谷歌学术按人名搜索批量采集论文数据

2022年10月28日 22:58 ry 84

今天接到任务,给我几个人名采集他们在谷歌学术上自己的论文数据,字段包括论文标题,作者,引用数,期刊会议,发表时间等,话不多说,直接用代码实现,进入谷歌学术官网(需要翻墙实现),找到人名搜索框,如图所示

 

 

如图所示搜索框,改页面已包含全部所需数据,话不多说,直接上代码

import requests
from lxml import etree
import re
import pandas as pd
headers = {
    'cookie': 'SID=PAhWmAWWikPJThzwR_jS546ISU2OAHRgtF1eqr3bQUDrDXZ4Vdo1GuEy0BKjK5RMhQS1qA.; __Secure-1PSID=PAhWmAWWikPJThzwR_jS546ISU2OAHRgtF1eqr3bQUDrDXZ4zV3PeW3Yz3khOurIC6nUjQ.; __Secure-3PSID=PAhWmAWWikPJThzwR_jS546ISU2OAHRgtF1eqr3bQUDrDXZ4Eid3rdD8Ai8Y--DYmHd2hQ.; HSID=AetAl0I0TdVuXmlVZ; SSID=A8W392Q1DtZiazS8t; APISID=FdZiBbZcgOXiV2oN/AfDGCpf4dEr_kj1K1; SAPISID=ildLYr2jtyApljoJ/AWHimn7B7G7CFZqY8; __Secure-1PAPISID=ildLYr2jtyApljoJ/AWHimn7B7G7CFZqY8; __Secure-3PAPISID=ildLYr2jtyApljoJ/AWHimn7B7G7CFZqY8; GSP=LM=1665983795:S=SL7wTz1dWfrquo4e; AEC=AakniGMVK4oL-uh9oIT07sltVkUJO6UjGyN8wLdgxGwUVfMgeb56M4nFiWM; NID=511=vLSYLrwXqWM9a5DpVG9o0Jk0LfRUecL3btSKDKjz0WGx8ZqAZeZJShDRDJwXZt_dL7_R5a8VlYKnnLLBH-uzPXUgISKmpr-9FqTuofqecUu1oaPMwfnhZHuz2KM5QRSs40w8RLnBypyLN6YyOXt2CIm5w86EbTL7WxfC5NrcHBLQiRyfb6iuT3ojUvTY_oETy9ZAFUfXpbCf0K4Q2LqcrW201V5o3WpI02PuvmJm-Wb1RAnbex0OaIQ0X26TpNrnl6rtCJebTpmE; SEARCH_SAMESITE=CgQI3ZYB; GOOGLE_ABUSE_EXEMPTION=ID=170e9c4c5037e2c5:TM=1666936190:C=>:IP=154.53.61.129-:S=hS92BPLMiJ7sm5vAJL6O3Q; 1P_JAR=2022-10-28-05; SIDCC=AIKkIs0OTfgMnAs-R5ovnaapRNsBn0Z0gTCe4hhWlK3hIOTA1kq6aSOP0nO09GxmOVzg5K3htEE; __Secure-1PSIDCC=AIKkIs2OObSKjFOvQ6sKIAQ_jmm_MAwiqaakua63Bmg91Af45lxZIZeXjfPnGo2mcEBXDPvzdw; __Secure-3PSIDCC=AIKkIs2eEPMxtvaZRt5CfdxM-0MCMTO5yXKnAQY5Y8HF2voo9856exF4PsTVgaRPllRNUeyDRA',
    'user-agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.114 Safari/537.36',
}
proxies = {
    'http':'127.0.0.1:10809',
    'https':'127.0.0.1:10809'
}
real_user_id = []
ids = []
def get_id():

    api = 'https://scholar.google.com/citations?view_op=search_authors&hl=en&mauthors=Haixia+Wang&btnG='
    r = requests.get(api, proxies=proxies, headers=headers)
    html = etree.HTML(r.text)
    users_links = html.xpath('//div[@id="gsc_sa_ccl"]/div[@class="gsc_1usr"]/div/a/@href')
    contents = [ii.text for ii in html.xpath('//div[@id="gsc_sa_ccl"]/div[@class="gsc_1usr"]//div[@class="gs_ai_aff"]')]
    print(contents)
    if len(users_links) == len(contents):
        for use, co in zip(users_links, contents):
            if co:
                if 'Zhejiang' in co and 'Technology' in co:
                    real_user_id.append(re.findall('.*user=(.*)', use)[0])
    print(real_user_id)
def get_msg(id):
    titless, update_timess, yinyong_numss, authorss, qikanss = [], [], [], [], []
    for pg in [0,100,200]:

        url = f'https://scholar.google.com/citations?hl=en&user={id}&cstart={pg}&pagesize=100'
        data = {
            'json': '1'
        }
        r = requests.post(url,headers=headers,data=data,proxies=proxies)
        results = r.json().get('B')
        if results:
            html = etree.HTML(results)
            qikans = [ii.text for ii in html.xpath('//td[@class="gsc_a_t"]/div[2]')]
            titles = [ii.text for ii in html.xpath('//a[@class="gsc_a_at"]')]
            yinyong_nums = [ii.text for ii in html.xpath('//a[@class="gsc_a_ac gs_ibl"]')]
            update_times = [ii.text for ii in html.xpath('//td[@class="gsc_a_y"]/span')]
            authors = [ii.text for ii in html.xpath('//td[@class="gsc_a_t"]/div[1]')]
            qikanss += qikans
            titless += titles
            yinyong_numss += yinyong_nums
            update_timess += update_times
            authorss += authors
            print(authors)
            print(len(authors))
            print(qikans)
            print(len(qikans))
            print(titles)
            print(len(titles))
            print(yinyong_nums)
            print(len(yinyong_nums))
            print(update_times)
            print(len(update_times))
            detail_links = ['https://scholar.google.com'+ i for i in html.xpath('//td[@class="gsc_a_t"]/a/@href')]
            print(detail_links)
            print(len(detail_links))
    df = pd.DataFrame({
        '标题':titless,
        '年份':update_timess,
        '引用次数':yinyong_numss,
        '作者':authorss,
        '期刊/会议':qikanss
    })
    df.to_csv('导师谷歌学术.csv',index=False,encoding='utf_8_sig',mode='a',header=False)

if __name__ == '__main__':
    ky = ['ronghua liang']

    get_msg(ids[3])


以上代码为思路,不可直接运行,纯属记录我的工作思路

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