python实现爬取微博热搜存入Mysql

import requestsfrom selenium.webdriver import Chrome, ChromeOptionsimport timefrom sqlalchemy import create_engineimport pandas as pd

	all = browser.find_elements_by_xpath('//*[@id="pl_top_realtimehot"]/table/tbody/tr/td[2]/a')  #得到所有数据context = [i.text for i in c]  # 得到标题内容    links = [i.get_attribute('href') for i in c]  # 得到link

dc = zip(dates, context, links)    pdf = pd.DataFrame(dc, columns=['date', 'hotsearch', 'link'])

enging = create_engine("mysql+pymysql://root:123456@localhost:3306/webo?charset=utf8")pdf.to_sql(name='infromation', con=enging, if_exists="append")

from selenium.webdriver import Chrome, ChromeOptionsimport timefrom sqlalchemy import create_engineimport pandas as pddef get_data():    url = r"https://s.weibo.com/top/summary"  # 微博的地址    option = ChromeOptions()    option.add_argument('--headless')    option.add_argument("--no-sandbox")    browser = Chrome(options=option)    browser.get(url)    all = browser.find_elements_by_xpath('//*[@id="pl_top_realtimehot"]/table/tbody/tr/td[2]/a')    context = [i.text for i in all]    links = [i.get_attribute('href') for i in all]    date = time.strftime("%Y-%m-%d-%H_%M_%S", time.localtime())    dates = []    for i in range(len(context)):        dates.append(date)    # print(len(dates),len(context),dates,context)    dc = zip(dates, context, links)    pdf = pd.DataFrame(dc, columns=['date', 'hotsearch', 'link'])    # pdf.to_sql(name=in, con=enging, if_exists="append")    return pdfdef w_mysql(pdf):    try:        enging = create_engine("mysql+pymysql://root:123456@localhost:3306/webo?charset=utf8")        pdf.to_sql(name='infromation', con=enging, if_exists="append")    except:        print('出错了')if __name__ == '__main__':    xx = get_data()    w_mysql(xx)