
try:#处理越界
avage_tcpConn = (nums[i] + nums[i+60])/2
cut_tcpConn.append(avage_tcpConn)
except:
break
for i in range(0,len(d_nums),60):
try:#处理越界
avage_addConn = (d_nums[i] + d_nums[i+60])/2
cut_tcpAddConn.append(avage_addConn)
except:
break
for i in range(0,len(add_connect_times),60): #处理新增连接数时间
avage_add_ConnTime = add_connect_times[i]
cut_add_time.append(avage_add_ConnTime)
for i in range(0,len(connect_times),60):#处理连接数时间
avage_ConnTime = connect_times[i]
cut_time.append(avage_ConnTime)
list_pop=cut_add_time.pop(-1)
list_pop2=cut_time.pop(-1)
return cut_tcpConn,cut_tcpAddConn,cut_time,cut_add_time
#3分钟内
else:
cut_tcpAddConn = copy.deepcopy(d_nums)
cut_tcpConn = copy.deepcopy(nums)
cut_time = copy.deepcopy(connect_times)
cut_add_time = copy.deepcopy(add_connect_times)
return cut_tcpConn,cut_tcpAddConn,cut_time,cut_add_time
if __name__ == '__main__':
end_time = '2018-05-10 15:27:00'
py_path = os.getcwd()
file_name = '%s/tcp_connect_numbers_%s.txt'%(py_path,end_time)
in_out_txt(file_name)
print 'nums ',nums
cut_tcpConn,cut_tcpAddConn,cut_time,cut_add_time = cut_Conn_time(end_time)
print 'cut_tcpConn ',cut_tcpConn
print 'cut_tcpAddConn ' ,cut_tcpAddConn
print 'cut_time ',cut_time
print 'cut_add_time ',cut_add_time
print_img1(end_time,cut_time,cut_tcpConn)
print_img2(end_time,cut_add_time,cut_tcpAddConn)版权声明：本文为a1496785原创文章，遵循CC 4.0 BY-SA版权协议，转载请附上原文出处链接和本声明。