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二次开发python_Python二次开发在行保后处理中的应用续

news 来源：原创 2024/5/13 14:48:28

上文讲到Python二次开发在行保后处理中的应用。

链接：Python二次开发在行保后处理中的应用

当时编写时没有考虑到后处理效率的问题。比如一个项目中单次结果处理需要123个点的结果，则需要按顺序执行meta进行结果后处理，每次运行meta提取结果的时间约为5s左右。则顺序进行所有结果提取的时间约为615s，大概10分钟左右。这个效率过于低下。

因此对脚本进行优化，需要用到Python的多进程管理包multiprocessing。

import osimport timeimport shutilfrom multiprocessing import Poolsesfile = r'F:\08_Project\08_Pedpro\PedPro\getHIC15.ses'batfile = r'F:\08_Project\08_Pedpro\PedPro\runmeta.bat'dir = os.getcwd()subdirall = []for root,dirs,files in os.walk(dir):  subdirall.append(root)subdircalcu = subdirall[1:]def calulateHIC(case):  os.chdir(case)  shutil.copy(sesfile,case)  shutil.copy(batfile,case)  os.system('runmeta')  print(os.getcwd())if __name__ == "__main__":  pool = Pool(4)  # 创建拥有4个进程数量的进程池  pool.map(calulateHIC, subdircalcu)  pool.close()  # 关闭进程池，不再接受新的进程  pool.join()  # 主进程阻塞等待子进程的退出

其中Pool(4)设置为4个进程，这个可以根据电脑配置情况进行调整。比如可以设置为Pool(40)即同时进行40个meta后处理进程。则整个后处理的时间大概为15s，约0.25分钟。效率大概提高40倍左右。源代码：

import osimport timeimport shutilimport xlwings as xwresultsfile = r'F:\08_Project\08_Pedpro\TS\TotalHIC.xlsx'app = xw.App(visible=True,add_book=False)wb = app.books.add()wb.save(resultsfile)wb = app.books.open(resultsfile)sht = wb.sheets[0]  # or wb.sheets["sheet1"]time.sleep(1)for i , num in enumerate(range(14,-1,-1),start=2):  sht.range("A"+ str(i)).value = "R" + str(num)for i , character in enumerate([chr(i) for i in range(86,65,-1)],start=-10):  sht.range(character + "1").value = "C" + str(i)for i in range(2,17):  for j in range(2,23):    sht.range((i,j)).color = (166, 166, 166)sht.range('A1:V16').row_height =28sht.range('A1:V16').column_width =5list1 = []for i, num in enumerate(range(14,-1,-1),start=1):  list1.append("R" + str(num))rowdict = dict(zip(list1,range(2,17,1)))list3 = []for i , character in enumerate([chr(i) for i in range(86,65,-1)],start=-10):  list3.append("C" + str(i))columdict = dict(zip(list3,[chr(i) for i in range(86,65,-1)]))fill_red = (255, 0, 0)fill_brown = (151, 72, 6)fill_orange = (244, 119, 16)fill_yellow = (255, 255, 0)fill_green = (0, 176, 80)dir = os.getcwd()subdirall = []for root,dirs,files in os.walk(dir):  #print('root_dir:',root)  subdirall.append(root)subdircalcu = subdirall[1:]#print(subdircalcu)for i , case in enumerate(subdircalcu,start=1):#  print(i)  os.chdir(case)  with open('getHIC15.ses.results','r') as g:    for line in g.readlines():      if "HIC15" in line:        HIC15 = line.split(',')[2]        position = case.split("\\")[-1]        c_position = position.split("_")[1]        r_position = position.split("_")[2]        r_posit = "R" + str(abs(int(r_position)))        if int(r_position) >= 0:          c_posit = "C" + c_position        else:          c_posit = "C-" + c_position        sht.range(columdict[c_posit] + str(rowdict[r_posit])).value = round(float(HIC15))        if float(HIC15) >= 1700:          sht.range(columdict[c_posit] + str(rowdict[r_posit])).color = fill_red        elif float(HIC15) >= 1350 and float(HIC15) < 1700:          sht.range(columdict[c_posit] + str(rowdict[r_posit])).color = fill_brown        elif float(HIC15) >= 1000 and float(HIC15) < 1350:          sht.range(columdict[c_posit] + str(rowdict[r_posit])).color = fill_orange        elif float(HIC15) >= 650 and float(HIC15) < 1000:          sht.range(columdict[c_posit] + str(rowdict[r_posit])).color = fill_yellow        else:          sht.range(columdict[c_posit] + str(rowdict[r_posit])).color = fill_green  g.close()  print(os.getcwd())  time.sleep(0.025)wb.save()wb.close()app.quit()

最终运行效果：