使用指南
- 本代码用于爬取
巴伦周刊
新闻网站首页的新闻文章(包括新闻标题,新闻链接,和发布日期三个数据)
- 在
Python3
环境下运行本代码,同时保证运行环境中安装有 requests
,pandas
库。
- 运行结果保存为
"巴伦周刊.csv"
文件,路径位于脚本同路径下(如有需要可以修改代码中 filename
的值,设置文件名和存储路径)
- 使用此爬虫前,请确保您的网络可以正常访问 巴伦周刊 网站,否则爬虫运行会报错失败。
- 本爬虫仅供学习交流使用,请勿用于商业用途。
源码
import requests
import json
from bs4 import BeautifulSoup
import pandas as pd
import time
def fetchUrl(url):
header = {
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/85.0.4183.102 Safari/537.36',
}
r = requests.get(url, headers = header)
r.encoding = r.apparent_encoding
return r.text
def parseHtml(html):
bsObj = BeautifulSoup(html, "lxml")
scripts = bsObj.find_all("script")[29]
content = scripts.text.lstrip().rstrip().replace("window.__STATE__ = ", "").split(";")[0]
retData = []
jsObj = json.loads(content)
headlines = jsObj['data']
for item in headlines:
if "article" in item:
dataObj = headlines[item]['data']['data']
timestamp = dataObj['timestamp'] / 1000
date = time.strftime("%Y-%m-%d", time.localtime(timestamp))
link = dataObj['url']
title = dataObj['headline']
print(date, title, link)
retData.append([date, title, link])
return retData
def saveData(data, filename):
dataframe = pd.DataFrame(data)
dataframe.to_csv(filename, mode='a', index=False, sep=',', header=False)
if __name__ == "__main__":
url = "https://www.barrons.com/"
html = fetchUrl(url)
data = parseHtml(html)
saveData(data, "巴伦周刊.csv")