一段流量分析工具代码

# !/usr/bin/env python
# -*- coding: cp936 -*-
import  threading,os,time

class  ReadConfig():
    
     def  Base_Config(self):
        
         # 配置话单路径
        TelPath  =   " d:/bak "
         # print TelPath
         return  TelPath
        
    
class  GetPath(ReadConfig):
    
     def  Get_Path(self):
        
         # 获取路径下分析文件，建立字典
        dict  =  {}
        dir_temp  =  []
        file_temp  =  []
        basepath  =  self.Base_Config()
         # print basepath
         for  root, dirs, files  in  os.walk(self.Base_Config()):
             # 获取文件夹节点，获取文件夹对应文件
             for  dir  in  dirs:
                dir_temp.append(dir)
        dir_temp.sort()
         for  i  in  dir_temp:
             # print self.Base_Config()+"/"+str(i)
             for  root, dirs, files  in  os.walk(self.Base_Config() + " / " + str(i)):
                 # 获取对应文件夹下的数据
                file_temp.append(files)
         for  i  in  range(len(dir_temp)):
             # 建立数据字典
            dict[dir_temp[i]]  =  file_temp[i]
         return  basepath,dict

class  ThreadMain(threading.Thread,GetPath):
    
     def   __init__ (self):
        
         # 设定一个分析时间片,单位为分钟
        self.AnalyseTimeArea  =   5
        basepath,dict  =  self.Get_Path()
         # print basepath,dict
        self.dict  =  dict
        self.basepath  =  basepath
    
     def  Thread_Contorl(self):
        
         # 读取字典的索引，索引为文件夹节点self.dict.keys()[i]
        self.Add_Tel_Path_temp2  =  []
         # print self.dict.keys()
         for  i  in  range(len(self.dict.keys())):
            self.Add_Tel_Path_temp1  =  []
             # print self.dict.keys()[i],self.dict[self.dict.keys()[i]]
             for  y  in  range(len(self.dict[self.dict.keys()[i]])):
                 # print self.dict.keys()[i],self.dict[self.dict.keys()[i]]
                 # print len(self.dict[self.dict.keys()[i]])
               self.Add_Tel_Path  =   self.basepath + " / " + self.dict.keys()[i] + " / " + self.dict[self.dict.keys()[i]][y]
               self.Add_Tel_Path_temp1.append(self.Add_Tel_Path)
             # print Add_Tel_Path_temp1
            self.Add_Tel_Path_temp2.append(self.Add_Tel_Path_temp1)
         # Add_Tel_Path_temp2得到已文件夹节点分类数组，格式如下[[2008-3-8],[2008-3-10],[2008-3-9]]
         return  self.Add_Tel_Path_temp2
    
     # ================================================================================
     #  已文件夹为单位进行时间分割计算每日的话单总流量
     #  Method Name：AnalyseMethod_Countdayflow
     #  Author：xinkai Add:2008-3-10
     # ================================================================================
     def  AnalyseMethod_Countdayflow(self):
        
        self.CountFlow  =  0
         # 由线程类获得分析数组
        self.AnalyseList  =  self.Thread_Contorl()
         # print AnalyseList
         for  i  in  range(len(self.AnalyseList)):
            self.CountFlow  =  0
             # print self.dict.keys()[i],AnalyseList[i]
             # ===============================================================================
             #             此处需要加判断日期以及有效话单
             # ===============================================================================
             for  y  in  range(len(self.AnalyseList[i])):
                 # print AnalyseList[i][y]
                self.AnalyseData  =  open(self.AnalyseList[i][y], ' r ' )
                self.CountFlow  +=  len(self.AnalyseData.readlines())
                 # print self.dict.keys()[i]+str(len(AnalyseData.readlines()))+" "
             print  self.dict.keys()[i] + " 当日数据总流量为: " + str(self.CountFlow)
            
     # ================================================================================
     #  已文件夹为单位进行时间分割按照划定的时间片对每日话单分时流量进行统计
     #  Method Name：AnalyseMethod_CountTimeFlow
     #  Author：xinkai Add:2008-3-10
     # ================================================================================
     def  AnalyseMethod_CountTimeFlow(self):
        
