本篇文章为大家展示了使用python怎么爬取谷歌趋势数据，内容简明扼要并且容易理解，绝对能使你眼前一亮，通过这篇文章的详细介绍希望你能有所收获。
python有哪些常用库
python常用的库：1.requesuts；2.scrapy；3.pillow；4.twisted；5.numpy；6.matplotlib；7.pygama；8.ipyhton等。
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 socketimport socksimport requestsimport jsonimport pandas as pdimport 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DataFrametime_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-CN&tz=-480&req={{"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-CN&tz=-480&req={}&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-CN&tz=-480&req={}&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-CN&tz=-480&req={}&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 contentdef 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()上述内容就是使用python怎么爬取谷歌趋势数据，你们学到知识或技能了吗？如果还想学到更多技能或者丰富自己的知识储备，欢迎关注编程网行业资讯频道。
