为什么我的简单 python web 爬虫运行很慢？

Question

I am trying to scrape about 34,000 pages. I calculated the time to find that it takes more than 5 seconds on average to request each page. Since I am directly scraping data from APIs, I only used the requests package. Is there any way that I could speed up my crawler? Or if it is not possible, how can I deploy the crawler to a server?

Here's some of my code:

# Using python selenium to scrape sellers on shopee.co.id
# Crawl one seller -> Crawl all sellers in the list
# Sample URL: https://shopee.co.id/shop/38281755/search
# Sample API: https://shopee.co.id/api/v2/shop/get?shopid=38281755
import pandas as pd
import requests
import json
from datetime import datetime
import time

PATH_1 = '/Users/lixiangyi/FirstIntern/temp/seller_list.csv'
shop_list = pd.read_csv(PATH_1)
shop_ids = shop_list['shop'].tolist()
# print(seller_list)

# Downloading all APIs of shopee sellers:
api_links = []  # APIs of shops
item_links = []  # Links to click into
for shop_id in shop_ids:
    api_links.append('https://shopee.co.id/api/v2/shop/get?shopid=' + str(shop_id))
    item_links.append(
        f'https://shopee.co.id/api/v2/search_items/?by=pop&limit=10&match_id={shop_id}&newest=0&order=desc&page_type=shop&version=2'
    )
# print(api_links)


shop_names = []
shopid_list = []
founded_time = []
descriptions = []
i = 1

for api_link in api_links[0:100]:
    start_time = time.time()
    shop_info = requests.get(api_link)
    shopid_list.append(shop_info.text)
    print(i)
    i += 1
    end_time = time.time()
    print(end_time - start_time)

Answer 1

You should be trying to retrieve multiple URLs in parallel using either threading or the aiohttp package. Using threading:

Update

Since all your requests are going against the same website, it will be more efficient to use a requests.Session object for making your retrievals. However, regardless of how you go about retrieving these URLs, issuing too many requests from the same IP address to the same website in a short period of time could be interpreted as a Denial of Service attack.

import requests
from concurrent.futures import ThreadPoolExecutor
from functools import partial
import time

api_links = [] # this will have been filled in
headers = {'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.105 Safari/537.36'}

shopid_list = []

def retrieve_url(session, url):
    shop_info = session.get(url)
    return shop_info.text


NUM_THREADS = 75 # experiment with this value
with ThreadPoolExecutor(max_workers=NUM_THREADS) as executor:
    with requests.Session() as session:
        session.headers = headers
        # session will be the first argument to retrieve_url:
        worker = partial(retrieve_url, session)
        start_time = time.time()
        for result in executor.map(worker, api_links):
            shopid_list.append(result)
        end_time = time.time()
        print(end_time - start_time)

Answer 2

use python urllib library

import urllib.request 
request_url = urllib.request.urlopen(some-url) 
print(request_url.read())