Python爬虫爬取目标小说并保存到本地
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利用Python爬虫爬取目标小说并保存到本地
小说地址:http://book.zongheng.com/showchapter/749819.html(目录地址)
通过小说目录获取小说所有章节对应的url地址,然后逐个访问解析得到每一章节小说的内容,最后保存到本地文件内
文章中的代码只是第一个版本,可以自行优化
例如:使用IP代理池防止IP地址被封禁
使用多线程对小说章节内容进行爬取可以提高爬取效率,降低运行时间
构建更加详细的requests请求头
代码还有诸多不足,欢迎指导
1 import requests 2 import bs4 3 from bs4 import BeautifulSoup 4 import lxml 5 import urllib 6 7 8 def getMuLu(Html): 9 """ 10 函数getMuLu由主函数传入小说目录网址,经解析后返回每一章节的具体网址 11 涉及内容: 12 requests库:进行网页请求 13 BeautifulSouping库:解析请求返回的网页内容 14 时间:2020-05-15 15 16 环境:Windows + python3.8 17 工具:Pycharm 18 21 22 """ 23 #构建请求头 24 headers = { 25 ‘User-Agent‘: ‘Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/52.0.2743.116 Safari/537.36‘ 26 } 27 #使用requests中的get方法请求网址并转换为text格式 28 demo = requests.get(Html) 29 demo1 = demo.text 30 31 #使用BeautifulSoup库对text格式的网页内容进行解析 32 soup = BeautifulSoup(demo1, ‘html.parser‘) 33 34 #将soup变量的值中的所有ID为list的标签返回到MuLu在转换为str类型后再次使用BeautifulSoup库进行解析 35 MuLu = soup.find_all(class_ = ‘volume-list‘) 36 soup1 = BeautifulSoup(str(MuLu), ‘html.parser‘) 37 38 #对soup1解析后将所有的a标签进行取出并赋值href1 39 href1 = soup1.find_all(‘li‘) 40 soup2 = BeautifulSoup(str(href1), ‘html.parser‘) 41 href2 = soup2.find_all(‘a‘) 42 43 #将所有a标签取出后,将a标签中href属性的值存储到列表类型的Web3中 44 Web3 = [] 45 for link in href2: 46 Web1 = link.get(‘href‘) 47 Web3.append(Web1) 48 return Web3 49 50 51 def getText(TextUrl): 52 53 """ 54 函数getText由主函数传入小说目录网址,经解析后返回小说目录以及正文 55 涉及内容: 56 requests库:进行网页请求 57 BeautifulSouping库:解析请求返回的网页内容 58 时间:2020-05-15 59 60 """ 61 i = 0 62 Mu = [] 63 for i in range(len(TextUrl)): 64 headers = { 65 ‘User-Agent‘: ‘Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36‘, 66 ‘Cookie‘: ‘lianjia_uuid=9d3277d3-58e4-440e-bade-5069cb5203a4; ‘ 67 ‘UM_distinctid=16ba37f7160390-05f17711c11c3e-454c0b2b-100200-16ba37f716618b; _smt_uid=5d176c66.5119839a; sensorsdata2015jssdkcross=%7B%22distinct_id%22%3A%2216ba37f7a942a6-0671dfdde0398a-454c0b2b-1049088-16ba37f7a95409%22%2C%22%24device_id%22%3A%2216ba37f7a942a6-0671dfdde0398a-454c0b2b-1049088-16ba37f7a95409%22%2C%22props%22%3A%7B%22%24latest_traffic_source_type%22%3A%22%E7%9B%B4%E6%8E%A5%E6%B5%81%E9%87%8F%22%2C%22%24latest_referrer%22%3A%22%22%2C%22%24latest_referrer_host%22%3A%22%22%2C%22%24latest_search_keyword%22%3A%22%E6%9C%AA%E5%8F%96%E5%88%B0%E5%80%BC_%E7%9B%B4%E6%8E%A5%E6%89%93%E5%BC%80%22%7D%7D; _ga=GA1.2.1772719071.1561816174; Hm_lvt_9152f8221cb6243a53c83b956842be8a=1561822858; _jzqa=1.2532744094467475000.1561816167.1561822858.1561870561.3; CNZZDATA1253477573=987273979-1561811144-%7C1561865554; CNZZDATA1254525948=879163647-1561815364-%7C1561869382; CNZZDATA1255633284=1986996647-1561812900-%7C1561866923; CNZZDATA1255604082=891570058-1561813905-%7C1561866148; _qzja=1.1577983579.1561816168942.1561822857520.1561870561449.1561870561449.1561870847908.0.0.0.7.3; select_city=110000; lianjia_ssid=4e1fa281-1ebf-e1c1-ac56-32b3ec83f7ca; srcid=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‘ 68 } 69 70 QingQiu = urllib.request.urlopen(TextUrl[i]).read() 71 date = QingQiu.decode(‘utf-8‘) 72 73 SoupText = BeautifulSoup(date,‘html.parser‘) 74 #通过解析SoupText获取章节名称 75 MingCheng = SoupText.find_all(class_ = ‘title_txtbox‘) 76 MingCheng1 = BeautifulSoup(str(MingCheng),‘lxml‘) 77 MingCheng2 = MingCheng1.get_text() 78 ls4 = ‘‘.join(MingCheng2) 79 80 #通过解析SoupText获取章节正文 81 BiaoTi = SoupText.find_all(class_ = ‘content‘) #在全部的html中查找class_ = ‘content‘的div标签 82 83 BiaoTi1 = BeautifulSoup(str(BiaoTi), ‘lxml‘) 84 BiaoTi2 = BiaoTi1.find_all(‘p‘) #获取p标签 85 86 #通过遍历p标签获取正文内容 87 qbs = 0 88 KongList = [] 89 for qbs in range(len(BiaoTi2)): 90 ZhangJie = BiaoTi2[qbs] 91 S = BeautifulSoup(str(ZhangJie), ‘html.parser‘) 92 str1 = S.get_text() 93 KongList.append(str1) 94 qbs += 1 95 96 #将列表转换为字符串类型 97 ls3 = ‘‘.join(KongList) 98 #通过组合返回章节名称以及正文内容 99 100 #将两个字符串类型数据组合为一个并返回 101 NeiRong = ls4 + ls3 102 103 104 #将所有内容写入列表Mu并返回 105 Mu.append(NeiRong) 106 107 return Mu 108 109 def BaoCunText(WenBen): 110 """ 111 函数BaoCunText由主函数传入小说目录以及内容,写入txt文件 112 涉及内容: 113 文件处理: 114 打开,写入,关闭文件 115 for遍历 116 时间:2020-05-16 117 """ 118 #打开文件 119 FlieText = open(‘MiMiShiMing.txt‘,‘a‘,encoding=‘utf-8‘) 120 #遍历列表WenBen,并利用索引写入文件,在每章节后换行 121 i = 0 122 for i in range(len(WenBen)): 123 FlieText.write(str(WenBen[i])) 124 FlieText.write(‘ ‘) 125 print("第{}章写入成功".format(i)) 126 i += 1 127 print("写入完成") 128 #关闭文件 129 FlieText.close() 130 131 if __name__ == ‘__main__‘: 132 """ 133 主函数:调用其他函数以及向函数传值 134 135 时间:2020-5-17 136 137 138 """ 139 140 url = ‘http://book.zongheng.com/showchapter/749819.html‘ 141 MuLuLianjie = getMuLu(url) 142 XiaoShuo = getText(MuLuLianjie) 143 BaoCunText(XiaoShuo)
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