python 多进程处理实验数据 runtimerror

在预备国赛 处理大量的数据 打算用multiprocessing
题目为 2017B 处理两个excel保存的数据信息

代码

```python
import pandas as pd
import xlrd as xl
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import time
import multiprocessing as mp
import math

def final_fun(name,param):
    global loc1
    global loc2
    global col1
    global col2
    result = np.zeros(len(param))
    distance = 0.001
    k = 1
    for i in param:
        count = 0
        if k == 1:
            start = time.time()
        for j in range(len(col1)):
            if (loc1[i]-col1[j])**2 + (loc2[i]-col2[j])**2 <= distance ** 2:
                count += 1
        result[param.index(i)] = count
        if k == 1:
            end = time.time()
            print((end-start)*len(param))
            k =10
    return restlt

dataframe = pd.read_excel("附件三：新项目任务数据.xls","t_tasklaunch",header=0)
col1 = dataframe["任务GPS纬度"][:10]
col2 = dataframe["任务GPS经度"][:10]
dataframe = pd.read_excel("附件二：会员信息数据.xlsx","Sheet1",header=0)
loc = dataframe["会员位置(GPS)"]
loc = [i.split(" ") for i in loc]
loc1 = [float(i[0]) for i in loc][:10]
loc2 = [float(i[1]) for i in loc][:10]

#plt.scatter(loc1,loc2,s=5)
#plt.scatter(col1,col2,s=5,c="red")
#plt.show()

len_loc = len(loc)
n_len_loc = math.floor(len_loc/16)

num_cores = int(mp.cpu_count())
pool = mp.Pool(num_cores)
param_dict = {"task"+str(i):[j for j in range(i*n_len_loc,(i+1)*n_len_loc)] for i in range(15)}
param_dict["taks15"] = [j for j in range(15*n_len_loc,len_loc-15 * n_len_loc)]
results = [pool.apply_async(final_fun,args=(name,param)) for name,param in param_dict.items()]
results = [p.get() for p in results]
f = open("information.txt","w")
f.writelines(results)
f.close()

报错：

![img](https://img-mid.csdnimg.cn/release/static/image/mid/ask/90432161306615.png "#left")

在windows中运行 加上:
if __name__ == '__main__':作为程序运行的入口

pool.close()
和
pool.join()
一定要加，
不加的话会因为进程池里的子进程还没工作完，父进程就结束了

num_cores = int(mp.cpu_count())
pool = mp.Pool(num_cores)
param_dict = {"task"+str(i):[j for j in range(i*n_len_loc,(i+1)*n_len_loc)] for i in range(15)}
param_dict["taks15"] = [j for j in range(15*n_len_loc,len_loc-15 * n_len_loc)]
results = [pool.apply_async(final_fun,args=(name,param)) for name,param in param_dict.items()]
results = [p.get() for p in results]
pool.close()
pool.join()
f = open("information.txt","w")
f.writelines(results)
f.close()