        Analyse_CountTimeFlow  =  open( ' Analyse_CountTimeFlow.log ' , ' w ' )
         # 由线程类获得分析数组
        self.AnalyseList  =  self.Thread_Contorl()
         for  i  in  range(len(self.AnalyseList)):
            temp  =  []
            self.AnalyseStack  =  []
            self.AnalyseStackSend  =  []
             for  y  in  range(len(self.AnalyseList[i])):
                 # 已时间文件夹为分割点，分类读取话单进行分析
                 # 用来计算每个文件中每个话单记录的时间堆栈
                self.AnalyseData  =  open(self.AnalyseList[i][y], ' r ' )
                self.AnalyseStackSend.append(self.AnalyseData.readlines())
                 # 用来计算基础时间轴的堆栈AnalyseStack
                self.AnalyseData  =  open(self.AnalyseList[i][y], ' r ' )
                self.AnalyseStack.append(self.AnalyseData.readlines()[0])
             # 已文件夹时间点分割，获取基础时间轴
            self.BaseTimeCenter  =  self.AnalyseStack[0].split( ' , ' )[ 21 ]
             # 转化话单发送时间为整数
            self.ChangeBaseTime  =  self.ChageTime(self.BaseTimeCenter)
             for  h  in  range(len(self.AnalyseList[i])):
                 for  z  in  self.AnalyseStackSend[h]:
                    self.TelTime  =  self.ChageTime(z.split( ' , ' )[ 21 ])
                     # print str(self.TelTime)+"///"+str(self.ChangeBaseTime)
                     import  math
                     # 获得已基础时间为轴的时间差值
                     # print int(math.fabs(self.TelTime - self.ChangeBaseTime))/60
                    temp.append((int(math.fabs(self.TelTime  -  self.ChangeBaseTime)) / 60 )  /  self.AnalyseTimeArea)
             print  self.dict.keys()[i]
            Analyse_CountTimeFlow.writelines( " 话单时间:%s 初始时间片    时间片    分时流量 "   %  (self.dict.keys()[i]))
            Analyse_CountTimeFlow.close()
             for  j  in  range( 1440 / int(self.AnalyseTimeArea)):
                 if  temp.count(j)  <>  0:
                    Analyse_CountTimeFlow  =  open( ' Analyse_CountTimeFlow.log ' , ' a ' )
                     print   " 分析时间片:%s分钟 ; 第%s时间片 ; 分时流量为%s条 ; "   %  (self.AnalyseTimeArea,j,temp.count(j))
                    Analyse_CountTimeFlow.writelines( " %s    %s    %s "   %  (self.AnalyseTimeArea,j,temp.count(j)))
                
     def  ChageTime(self,datatime):
        
         # 初始化变量
        self.YearMD  =   ""
        self.TimeCS  =   ""
        
         # 引用时间参数
        self.datatime  =  datatime
        self.SplitDataTime1  =  self.datatime.split( '   ' )
        self.SplitDataTime2  =  self.SplitDataTime1[0].split( ' / ' )
        self.SplitDataTime3  =  self.SplitDataTime1[ 1 ].split( ' : ' )
         # 分割结果['2008', '03', '10'] ['11', '18', '18']
        
         # 组合分割数据转换时间为整数
         for  i  in  self.SplitDataTime2:
            self.YearMD  +=  i
         for  h  in  self.SplitDataTime3:
            self.TimeCS  +=  h
        self.newTime  =  self.YearMD  +  self.TimeCS
         return  int(self.newTime)
        
     def   __del__ (self):
         pass
    
class  ControlThread(ThreadMain):
    
     def   __init__ (self):
        
        basepath,dict  =  self.Get_Path()
        self.dict  =  dict
        self.basepath  =  basepath
        
     def  Control_Thread(self):
        
         # 控制使用分析线程
         print   " ----------------------------------------- "
        ObjectThread  =  ThreadMain()
         print   " 开始计算每日流量： "
        ObjectThread.AnalyseMethod_Countdayflow()
         print   " 计算结束 "
         print   " ----------------------------------------- "
         import  time
        time.sleep( 0.01 )
         print   " 开始计算分时流量： "
        ObjectThread.AnalyseMethod_CountTimeFlow()
         print   " 计算结束 "
         print   " ----------------------------------------- "
            
if   __name__   ==   " __main__ " :
    
    ObjectControl  =  ControlThread()
    ObjectControl.Control_Thread()