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python监控百度PC前五页/四页/三页/二页/首页词数-分关键词种类
老董-我爱我家房产SEO2020-09-10179围观,100赞
必看!必看!必看!
1 鼠标的动作或者滚动条下拉会触发gif请求,这是百度反爬的一个因素。
2 所以直接拼接翻页url抓取来的页面内容和实际点击搜索的不一样,移动端特别明显,PC也是。
3 直接访问拼接url必须加cookie否则很快就被反爬
最好是selenium驱动浏览器搜索获取源码,这样才准确,但是太费时间。
本脚本是直接拼接的翻页url,不喜可不用!
脚本功能:
给定一批行业词,分关键词种类批量监控某个域名首页、前二页、前三页、前四页、前五页词数的变化!
脚本说明:
1)bdpc1_page5_info.txt记录每个kwd在第几页有排名
2)bdpc1_page5_rankurl.txt记录每个kwd在前五页对应的排名url,同一个页面出现多个就记多个
3)bdpc1_page5.xlsx和bdpc1_page5.txt是统计结果
4)bdpc1_page5_info.txt的行数为查询成功词数
5)关键词文件kwd_core_city.xlsx中sheet名代表关键词种类,每个sheet第一列放关键词
6)线程数默认是1,现在百度反爬比之前严重!线程最好是1。【此外,多线程写同一个文件需要加锁否则可能数据错乱】
提示:
脚本如果有问题请及时反馈,任何爬虫程序都不能永久运行因为对方网站稍微一调整爬虫程序 就得跟着更新。
# ‐*‐ coding: utf‐8 ‐*‐ """ 分关键词种类批量查询首页/前二/三/四/五/五页覆盖率 bdpc1_page5_info.txt记录每个kwd在第几页有排名 bdpc1_page5_rankurl.txt记录每个kwd前五页排名的url,页面出现多个就记多个 bdpc1_page5.xlsx和bdpc1_page5.txt是统计结果 bdpc1_page5_info.txt的行数为查询成功词数 kwd_core_city.xlsx中sheet名代表关键词种类,每个sheet第一列放关键词 cookie必须是登录baidu账号后的cookie否则很容易被反爬 """ import requests from pyquery import PyQuery as pq import threading import queue import time from urllib.parse import urlparse from openpyxl import load_workbook from openpyxl import Workbook import time import gc # 计算最终结果 def get_result(file_path, result, result_last): # 读取文件 计算首页到五页每页词数 for line in open(file_path, 'r', encoding='utf-8'): line = line.strip().split(' ') page = line[1] group = line[2] result[group][page] += 1 # 计算首页、前二页、前三页、前四页、前五页词数 for group, page_num in result.items(): print(group, page_num) for page, num in page_num.items(): if page == '五页后': result_last[group]['五页后'] = num if page in ['首页', '二页', '三页', '四页', '五页']: result_last[group]['前五页'] += num if page in ['首页', '二页', '三页', '四页']: result_last[group]['前四页'] += num if page in ['首页', '二页', '三页']: result_last[group]['前三页'] += num if page in ['首页', '二页']: result_last[group]['前二页'] += num if page == '首页': result_last[group]['首页'] += num return result_last # 写入excel文件 def write_excel(group_list, result_last, today): wb = Workbook() # 创建sheet for group in group_list: sheet_num = 0 wb.create_sheet(u'{0}'.format(group), index=sheet_num) sheet_num += 1 # 写内容 row_first = ['日期', '首页', '前二页', '前三页', '前四页', '前五页', '五页后'] for group, data_dict in result_last.items(): # 写第一行表头 wb[group].append(row_first) # 写数据 row_value = [today] for page, value in data_dict.items(): row_value.append(value) wb[u'{0}'.format(group)].append(row_value) wb.save('{0}bdpc1_page5.xlsx'.format(today)) class bdpcCoverPage5(threading.Thread): def __init__(self): threading.Thread.__init__(self) @staticmethod def read_excel(filepath): q = queue.Queue() group_list = [] kwd_dict = {} wb_kwd = load_workbook(filepath) for sheet_obj in wb_kwd: sheet_name = sheet_obj.title group_list.append(sheet_name) kwd_dict[sheet_name]= [] col_a = sheet_obj['A'] for cell in col_a: kwd = (cell.value) # 加个判断吧 if kwd: q.put([sheet_name,kwd]) return q, group_list # 初始化结果字典 @staticmethod def result_init(group_list): pages = ['首页','二页','三页','四页','五页','五页后'] result = {} #记录首页、第二页..