Many companies in the data recording of all aspects of the work, almost entirely by manual completion, time-consuming and laborious, easy to make mistakes. For example, in the warehouse operation management process, daily activities such as purchase, return, shipment, inventory, etc. are all done manually. Due to the filling of trivial and complicated forms and data, the workload is increased, so the work is easy to make mistakes and inefficiency. Faced with this situation, many companies have asked to introduce a computer management system, but after the introduction of the computer system, it was found that only half of the problem was solved, because with the support of computer software, only the work of conditional placement of the computer can be solved. Occasionally, the manual transcription of the unconditional placement of the computer still cannot be resolved. Even if the computer solves some manual transcription conditions, it cannot change the bottleneck caused by the large number of printed form data being re-entered at the next computer work point. If you use the PT923 or LK934 collector device, configure a set of effective workflow. , timely and accurate grasp of the situation of each commodity in each order. Bar code scanning registration of items with PT923 or LK934. You can also modify the item query. At the same time, the item information is directly uploaded to the computing center through the MODEM. After the collector device is used, each link recorded in the data realizes automatic registration of data, thereby avoiding the problem of newly entering data. Collect server performance data by combining python scripts with linux commands. Determine whether the data collection is over according to the current number of tcp links of the server during the test. The script mainly has three operations. The first one is the preliminary collection of performance data. The data is written to the original file by calling the sar and iostat commands of linux. After the acquisition is completed, the performance indicator extraction script is executed, and the valid data is extracted from the original indicator file and written into the final file, and the packaging operation is performed. The code is only for me to meet the needs of the work, not very good, can meet the needs of the work, nothing more. The configuration file that extracts data from the original file, according to the server language type: abstractConf_ch.xml—Chinese abstractConf_en.xml—English The configuration file mainly indicates the original file path and uses the linux cat, egrep, and awk commands to extract data from the file as required. "? Xml version='1.0' encoding='utf-8'? 》 "abstract" Res_file name=“res/CPU†"uniqflag" CPU "/uniqflag" "object_file" result/cpu_status "/object_file" "graphtitle" Cpu_Status "/graphtitle" Linelabel %user %system "/linelabel" "x_y_label" Time(s) Cpu_Percent(%)"/x_y_label" "cmd"cat %s | egrep -v "Linux|^$|%s" | awk 'BEGIN {print "%s%s%s"}{if($2 !~/AM|PM/) print $3,$5 }' 》》 %s//cmd /res_file . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "/abstract"12345678910111213 # coding:utf-8 #__author__ = 'Libiao' Import subprocess Class GetLinkingNumber(object): Def __init__(self): Pass Def getLinkingNumber(serlf,servers): Ret = [] If isinstance(servers,str): Num = subprocess.Popen("netstat -tnap | grep tcp | grep %s | wc -l" %servers,stdout=subprocess.PIPE,shell=True).stdout Ret.append(int(num.readline().strip())) Elif isinstance(servers,dict): For k,v in servers.items(): Num = subprocess.Popen("netstat -tnap | grep tcp | grep %s | wc -l" %v,stdout=subprocess.PIPE,shell=True).stdout Ret.append(int(num.readline().strip())) Else: Pass Return ret123456789101112131415161718192021 Need linux command to be executed by the main program #! /bin/bash Sar -n DEV 10 》"res/NetWork & Iostat -x -d -k 10 》res/Disk & Sar -r 10 》"res/Memory & Sar -q 10 》res/System_load_average & Sar -u 10 》"res/CPU & Sar -b 10 》res/TPS &12345678 #-*- coding:utf-8 -*- """ Reated on October 16, 2015 @author: LiBiao "" Import time, os Import subprocess Import multiprocessing From write_log import writeLog Import del_old_file From record_test_data import Record_Data From server_memory_collect import serverMemoryCollect From get_linking_number import GetLinkingNumber #Parameters that need to be set manually SERVERS_D = {'1935':'srs-rtmp', '18080': 'srs-hls', '80': 'nginx'} # can enter srs or nginx or ATS #Intervals INTERVAL_TIME = 10 Class KPI_Collect(object): Def __init__(self): self.getLinkNum = GetLinkingNumber() self.TCP_COUNT = self.getLinkNum.getLinkingNumber(SERVERS_D) self.tcpRecord = Record_Data("res/linking_number") Def getStr(self,alist): Ret = "" For s in alist: Ret += str(s) Ret += ' ' Return [ret.rstrip(' ')] #Perform server performance data collection by calling collect.sh script Def sys_kpi_collect(self): Flag = '1' Cmds = ['. /collect.sh'] Popen = subprocess.Popen(cmds[0],stdout=subprocess.PIPE,shell=True) Pid = popen.pid writeLog('INFO','》》》》》 Performance indicator collection process is in progress. . . . Self.to_stop_subprocess(flag,popen) # Stop the open handle of the program executed by sys_kpi_collect Def to_stop_subprocess(self,flag,popen): Curr_tcpnum = self.getLinkNum.getLinkingNumber(SERVERS_D) self.tcpRecord.recordData(["srs&nginx Linking","%s %s %s" %tuple(SERVERS_D.values()), "Time(s) Numbers"]) self.tcpRecord.recordData(self.getStr(self.TCP_COUNT)) If flag is '1': Loops = 0 While True: If sum(curr_tcpnum) <<= sum(self.TCP_COUNT): If loops == 15: #15sThe number of current connections is less than the number of initial connections, exit the program # Delete the sar and iostat processes that still exist in the system Names = ['sar','iostat'] Cmd = “killall -9 %s %s†%tuple(names) Subprocess.call(cmd,shell=True) #terminate the child process Popen.kill() If subprocess.Popen.poll(popen) is not None: Break Else: writeLog("INFO",r"》》》》 Waiting for the child process to terminate") Else: Loops += 5 Time.sleep(5) Else: Loops = 0 Time.sleep(INTERVAL_TIME)#waiting INTERVAL_TIME time Curr_tcpnum = self.getLinkNum.getLinkingNumber(SERVERS_D) self.tcpRecord.recordData(self.getStr(curr_tcpnum)) writeLog("INFO",r"》》》》†Performance indicator acquisition completedâ€) Else: While True: If subprocess.Popen.poll(popen) is not None: Break Else: writeLog("INFO",r"》》》》 Waiting for the child process to terminate") writeLog("INFO",r"》》》》†Performance indicator acquisition completedâ€) # Determine whether the sar and iostat processes remain in the system. Def is_process_exists(self,name): Cmd = “ps ax | grep %s | grep -v grep†%name p = subprocess.Popen(cmd,stdout=subprocess.PIPE,shell=True) P.wait() If p.stdout.readline(): Return 1 Return 0 Def main_start(self): Start_times = 0.0 timeRecord = Record_Data("res/timeConsum") For server,num in zip(SERVERS_D.values(),self.TCP_COUNT): writeLog("INFO",r"》》》 Initial %s service connection %d†%(server,num)) curr_tcpN = self.getLinkNum.getLinkingNumber(SERVERS_D) Time.sleep(10) While True: If not sum(curr_tcpN) <<= sum(self.TCP_COUNT): Start_times = time.time() For server,num in zip(SERVERS_D.values(),curr_tcpN): writeLog("INFO",r""》》》 The indicator collection task starts, the current %s connection number %d†%(server,num)) # Delete old kpi file del_old_file.Del_Old_File("res/").del_old_file() # separate thread to execute other services (srs, nginx, etc.) process memory metrics collection task For port,server in SERVERS_D.items(): multiprocessing.Process(target=serverMemoryCollect,args=([port,server],INTERVAL_TIME,sum(self.TCP_COUNT),self.getLinkNum)).start() #采集 server system kpi indicator Self.sys_kpi_collect() writeLog("INFO",r"》》》》》 Performance data collection is over!â€) Time_consum = time.time() - start_times timeRecord.recordData(["%s" %str(time_consum)]) Break Else: Time.sleep(1) curr_tcpN = self.getLinkNum.getLinkingNumber(SERVERS_D) If __name__ == '__main__': kpiCollect = KPI_Collect() kpiCollect.main_start() #-*- coding:utf-8 -*- """ Reated on October 16, 2015 @author: LiBiao "" Import time Import subprocess From write_log import writeLog From record_test_data import Record_Data #Record the memory of server used Def serverMemoryCollect(servers,intervaltime,tcpNum,getLinkObj): getLinkNum = getLinkObj memRecord = Record_Data("res/%s" %(servers[1]+":"+servers[0])) Cmd = “ps -ef | grep %s | grep -v grep | awk \'{print $2}\'†%servers[1] f = subprocess.Popen(cmd,stdout=subprocess.PIPE,shell=True) writeLog("INFO","》》》》》 %s indicator collection process execution... "%servers[1]) Pids = [pid.strip() for pid in f.stdout] Heard = [servers[1],'used','Linking_Number Memory_Capacity(MB)'] Try: memRecord.recordData(heard) curr_tcpN = sum(getLinkNum.getLinkingNumber(servers[0])) Loops = 0 While True: Vrss = [] For p in pids: Cmd2 = "cat /proc/%s/status | grep VmRSS | awk \'{print $2}\'" %p Rss = subprocess.Popen(cmd2,stdout=subprocess.PIPE,shell=True).stdout Vrss.append(int(rss.readline().strip())) memRecord.recordData(['%s' %str((sum(vrss)/1024)))) If curr_tcpN <<= tcpNum: If loops == 15: Within #15s, the current number of connections is less than the initial number of connections, the program exits Break Else: Loops += 5 Time.sleep(5) Else: Loops = 0 Time.sleep(intervaltime) curr_tcpN = sum(getLinkNum.getLinkingNumber(servers[0])) writeLog("INFO",r"》》》》 %s process memory acquisition completed "%servers[1]) Except IOError as err: writeLog("INFO","File error: " + str(err)) Return 0 # -*- coding: utf-8 -*- ''' Created on September 14, 2015 @author: LiBiao ''' Import os,time Import subprocess Import getCmds Import del_old_file From write_log import writeLog #Requires manually configured data #SERVER_NAME = ['srs_2.0.0.','nginx']#'nginx' # can enter nginx or srs SERVERS_D = {'1935': 'srs-rtmp', '18080': 'srs-hls', '80': 'nginx'} #系统è¯è¨€ç¼–ç LANG = "en_US.UTF-8" #Get the language currently used by the system Def getSysLANG(): Popen = subprocess.Popen('echo $LANG',stdout=subprocess.PIPE,shell=True) Return popen.stdout.read().strip() # Get the corresponding configuration file path according to the system language code Def getConfPath(): If getSysLANG() == LANG: Return "./conf/abstractConf_en.xml" Return "./conf/abstractConf_ch.xml" Class AbstractKPI(object): Def __init__(self, *args): (self.cmds,) = args Def abstract_kpi(self): For cmd in self.cmds: # print cmd subprocess.Popen(cmd,stdout=subprocess.PIPE,shell=True) #Get the local ip address, used to generate data different from other machines Def get_local_ip(): Try: Ip = os.popen("ifconfig | grep 'inet addr' | awk '{print $2}'").read() Ip = ip[ip.find(':') + 1:ip.find('')] Except Exception,e: Print e Return ip #Package the final collected data Def to_tar(): Ip = get_local_ip() Times = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) Subprocess.call("cp res/linking_number res/timeConsum" +"res/%s"*len(SERVERS_D.items()) %tuple([v + "\:" + k for k,v in SERVERS_D.items( )]) + "result/", shell=True) Files = ["result/" + filename for filename in os.listdir("result/")] Cmd = 'tar -cf SYS_KPI_'+ ip + "_" + times + '.tar' + ' %s'*len(files) %tuple(files) Try: Subprocess.call(cmd,shell=True) Except Exception as err: writeLog("ERROR",r"》》》》†File compression error %s†%str(err)) Exit() writeLog("INFO",r"》》》》†The indicator file is packaged and completedâ€) #Script main entry function Def main_start(): # Delete old kpi file del_old_file.Del_Old_File("result/").del_old_file() #Get to the configuration file path Confpath = getConfPath() #call getCmds to get the command to parse the kpi file Cmds = getCmds.Get_Cmds(confpath).getcmds() #Extract useful data from the original indicator file AbstractKPI(cmds).abstract_kpi() #Pack up the parsed kpi file in the result directory To_tar() writeLog("INFO",r"》》》》†Index data extraction and packaging completedâ€) If __name__ == '__main__': Main_start() The command to collect data in the script is linux. In fact, this is not the most suitable way to deal with it. It was only used to meet the needs of the work. Some methods in Python third-party module psutil are currently being used to perform server performance data collection, so that the script will be more in line with the Python development model. The utility model provides a scanner capable of scanning one-dimensional and two-dimensional barcodes, comprising: a casing and a scanning device, a start button is arranged on the casing, the scanning device is provided with a circuit board, and the circuit board carries a microcomputer A control processing module, an image capture module, and a laser light module; and the key point of the present invention is that the laser light module can emit a linear laser light and project it on a barcode, and the linear laser light is used as an indicator light (pointer). ), but when the scanning device wants to read the barcode, immediately turn off the linear laser light so as not to cause interference and affect the reading efficiency of the scanner. 1D Scanner ,1D Wired Barcode Scanner,1D 2D Barcode Scanner,1D Bar Code Scanner ShengXiaoBang(GZ) Material Union Technology Co.Ltd , https://www.sxbgz.com
