How to scrape the web table with multiple pages using R or Python

Question

I want to scrape a web to gather the data for studying data mining. This web data contains a big table with 43 pages. And it also hide some stocks at the most right hand side of the expand menu.

The web page is below.

http://data.10jqka.com.cn/market/longhu/yyb/

import bs4
import requests


url = r"http://data.10jqka.com.cn/market/longhu/yyb/"

response = requests.get(url)
if response.status_code == 200:
    content = response.content

soup = bs4.BeautifulSoup(content)
table_results = soup.findAll("table", {"class": "m_table"})
for item in table_results:
    company_name = item.findAll("td", {"class": "tl"})[0].text.strip()
    detail = item.findAll("td", {"class": "tc"})[0].text.strip()
    c_rise = item.findAll("td", {"class": "c_rise"})[0].text.strip()
    c_fall = item.findAll("td", {"class": "c_fall"})[0].text.strip()
    cur = item.findAll("td", {"class": "cur"})[0].text.strip()
    lhb_stocklist = item.findAll("div", {"class": "lhb_stocklist"})[0].text.strip()
    print company_name, detail, c_rise, c_fall, lhb_stocklist

Answer 1

A solution based on requests, BeautifulSoup, and lxml:

import json
import requests
from bs4 import BeautifulSoup

URL = 'http://data.10jqka.com.cn/interface/market/longhuyyb/stocknum/desc/%d/20'
# config end_page as needed, or parse http://data.10jqka.com.cn/market/longhu/yyb/ to make it auto adapted
end_page = 2

result = []
for page_idx in range(1, end_page + 1):
    print 'Extracting page', page_idx
    raw_response = requests.get(URL % page_idx)
    page_content = json.loads(raw_response.text)['data']
    html = BeautifulSoup(page_content, 'lxml')
    for row in html.tbody.find_all('tr'):
        company = row.find(class_='tl').text
        detail_link = row.find(class_='tl').a['href']
        buy = float(row.find(class_='c_rise').text)
        sell = float(row.find(class_='c_fall').text)
        stock_cnt = int(row.find(class_='cur').text)
        stocks = []
        for a in row.find(class_='lhb_stocklist_box hide').p.find_all('a'):
            stocks.append((a.text, a['href']))
        result.append({
            'company': company,
            'detail_link': detail_link,
            'buy': buy,
            'sell': sell,
            'stock_cnt': stock_cnt,
            'stocks': stocks,
        })

print 'Company number:', len(result)

I put all data into a list of dictionaries, for easy accessing. You can modify the codes to directly write to a CSV or whatever