AttributeError的：模块“并发”有没有属性“期货”，当我在Python 3.6尝试并行处理

Question

我试图分裂一个过程，需要很长的时间来使用concurrent.futures模块多个进程。附件是以下代码

主功能：

with concurrent.futures.ProcessPoolExecutor() as executor:
for idx, score in zip([idx for idx in range(dataframe.shape[0])],executor.map(get_max_fuzzy_score,[dataframe[idx:idx+1] for idx in range(dataframe.shape[0])])):
    print('processing '+str(idx+1)+' of '+str(dataframe.shape[0]+1))
    dataframe['max_row_score'].iloc[idx] = score

get_max_fuzzy_score功能：

def get_max_fuzzy_score(picklepath_or_list, df):
import numpy as np
extracted_text_columns = list(df.filter(regex='extracted_text').columns)
data_list = [df[data].iloc[0] for data in extracted_text_columns if not df[data].isnull().values.any()]
try:
    size = len(picklepath_or_list)
    section_snippet_list = picklepath_or_list
except:
    section_snippet_list = pickle.load(open(picklepath_or_list,'rb'))
scores = []
for section_snippet in section_snippet_list:
    for data in data_list:
        scores.append(fuzz.partial_ratio(data,section_snippet))
score = max(scores)

return score

该功能需要几列的值，并且从先前建立返回列表中的最大比分模糊。

这是我得到的错误：

Traceback (most recent call last):
  File "multiprocessing.py", line 8, in <module>
    import concurrent.futures
  File "/home/naveen/anaconda3/lib/python3.6/concurrent/futures/__init__.py", line 17, in <module>
    from concurrent.futures.process import ProcessPoolExecutor
  File "/home/naveen/anaconda3/lib/python3.6/concurrent/futures/process.py", line 53, in <module>
    import multiprocessing
  File "/home/naveen/Documents/pramata-ie/data-science/scripts/multiprocessing.py", line 79, in <module>
    with concurrent.futures.ProcessPoolExecutor() as executor:
AttributeError: module 'concurrent' has no attribute 'futures'

任何有关相同的帮助将是巨大的。谢谢

Answer 1

你可以导入这样说：

import concurrent.futures

而使用这种方式：

executor = concurrent.futures.ThreadPoolExecutor(max_workers=num_workers)。

---

您还可以导入的ThreadPoolExecutor是这样的：

from concurrent.futures.thread import ThreadPoolExecutor

而使用这种方式：

executor = ThreadPoolExecutor(max_workers=num_workers)。