熊猫和多

Question

我使用的是FCC的API经/纬坐标转换成块组代码：

import pandas as pd 
import numpy as np 
import urllib 
import time 
import json 

# getup, getup1, and getup2 make up the url to the api 
getup = 'http://data.fcc.gov/api/block/find?format=json&latitude=' 

getup1 = '&longitude=' 

getup2 = '&showall=false' 

lat = ['40.7127837','34.0522342','41.8781136','29.7604267','39.9525839', 
'33.4483771','29.4241219','32.715738','32.7766642','37.3382082','30.267153', 
'39.768403','30.3321838','37.7749295','39.9611755','35.2270869', 
'32.7554883','42.331427','31.7775757','35.1495343'] 

long = ['-74.0059413','-118.2436849','-87.6297982','-95.3698028','-75.1652215', 
'-112.0740373','-98.4936282','-117.1610838','-96.7969879','-121.8863286', 
'-97.7430608','-86.158068','-81.655651','-122.4194155','-82.9987942', 
'-80.8431267','-97.3307658','-83.0457538','-106.4424559','-90.0489801'] 

#make lat and long in to a Pandas DataFrame 
latlong = pd.DataFrame([lat,long]).transpose() 
latlong.columns = ['lat','long'] 

new_list = [] 

def block(x): 
    for index,row in x.iterrows(): 
     #request url and read the output 
     a = urllib.request.urlopen(getup + row['lat'] + getup1 + row['long'] + getup2).read() 
     #load json output in to a form python can understand 
     a1 = json.loads(a) 
     #append output to an empty list. 
     new_list.append(a1['Block']['FIPS']) 

#call the function with latlong as the argument.   
block(latlong) 

#print the list, note: it is important that function appends to the list 
print(new_list) 

给出了这样的输出：

['360610031001021', '060372074001033', '170318391001104', '482011000003087', 
'421010005001010', '040131141001032', '480291101002041', '060730053003011', 
'481130204003064', '060855010004004', '484530011001092', '180973910003057', 
'120310010001023', '060750201001001', '390490040001005', '371190001005000', 
'484391233002071', '261635172001069', '481410029001001', '471570042001018'] 

与该脚本的问题是，我可以每行只调用一次api。脚本运行需要花费大约5分钟的时间，这对于我计划使用此脚本的1,000,000个条目来说是不可接受的。

我想用多处理来并行这个函数来减少运行函数的时间。我试图查看多处理手册，但一直未能弄清楚如何运行该函数并将输出追加到并行的空列表中。

仅供参考：我正在使用python 3.6

任何指导都会很棒！

Answer 1

您不必自己实现并行性，有比urllib更好的库，例如，请求[0]和一些使用线程或期货的分拆[1]。我想你需要检查自己哪个是最快的。

由于依赖性很少，我喜欢request-futures最好的，在这里我使用十个线程来实现您的代码。图书馆甚至支持过程如果您认为或弄清楚，它是在你的情况下，莫名其妙地更好：

import pandas as pd 
import numpy as np 
import urllib 
import time 
import json 
from concurrent.futures import ThreadPoolExecutor 

from requests_futures.sessions import FuturesSession 

#getup, getup1, and getup2 make up the url to the api 
getup = 'http://data.fcc.gov/api/block/find?format=json&latitude=' 

getup1 = '&longitude=' 

getup2 = '&showall=false' 

lat = ['40.7127837','34.0522342','41.8781136','29.7604267','39.9525839', 
'33.4483771','29.4241219','32.715738','32.7766642','37.3382082','30.267153', 
'39.768403','30.3321838','37.7749295','39.9611755','35.2270869', 
'32.7554883','42.331427','31.7775757','35.1495343'] 

long = ['-74.0059413','-118.2436849','-87.6297982','-95.3698028','-75.1652215', 
'-112.0740373','-98.4936282','-117.1610838','-96.7969879','-121.8863286', 
'-97.7430608','-86.158068','-81.655651','-122.4194155','-82.9987942', 
'-80.8431267','-97.3307658','-83.0457538','-106.4424559','-90.0489801'] 

#make lat and long in to a Pandas DataFrame 
latlong = pd.DataFrame([lat,long]).transpose() 
latlong.columns = ['lat','long'] 

def block(x): 
    requests = [] 
    session = FuturesSession(executor=ThreadPoolExecutor(max_workers=10)) 
    for index, row in x.iterrows(): 
     #request url and read the output 
     url = getup+row['lat']+getup1+row['long']+getup2   
     requests.append(session.get(url)) 
    new_list = [] 
    for request in requests: 
     #load json output in to a form python can understand 
     a1 = json.loads(request.result().content) 
     #append output to an empty list. 
     new_list.append(a1['Block']['FIPS']) 
    return new_list 

#call the function with latlong as the argument.   
new_list = block(latlong) 

#print the list, note: it is important that function appends to the list 
print(new_list) 

[0] http://docs.python-requests.org/en/master/

[1] https://github.com/kennethreitz/grequests