自学教程：如何用python爬取微博热搜数据并保存

import requests;import bs4mylist=[]r = requests.get(url='https://s.weibo.com/top/summary?Refer=top_hot&topnav=1&wvr=6',timeout=10)print(r.status_code) # 获取返回状态r.encoding=r.apparent_encodingdemo = r.textfrom bs4 import BeautifulSoupsoup = BeautifulSoup(demo,"html.parser")for link in soup.find('tbody') : hotnumber='' if isinstance(link,bs4.element.Tag):#  print(link('td'))  lis=link('td')  hotrank=lis[1]('a')[0].string#热搜排名  hotname=lis[1].find('span')#热搜名称  if isinstance(hotname,bs4.element.Tag):   hotnumber=hotname.string#热搜指数   pass  mylist.append([lis[0].string,hotrank,hotnumber,lis[2].string])f=open("d://hotsearch.txt","w+")for line in mylist: f.write('%s %s %s %s/n'%(line[0],line[1],line[2],line[3]))

import scheduleimport pandas as pdfrom datetime import datetimeimport requestsfrom bs4 import BeautifulSoupurl = "https://s.weibo.com/top/summary?cate=realtimehot&sudaref=s.weibo.com&display=0&retcode=6102"get_info_dict = {}count = 0def main():  global url, get_info_dict, count  get_info_list = []  print("正在爬取数据~~~")  html = requests.get(url).text  soup = BeautifulSoup(html, 'lxml')  for tr in soup.find_all(name='tr', class_=''):    get_info = get_info_dict.copy()    get_info['title'] = tr.find(class_='td-02').find(name='a').text    try:      get_info['num'] = eval(tr.find(class_='td-02').find(name='span').text)    except AttributeError:      get_info['num'] = None    get_info['time'] = datetime.now().strftime("%Y/%m/%d %H:%M")    get_info_list.append(get_info)  get_info_list = get_info_list[1:16]  df = pd.DataFrame(get_info_list)  if count == 0:    df.to_csv('datas.csv', mode='a+', index=False, encoding='gbk')    count += 1  else:    df.to_csv('datas.csv', mode='a+', index=False, header=False, encoding='gbk')# 定时爬虫schedule.every(1).minutes.do(main)while True:  schedule.run_pending()

import pandas as pdfrom pyecharts import options as optsfrom pyecharts.charts import Bar, Timeline, Gridfrom pyecharts.globals import ThemeType, CurrentConfigdf = pd.read_csv('datas.csv', encoding='gbk')print(df)t = Timeline(init_opts=opts.InitOpts(theme=ThemeType.MACARONS)) # 定制主题for i in range(int(df.shape[0]/15)):  bar = (    Bar()      .add_xaxis(list(df['title'][i*15: i*15+15][::-1])) # x轴数据      .add_yaxis('num', list(df['num'][i*15: i*15+15][::-1])) # y轴数据      .reversal_axis() # 翻转      .set_global_opts( # 全局配置项      title_opts=opts.TitleOpts( # 标题配置项        title=f"{list(df['time'])[i * 15]}",        pos_right="5%", pos_bottom="15%",        title_textstyle_opts=opts.TextStyleOpts(          font_family='KaiTi', font_size=24, color='#FF1493'        )      ),      xaxis_opts=opts.AxisOpts( # x轴配置项        splitline_opts=opts.SplitLineOpts(is_show=True),      ),      yaxis_opts=opts.AxisOpts( # y轴配置项        splitline_opts=opts.SplitLineOpts(is_show=True),        axislabel_opts=opts.LabelOpts(color='#DC143C')      )    )      .set_series_opts( # 系列配置项      label_opts=opts.LabelOpts( # 标签配置        position="right", color='#9400D3')    )  )  grid = (    Grid()      .add(bar, grid_opts=opts.GridOpts(pos_left="24%"))  )  t.add(grid, "")  t.add_schema(    play_interval=1000, # 轮播速度    is_timeline_show=False, # 是否显示 timeline 组件    is_auto_play=True, # 是否自动播放  )t.render('时间轮播图.html')