python - python中的并行执行失败？

Question

我有如下代码：

import pandas as pd
import multiprocessing as mp

a = {'a' : [1,2,3,1,2,3], 'b' : [5,6,7,4,6,5], 'c' : ['dog', 'cat', 'tree','slow','fast','hurry']}
df = pd.DataFrame(a)

def performDBSCAN(feature): 
    value=scorecalculate(feature)
    print(value)
    for ele in range(4):
        value=value+1
        print('here value is ', value)
    return value

def processing(feature):
    result1=performDBSCAN(feature)
    return result1

def scorecalculate(feature):
    scorecal=0
    for val in ['a','b','c','d']:
        print('alpha is:', val )
        scorecal=scorecal+1
    return scorecal

columns = df.columns
for ele in df.columns:
    processing(ele)

上面的代码是以串行方式执行的。我想通过在 python 中使用多处理来提高速度并编写了以下代码。

import pandas as pd
import multiprocessing as mp     

def performDBSCAN(feature): 
    value=scorecalculate(feature)
    print(value)
    for ele in range(4):
        value=value+1
        print('here value is ', value)
    return value

def scorecalculate(feature):
    scorecal=0
    for val in ['a','b','c','d']:
        print('alpha is:', val )
        scorecal=scorecal+1
    return scorecal

def processing(feature):
    result1=performDBSCAN(feature)
    return result1

a = {'a' : [1,2,3,1,2,3], 'b' : [5,6,7,4,6,5], 
'c' : ['dog','cat','tree','slow','fast','hurry']}
df = pd.DataFrame(a)
columns = df.columns
pool = mp.Pool(4)
resultpool = pool.map(processing, columns)

我想查看输出但内核一直在运行而没有任何输出？可能是什么问题？

标签： pythonpython-3.xpandasmultiprocessing