Automated Testing with python-drawing and scientific computing with Python

In performance testing, we often need to plot the CPU memory or IO trend chart. It is estimated that most people in the university have studied matlib and learned the power of matlib. Python provides a powerful drawing module matplotlib, Which is based entirely on the matlib library. Go to the official website and check http://matplotlib.org /.

Drawing a trend chart of CPU, memory, and IO in performance testing does not require many complex functions. It is a 2D chart. Check the Code directly! You can download this Code directly. It is compatible with CPU/Memory/IO, or multiple processes. The file name is draw_trend.py. Usage, draw_trend.py data_file cpu/mem/io, the reader only needs to process the monitoring data in the format following the code.

#!/usr/bin/env python#coding=utf-8import matplotlib as mplmpl.use('Agg')import matplotlib.pyplot as pltimport datetime as dtfrom matplotlib.font_manager import FontPropertiesimport sysdef draw_trend(data_file,object_type):    fontP = FontProperties()    fontP.set_size('small')    data=open(data_file,"r")    lines=data.readlines()    data.close()    lable_list=lines[0].split(None)    #data={"lable_name":[x,y1,y2],x:[1,2,4],y1:[2,4],y3:[4,5]}    lable_name=[]    data_list=[]    for lable in lable_list:        lable_name.append(lable)        data_list.append([])    for line in lines[1:]:        line_list=line.strip().split(None)        #print line_list        #print data_list        for i in xrange(len(data_list)):            #print data_list            if i==0:                data_list[0].append(dt.datetime(int(line_list[0][0:4]), int(line_list[0][4:6]),                    int(line_list[0][6:8]),int(line_list[0][9:11]),                    int(line_list[0][12:14]),int(line_list[0][15:17])))            else:                if object_type=="mem":                    data_list[i].append(float(line_list[i]))                else:                    data_list[i].append(float(line_list[i]))    #print data_list    '''    dates = [dt.datetime.today() + dt.timedelta(days=i) for i in range(10)]    values = np.random.rand(len(dates))    '''    mpl_date2num=mpl.dates.date2num(data_list[0])    for y_value in data_list[1:]:        plt.plot_date(mpl_date2num, y_value,"-",label=lable_name[data_list.index(y_value)])    xAxis = plt.axes().xaxis    dateFmt = mpl.dates.DateFormatter('%H:%M')    #daysLoc = mpl.dates.DayLocator()    #minLoca=mpl.dates.MinuteLocator(interval=2)    #secLoc=mpl.dates.SecondLocator(interval=60)    xAxis.set_major_formatter(dateFmt)    #xAxis.set_major_locator(minLoca)    #xAxis.set_minor_locator(secLoc)    #plt.legend(loc='upper right',bbox_to_anchor=(1.0, 1.07),prop = fontP,ncol=len(lable_name)-1)    #leg=plt.legend(loc='upper right',prop = fontP)    leg=plt.legend(loc='upper right',prop={'size':8})    leg.get_frame().set_alpha(0.5)    plt.tick_params(axis='both', labelsize=8)    plt.xlabel('Time')    if object_type=="mem":        plt.ylabel('Memory/unit M')    if  object_type=="io":        plt.ylabel('IO Busy')    if  object_type=="cpu":        plt.ylabel('CPU Usage Percent')    plt.savefig(data_file+".png")    #plt.show()try:    draw_trend(sys.argv[1],sys.argv[2])except:    print "error command, right command should be:","python draw_matlab.py datafile  mem/io/cpu"

Upload a CPU sample.

The data must be in the format of the first row X-axis title, which is separated by spaces from the corresponding drawing object. View the following data

Time Process1 Process2 Process3 Process4 Process5
20120410-13:13:47 1 1 0 80 2
20120410-13:13:53 0 0 81 0
20120410-13:13:59 4 2 0 82 6
20120410-13:14:05 4 2 0 83 6
20120410-13:14:11 5 3 0 84 8
20120410-13:14:17 5 3 0 85 8
20120410-13:14:23 5 2 0 93 7
20120410-13:14:29 5 2 0 93 7
20120410-13:14:35 4 2 0 94 6
20120410-13:14:41 5 3 0 92 8
20120410-13:14:47 4 3 0 93 7
20120410-13:14:53 4 2 0 94 6
20120410-13:14:59 4 2 0 94 6
20120410-13:15:05 3 2 0 95 5
20120410-13:15:11 4 2 0 94 6
20120410-13:15:17 4 2 0 94 6
20120410-13:15:23 4 1 0 95 5
20120410-13:15:29 5 1 0 94 6