第五页各多少词 for group in group_list: result[group] = {} for group in group_list: for page in pages: result[group][page] = 0 print("结果字典init...") return result # 初始化最后结果字典 @staticmethod def result_last_init(group_list): result_last = {} # 记录首页、第二页..第五页各多少词 pages = ['首页','前二页','前三页','前四页','前五页','五页后'] for group in group_list: result_last[group] = {} for group in group_list: for page in pages: result_last[group][page] = 0 print("最终结果字典init...") return result_last # 获取某词serp源码 def get_html(self,url,retry=2): try: r = requests.get(url=url,headers=user_agent,timeout=5) except Exception as e: print('获取源码失败',e) time.sleep(6) if retry > 0: self.get_html(url,retry-1) else: html = r.content.decode('utf-8',errors='ignore') # 用r.text有时候识别错误 url = r.url # 反爬会重定向,取定向后的地址 return html,url # 获取某词serp源码上自然排名的所有url def get_encrpt_urls(self,html,url): encrypt_url_list = [] doc = pq(html) title = doc('title').text() if '_百度搜索' in title and 'https://www.baidu.com/s?tn=48020221' in url: try: a_list = doc('.t a').items() except Exception as e: print('未提取到serp上的解密url', e) else: for a in a_list: encrypt_url = a.attr('href') if encrypt_url.find('http://www.baidu.com/link?url=') == 0: encrypt_url_list.append(encrypt_url) else: print(title,'源码异常,可能反爬') time.sleep(6) return encrypt_url_list # 解密某条加密url def decrypt_url(self,encrypt_url,retry=1): real_url = None # 默认None try: encrypt_url = encrypt_url.replace('http://','https://') # print(encrypt_url) r = requests.head(encrypt_url,headers=user_agent) except Exception as e: print(encrypt_url,'解密失败',e) time.sleep(6) if retry > 0: self.decrypt_url(encrypt_url,retry-1) else: real_url = r.headers['Location'] return real_url # 获取某词serp源码首页排名真实url def get_real_urls(self,encrypt_url_list): real_url_list = [self.decrypt_url(encrypt_url) for encrypt_url in encrypt_url_list] real_url_set = set(real_url_list) real_url_set = real_url_set.remove(None) if None in real_url_set else real_url_set real_url_list = list(real_url_set) return real_url_list # 提取某url的域名部分 def get_domain(self,real_url): domain = None try: res = urlparse(real_url) except Exception as e: print (e,real_url) else: domain = res.netloc return domain # 获取某词serp源码首页排名所有域名 def get_domains(self,real_url_list): domain_list = [self.get_domain(real_url) for real_url in real_url_list] # 一个词某域名多个url有排名,计算一次 domain_set = set(domain_list) domain_set = domain_set.remove(None) if None in domain_set else domain_set domain_str = ','.join(domain_set) return domain_str # 线程函数 def run(self): while 1: group_kwd = q.get() group,kwd = group_kwd print(group,kwd) try: for page in page_dict.keys(): if page == '': url = "https://www.baidu.com/s?tn=48020221_28_hao_pg&ie=utf-8&wd={0}".format(kwd) else: url = "https://www.baidu.com/s?tn=48020221_28_hao_pg&ie=utf-8&wd={0}&pn={1}".format(kwd,page) html,now_url = self.get_html(url) encrypt_url_list = self.get_encrpt_urls(html,now_url) # 源码ok再写入 if encrypt_url_list: real_url_list = self.get_real_urls(encrypt_url_list) domain_str = self.get_domains(real_url_list) if domain_str and domain in domain_str: page = '首页' if page == '' else page_dict[page] f.write('{0}{1}{2}'.format(kwd,page,group)) for real_url in real_url_list: