Question

我尝试比较2个csv文件，每个文件包含100000行和10列。我运行这个代码它工作，但它只使用一个CPU的线程，而我有8个核心。我希望这段代码使用所有的cpu线程。我有搜索，我发现了并行的想法。但是当我尝试在这个python代码中对for循环应用并行时，它不起作用。如何申请并行此代码？提前谢谢你的帮助！

import csv  
#read csv files
f1= file('host.csv','r')
f2= file('master.csv','r')
f3= file('results.csv','w') 

c1=csv.reader(f1) 
c2=csv.reader(f2)
next(c2, None)
c3=csv.writer(f3)
#for loop compare row in host csv file 
master_list = list(c2) 
for row in c1: 
    row=1
    found = False
    colA = str(row[0])  #protocol
    colB = str(row[11])  
    colC = str(row[12])  
    colD = str(row[13]) 
    colE = str(row[14])  
    #loop in each row of master csv file
    for master_row in master_list:
        results_row=row
        colBf2 = str(master_row[4])  
        colCf2 = str(master_row[5])  
        colDf2 = str(master_row[6])  
        colEf2 = str(master_row[7])  
        colFf2 = str(master_row[3])
        #check condition
        if colA == 'icmp':
           #sub condiontion
           if colB == colBf2 and colD == colDf2:
              results_row.append(colFf2)
              found = True
              break
           row = row + 1
        else:
           if colB == colBf2 and colD == colDf2 and colE == colEf2:
              results_row.append(colFf2)
              found = True
              break
           row =row+1
   if not found:
      results_row.append('Not Match')
   c3.writerow(results_row)
f1.close()
f2.close()
f3.close()

Answer 1

昂贵的任务是内部循环，它为每个主机行重新扫描主表。由于python执行协作多线程（您可以搜索“python GIL”），因此一次只运行一个线程，因此多个线程不会加速cpu绑定操作。您可以生成子进程，但是您必须权衡将数据与工作进程相比的成本和速度增益。

或者，优化您的代码。而不是并行运行，而是索引主服务器。您可以交换昂贵的100000条记录扫描，以便快速查找字典。

我冒昧地将with子句添加到您的代码中以保存几行，并且还跳过了colA等等...（使用命名索引）来保持代码较小。

import csv

# columns of interest
A, B, C, D, E, F = 0, 11, 12, 13, 14, 3

# read and index column F in master by (B,D) and (B,D,E), discarding
# duplicates for those keys
col_index = {}
with open('master.csv') as master:
    next(master)
    for row in csv.reader(master):
        key = row[B], row[D]
        if key not in col_index:
            col_index[key] = row[F]
        key = row[B], row[D], row[E]
        if key not in col_index:
            col_index[key] = row[F]

#read csv files
with open('host.csv') as f1, open('results.csv','w') as f3: 
    c1=csv.reader(f1)
    c3=csv.writer(f3) 
    for row in c1:
        if row[A] == "icmp":
            indexer = (row[B], row[D])
        else:
            indexer = (row[B], row[D], row[E])
        row.append(col_index.get(indexer, 'Not Match'))
        c3.writerow(row)

python parallel比较2个csv文件

1 个答案: