CODEWITHSUNDEEP
pythonimportmultiprocessingpool
user2653711
user2653711

Reputation: 27

in Python, how to implement (multiprocessing pool)

in this part of scraping code , I fetch alot of URLs from stored URLs in (url.xml) file and it is take so long to finish, how to implement (multiprocessing pool)

any simple code to fix this problem ? Thanks

from bs4 import BeautifulSoup as soup
import requests
from multiprocessing import Pool

p = Pool(10) # “10” means that 10 URLs will be processed at the same time
p.map

page_url = "url.xml"


out_filename = "prices.csv"
headers = "availableOffers,otherpricess,currentprice \n"

with open(out_filename, "w") as fw:
  fw.write(headers)
  with open("url.xml", "r") as fr:
    for url in map(lambda x: x.strip(), fr.readlines()): 
      print(url)
      response = requests.get(url)
      page_soup = soup(response.text, "html.parser")


      availableOffers = page_soup.find("input", {"id": "availableOffers"})
      otherpricess = page_soup.find("span", {"class": "price"})
      currentprice = page_soup.find("div", {"class": "is"})

      fw.write(availableOffers + ", " + otherpricess + ", " + currentprice + "\n")


p.terminate()
p.join()

Upvotes: 0

Views: 372

Answers (2)

Saurabh Kansal
Saurabh Kansal

Reputation: 702

You can use concurrent.futures standard package in python for multiprocessing and multi-threading.

In, your case, you don't need multiprocessing, multi-threading will help. Because, your function in computationally expensive.

By, use of multi-threading, you can send multiple request at same time. number_of_threads argument can control the number of the request, you want to send at a time.

I have created a function, extract_data_from_url_func that will extract the data from single URL and i pass this function and list of URLS to multi-threading executor using concurrent.futures.

from bs4 import BeautifulSoup as soup
from concurrent.futures import ThreadPoolExecutor
import requests

page_url = "url.xml"
number_of_threads = 6
out_filename = "prices.csv"
headers = "availableOffers,otherpricess,currentprice \n"

def extract_data_from_url_func(url):
    print(url)
    response = requests.get(url)
    page_soup = soup(response.text, "html.parser")
    availableOffers = page_soup.find("input", {"id": "availableOffers"})["value"]
    otherpricess = page_soup.find("span", {"class": "price"}).text.replace("$", "")
    currentprice = page_soup.find("div", {"class": "is"}).text.strip().replace("$", "")
    output_list = [availableOffers, otherpricess, currentprice]
    output = ",".join(output_list)
    print(output)
    return output

with open("url.xml", "r") as fr:
    URLS = list(map(lambda x: x.strip(), fr.readlines()))

with ThreadPoolExecutor(max_workers=number_of_threads) as executor:
    results = executor.map( extract_data_from_url_func, URLS)
    responses = []
    for result in results:
        responses.append(result)


with open(out_filename, "w") as fw:
  fw.write(headers)
  for response in responses:
      fw.write(response)

reference: https://docs.python.org/3/library/concurrent.futures.html

Upvotes: 1

Luv
Luv

Reputation: 496

It must be something of this form. Please make changes so that urls being passed to p.map is a list of urls:

from bs4 import BeautifulSoup as soup
import requests
from multiprocessing import Pool
import csv

def parse(url):
    response = requests.get(url)
    page_soup = soup(response.text, "html.parser")
    availableOffers = page_soup.find("input", {"id": "availableOffers"})["value"]
    otherpricess = page_soup.find("span", {"class": "price"}).text.replace("$", "")
    currentprice = page_soup.find("div", {"class": "is"}).text.strip().replace("$", "")
    return availableOffers, otherpricess, currentprice


if __name__ == '__main__':
    urls = [ ... ]  # List of urls to fetch from
    p = Pool(10) # “10” means that 10 URLs will be processed at the same time
    records = p.map(parse, urls)
    p.terminate()
    p.join()
    with open("outfile.csv", "w") as csvfile:
        writer = csv.writer(csvfile, delimiter=',', quoting=csv.QUOTE_MINIMAL)
        for r in records:
             writer.writerow(r)

Upvotes: 0

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