主页 > 知识库 > python爬虫之爬取谷歌趋势数据

python爬虫之爬取谷歌趋势数据

热门标签:企业做大做强 呼叫中心市场需求 电话运营中心 硅谷的囚徒呼叫中心 客户服务 百度AI接口 Win7旗舰版 语音系统

一、前言 

爬取谷歌趋势数据需要科学上网~

二、思路

谷歌数据的爬取很简单,就是代码有点长。主要分下面几个就行了

爬取的三个界面返回的都是json数据。主要获取对应的token值和req,然后构造url请求数据就行

token值和req值都在这个链接的返回数据里。解析后得到token和req就行

socks5代理不太懂,抄网上的作业,假如了当前程序的全局代理后就可以跑了。全部代码如下

import socket
import socks
import requests
import json
import pandas as pd
import logging

#加入socks5代理后,可以获得当前程序的全局代理
socks.set_default_proxy(socks.SOCKS5,"127.0.0.1",1080)
socket.socket = socks.socksocket

#加入以下代码,否则会出现InsecureRequestWarning警告,虽然不影响使用,但看着糟心
# 捕捉警告
logging.captureWarnings(True)
# 或者加入以下代码,忽略requests证书警告
# from requests.packages.urllib3.exceptions import InsecureRequestWarning
# requests.packages.urllib3.disable_warnings(InsecureRequestWarning)

# 将三个页面获得的数据存为DataFrame
time_trends = pd.DataFrame()
related_topic = pd.DataFrame()
related_search = pd.DataFrame()

#填入自己打开网页的请求头
headers = {
    'user-agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.114 Safari/537.36',
    'x-client-data': 'CJa2yQEIorbJAQjEtskBCKmdygEI+MfKAQjM3soBCLKaywEI45zLAQioncsBGOGaywE=Decoded:message ClientVariations {// Active client experiment variation IDs.repeated int32 variation_id = [3300118, 3300130, 3300164, 3313321, 3318776, 3321676, 3329330, 3329635, 3329704];// Active client experiment variation IDs that trigger server-side behavior.repeated int32 trigger_variation_id = [3329377];}',
    'referer': 'https://trends.google.com/trends/explore',
    'cookie': '__utmc=10102256; __utmz=10102256.1617948191.1.1.utmcsr=(direct)|utmccn=(direct)|utmcmd=(none); __utma=10102256.889828344.1617948191.1617948191.1617956555.3; __utmt=1; __utmb=10102256.5.9.1617956603932; SID=8AfEx31goq255ga6Ldt9ljEVZ5xQ7fYTAdzCK3DgEYp2s6MOxeKc__hQ90tTtn0W-6AVoQ.; __Secure-3PSID=8AfEx31goq255ga6Ldt9ljEVZ5xQ7fYTAdzCK3DgEYp2s6MOLU4HYHzyoAXIvtAhfF_WNg.; HSID=AELT1m_DoHJY-r6SW; SSID=AJSlRt0T7ngXXMtqv; APISID=3Nt6oALGV8kSym2M/A2QeNBMtb9P7VcIwV; SAPISID=iAA0fu76JZezPfK4/Apws7zK1y-o74b2YD; __Secure-3PAPISID=iAA0fu76JZezPfK4/Apws7zK1y-o74b2YD; 1P_JAR=2021-04-06-06; SEARCH_SAMESITE=CgQIo5IB; NID=213=oYQE35gIVD2DrxbpY7NdAQsAEyg-If7Jh_nBdSKTkvmtgaVV7tYeSQNq_636cysbsajJP3_dKfr95w51ywK-dxVYhzPP4Zll9JndBYY98vd_XegGoeLEevpxIhNxUAv6H24OVt_edoGFkSjTpWKn4QAoIoerHCViyvozrvGF7m4scupppmxN-h9dwm1nrs15I3b_E-ifLq0lgd9s7QrgA-FRuaDeyuXN8t1K7l_DMTB1jkE5ED_dC-_QAO7DDw; SIDCC=AJi4QfFdMiK_qV41ViVJf0wWmtOu8yUVSQc_UEvemoaQwTGI9W0w2XwwkMCufVcYIS5ogRSkq5w; __Secure-3PSIDCC=AJi4QfEmB-gnzZLHWR4p1EmOfS2dhSz9zWSGNGOozrY2udFk4KwVmVo_srZdZrmdy7h_mwLSwQ'
}


