如何用python爬取微博热搜数据并保存_Python

如何用python爬取微博热搜数据并保存

2021-09-07 00:19ZileLee Python

这篇文章主要介绍了如何用python爬取微博热搜数据并保存,本文给大家介绍的非常详细，对大家的学习或工作具有一定的参考借鉴价值，需要的朋友可以参考下

主要用到requests和bf4两个库
将获得的信息保存在d://hotsearch.txt下

				?

									import requests;

									import bs4

									mylist=[]

									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_encoding

									demo = r.text

									from bs4 import beautifulsoup

									soup = 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]))

如何用python爬取微博热搜数据并保存

知识点扩展：利用python爬取微博热搜并进行数据分析

爬取微博热搜

				?

									import schedule

									import pandas as pd

									from datetime import datetime

									import requests

									from bs4 import beautifulsoup

									url = "https://s.weibo.com/top/summary?cate=realtimehot&sudaref=s.weibo.com&display=0&retcode=6102"

									get_info_dict = {}

									count = 0

									def 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()

pyecharts数据分析

				?

									import pandas as pd

									from pyecharts import options as opts

									from pyecharts.charts import bar, timeline, grid

									from pyecharts.globals import themetype, currentconfig

									df = 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')