if domain in real_url: f_url.write('{0}{1}{2}{3}'.format(kwd,page,group,real_url)) break if page == 40 and domain not in domain_str: f.write('{0}{1}{2}'.format(kwd,'五页后',group)) f.flush() f_url.flush() except Exception as e: print(e) finally: del kwd gc.collect() q.task_done() if __name__ == "__main__": start = time.time() local_time = time.localtime() today = time.strftime('%Y%m%d',local_time) domain = '5i5j.com' user_agent = { 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.97 Safari/537.36', 'Host': 'www.baidu.com', 'Referer': 'https://www.hao123.com/?tn=48020221_28_hao_pg', 'is_xhr': '1', 'X-Requested-With': 'XMLHttpRequest', 'is_referer': 'https://www.baidu.com/s?ie=utf-8&f=8&rsv_bp=1&srcqid=3720942946388228931&tn=48020221_28_hao_pg&wd=seo&rsv_pq=e98531eb0004488e&rsv_t=1746b7LmCS0qfn89n4GHuc6v28Qh9vRpiPuJS%2FiLAQCSn3MUkcks%2F5JTuoHtkycJ%2BbGMoBBU0z8%2F&rqlang=cn', 'cookie':'BIDUPSID=95E739A8EE050812705C1FDE2584A61E; PSTM=1563865961; BAIDUID=95E739A8EE050812705C1FDE2584A61E:SL=0:NR=10:FG=1; BDUSS=NMRzZPVUFqR0JtbzJJc1ZDdkx2MGtiQUpvWVNUSjhnSUFmRFRmTnpDdmpGcXhkRVFBQUFBJCQAAAAAAAAAAAEAAADag5oxzI2IkAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAOOJhF3jiYRdOU; NOJS=1; BD_UPN=12314353; MSA_WH=346_288; H_WISE_SIDS=136721_138198_137831_114177_139149_120169_138490_133995_138878_137979_132909_137690_131247_137750_136680_118880_118865_118839_118832_118793_138165_107313_136431_138845_138691_136863_138147_139174_138776_136195_131861_137105_133847_138476_137734_138343_137467_138648_131423_138663_136537_138178_110085_137441_127969_137829_138275_127417_138312_137187_136635_138425_138562_138943_135718_138302_138239; H_PS_PSSID=1440_21099_30210_30245_29699_26350; sug=0; sugstore=0; ORIGIN=0; bdime=20100; H_PS_645EC=607dCUWuXpw3NdlXp716wheeouvfrYMdSgV%2FDEOshMglObRb1YYwNQxR0mI; BDORZ=B490B5EBF6F3CD402E515D22BCDA1598; BDSVRTM=0; COOKIE_SESSION=55433_0_8_8_3_12_0_1_7_5_215_3_55436_0_9_0_1575596447_0_1575596438%7C9%231036863_54_1573608641%7C9' } q,group_list = bdpcCoverPage5.read_excel('kwd_core_city.xlsx') # 关键词队列及分类 result = bdpcCoverPage5.result_init(group_list) # 结果字典-记录首页到5页各多少词 result_last = bdpcCoverPage5.result_last_init(group_list) # 结果字典-统计首页,前2页到前5页多少词 all_num = q.qsize() # 总词数 page_dict = {'':'首页',10:'二页',20:'三页',30:'四页',40:'五页'} # 查询页码 f = open('{0}bdpc1_page5_info.txt'.format(today),'w',encoding="utf-8") f_url = open('{0}bdpc1_page5_rankurl.txt'.format(today),'w',encoding="utf-8") file_path = f.name # 设置线程数 for i in list(range(1)): t = bdpcCoverPage5() t.setDaemon(True) t.start() q.join() f.close() f_url.close() # 根据bdpc1_page5_info.txt数据计算结果 result_last = get_result(file_path,result,result_last) # 写入txt文件 with open('{0}bdpc1_page5.txt'.format(today), 'w', encoding="utf-8") as f: for group,data_dict in result_last.items(): for page,value in data_dict.items(): f.write(group + ' ' + page + ' ' + str(value) + ' ') end = time.time() # 写入excel write_excel(group_list,result_last,today) print('关键词共{0}个,成功个数看page5_info.txt,耗时{1}min'.format(all_num, (end - start) / 60))
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