# 获取需要的三个界面的req值和token值
def get_token_req(keyword):
    url = 'https://trends.google.com/trends/api/explore?hl=zh-CNtz=-480req={{"comparisonItem":[{{"keyword":"{}","geo":"US","time":"today 12-m"}}],"category":0,"property":""}}tz=-480'.format(
        keyword)
    html = requests.get(url, headers=headers, verify=False).text
    data = json.loads(html[5:])

    req_1 = data['widgets'][0]['request']
    token_1 = data['widgets'][0]['token']

    req_2 = data['widgets'][2]['request']
    token_2 = data['widgets'][2]['token']

    req_3 = data['widgets'][3]['request']
    token_3 = data['widgets'][3]['token']

    result = {'req_1': req_1, 'token_1': token_1, 'req_2': req_2, 'token_2': token_2, 'req_3': req_3,
              'token_3': token_3}
    return result


# 请求三个界面的数据,返回的是json数据,所以数据不用解析,完美
def get_info(keyword):
    content = []
    keyword = keyword
    result = get_token_req(keyword)

    #第一个界面
    req_1 = result['req_1']
    token_1 = result['token_1']
    url_1 = "https://trends.google.com/trends/api/widgetdata/multiline?hl=zh-CNtz=-480req={}token={}tz=-480".format(
        req_1, token_1)
    r_1 = requests.get(url_1, headers=headers, verify=False)
    if r_1.status_code == 200:
        try:
            content_1 = r_1.content
            content_1 = json.loads(content_1.decode('unicode_escape')[6:])['default']['timelineData']
            result_1 = pd.json_normalize(content_1)
            result_1['value'] = result_1['value'].map(lambda x: x[0])
            result_1['keyword'] = keyword
        except Exception as e:
            print(e)
            result_1 = None
    else:
        print(r_1.status_code)

    #第二个界面
    req_2 = result['req_2']
    token_2 = result['token_2']
    url_2 = 'https://trends.google.com/trends/api/widgetdata/relatedsearches?hl=zh-CNtz=-480req={}token={}'.format(
        req_2, token_2)
    r_2 = requests.get(url_2, headers=headers, verify=False)
    if r_2.status_code == 200:
        try:
            content_2 = r_2.content
            content_2 = json.loads(content_2.decode('unicode_escape')[6:])['default']['rankedList'][1]['rankedKeyword']
            result_2 = pd.json_normalize(content_2)
            result_2['link'] = "https://trends.google.com" + result_2['link']
            result_2['keyword'] = keyword
        except Exception as e:
            print(e)
            result_2 = None
    else:
        print(r_2.status_code)

    #第三个界面
    req_3 = result['req_3']
    token_3 = result['token_3']
    url_3 = 'https://trends.google.com/trends/api/widgetdata/relatedsearches?hl=zh-CNtz=-480req={}token={}'.format(
        req_3, token_3)
    r_3 = requests.get(url_3, headers=headers, verify=False)
    if r_3.status_code == 200:
        try:
            content_3 = r_3.content
            content_3 = json.loads(content_3.decode('unicode_escape')[6:])['default']['rankedList'][1]['rankedKeyword']
            result_3 = pd.json_normalize(content_3)
            result_3['link'] = "https://trends.google.com" + result_3['link']
            result_3['keyword'] = keyword
        except Exception as e:
            print(e)
            result_3 = None
    else:
        print(r_3.status_code)

    content = [result_1, result_2, result_3]

    return content

def main():
    global time_trends,related_search,related_topic
    with open(r'C:\Users\Desktop\words.txt','r',encoding = 'utf-8') as f:
        words = f.readlines()
    for keyword in words:
        keyword = keyword.strip()
        data_all = get_info(keyword)
        time_trends = pd.concat([time_trends,data_all[0]],sort = False)
        related_topic = pd.concat([related_topic,data_all[1]],sort = False)
        related_search = pd.concat([related_search,data_all[2]],sort = False)

if __name__ == "__main__":
    main()

到此这篇关于python爬虫之爬取谷歌趋势数据的文章就介绍到这了,更多相关python爬取谷歌趋势内容请搜索脚本之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持脚本之家!

您可能感兴趣的文章:
  • 教你如何使用Python快速爬取需要的数据
  • python爬取豆瓣电影TOP250数据
  • python爬取链家二手房的数据
  • Python手拉手教你爬取贝壳房源数据的实战教程
  • Python数据分析之Python和Selenium爬取BOSS直聘岗位
  • python selenium实现智联招聘数据爬取
  • python爬虫之教你如何爬取地理数据
  • Python爬虫爬取全球疫情数据并存储到mysql数据库的步骤
  • Python爬取腾讯疫情实时数据并存储到mysql数据库的示例代码
  • Python爬虫之自动爬取某车之家各车销售数据

标签:安康 山西 崇左 济南 山西 海南 喀什 长沙

巨人网络通讯声明:本文标题《python爬虫之爬取谷歌趋势数据》,本文关键词  ;如发现本文内容存在版权问题,烦请提供相关信息告之我们,我们将及时沟通与处理。本站内容系统采集于网络,涉及言论、版权与本站无关。
  • 相关文章
  • 收缩
    • 微信客服
    • 微信二维码
    • 电话咨询

    • 400-1100-266