python书籍信息爬虫示例，供大家参考，具体内容如下

背景说明

需要收集一些书籍信息，以豆瓣书籍条目作为源，得到一些有效书籍信息，并保存到本地数据库。

获取书籍分类标签

具体可参考这个链接：
https://book.douban.com/tag/?view=type

然后将这些分类标签链接存到本地某个文件，存储内容如下

https://book.douban.com/tag/小说https://book.douban.com/tag/外国文学https://book.douban.com/tag/文学https://book.douban.com/tag/随笔https://book.douban.com/tag/中国文学https://book.douban.com/tag/经典https://book.douban.com/tag/日本文学https://book.douban.com/tag/散文https://book.douban.com/tag/村上春树https://book.douban.com/tag/诗歌https://book.douban.com/tag/童话......

获取书籍信息，并保存本地数据库

假设已经建好mysql表，如下：

CREATE TABLE `book_info` ( `id` int(11) NOT NULL AUTO_INCREMENT, `bookid` varchar(64) NOT NULL COMMENT 'book ID', `tag` varchar(32) DEFAULT '' COMMENT '分类目录', `bookname` varchar(256) NOT NULL COMMENT '书名', `subname` varchar(256) NOT NULL COMMENT '二级书名', `author` varchar(256) DEFAULT '' COMMENT '作者', `translator` varchar(256) DEFAULT '' COMMENT '译者', `press` varchar(128) DEFAULT '' COMMENT '出版社', `publishAt` date DEFAULT '0000-00-00' COMMENT '出版日期', `stars` float DEFAULT '0' COMMENT '评分', `price_str` varchar(32) DEFAULT '' COMMENT '价格string', `hotcnt` int(11) DEFAULT '0' COMMENT '评论人数', `bookdesc` varchar(8192) DEFAULT NULL COMMENT '简介', `updateAt` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '修改日期', PRIMARY KEY (`id`), UNIQUE KEY `idx_bookid` (`bookid`), KEY `idx_bookname` (`bookname`), KEY `hotcnt` (`hotcnt`), KEY `stars` (`stars`), KEY `idx_tag` (`tag`)) ENGINE=InnoDB DEFAULT CHARSET=utf8 COMMENT='书籍信息';

并已实现相关爬虫逻辑，主要用到了BeautifulSoup包，如下：

#!/usr/bin/python# coding: utf-8import reimport loggingimport requestsimport pymysqlimport randomimport timeimport datetimefrom hashlib import md5from bs4 import BeautifulSouplogging.basicConfig(level=logging.INFO, format='[%(levelname)s][%(name)s][%(asctime)s]%(message)s', datefmt='%Y-%m-%d %H:%M:%S')class DestDB: Host = "192.168.1.10" DB = "spider" Table = "book_info" User = "test" Pwd = "123456"def connect_db(host, db, user, pwd): conn = pymysql.connect( host=host, user=user, passwd=pwd, db=db, charset='utf8', connect_timeout=3600) #,# cursorclass=pymysql.cursors.DictCursor) conn.autocommit(True) return conndef disconnect_db(conn, cursor): cursor.close() conn.close()#提取评价人数，如果评价人数少于10人，按10人处理def hotratings(person): try: ptext = person.get_text().split()[0] pc = int(ptext[1:len(ptext)-4]) except ValueError: pc = int(10) return pc# 持久化到数据库def save_to_db(tag, book_reslist): dest_conn = connect_db(DestDB.Host, DestDB.DB, DestDB.User, DestDB.Pwd) dest_cursor = dest_conn.cursor() isql = "insert ignore into book_info " isql += "(`bookid`,`tag`,`author`,`translator`,`bookname`,`subname`,`press`," isql += "`publishAt`,`price_str`,`stars`,`hotcnt`,`bookdesc`) values " isql += ",".join(["(%s)" % ",".join(['%s']*12)]*len(book_reslist)) values = [] for row in book_reslist: # 暂时将md5(bookname+author)作为bookid唯一指 bookid = md5(("%s_%s"%(row[0],row[2])).encode('utf-8')).hexdigest() values.extend([bookid, tag]+row[:10]) dest_cursor.execute(isql, tuple(values)) disconnect_db(dest_conn, dest_cursor)# 处理每一次访问的页面def do_parse(tag, url): page_data = requests.get(url) soup = BeautifulSoup(page_data.text.encode("utf-8"), "lxml") # 提取标签信息 tag = url.split("?")[0].split("/")[-1] # 抓取作者，出版社信息 details = soup.select("#subject_list > ul > li > div.info > div.pub") # 抓取评分 scores = soup.select("#subject_list > ul > li > div.info > div.star.clearfix > span.rating_nums") # 抓取评价人数 persons = soup.select("#subject_list > ul > li > div.info > div.star.clearfix > span.pl") # 抓取书名 booknames = soup.select("#subject_list > ul > li > div.info > h2 > a") # 抓取简介 descs = soup.select("#subject_list > ul > li > div.info > p") # 从标签信息中分离内容 book_reslist = [] for detail, score, personCnt, bookname, desc in zip(details, scores, persons, booknames, descs): try: subtitle = "" title_strs = [s.replace('\n', '').strip() for s in bookname.strings] title_strs = [s for s in title_strs if s] # 部分书籍有二级书名 if not title_strs: continue elif len(title_strs) >= 2: bookname, subtitle = title_strs[:2] else: bookname = title_strs[0] # 评分人数 hotcnt = hotratings(personCnt) desc = desc.get_text() stars = float('%.1f' % float(score.get_text() if score.get_text() else "-1")) author, translator, press, publishAt, price = [""]*5 detail_texts = detail.get_text().replace('\n', '').split("/") detail_texts = [s.strip() for s in detail_texts] # 部分书籍无译者信息 if len(detail_texts) == 4: author, press, publishAt, price = detail_texts[:4] elif len(detail_texts) >= 5: author, translator, press, publishAt, price = detail_texts[:5] else: continue # 转换出版日期为date类型 if re.match('^[\d]{4}-[\d]{1,2}', publishAt): dts = publishAt.split('-') publishAt = datetime.date(int(dts[0]), int(dts[1]), 1) else: publishAt = datetime.date(1000, 1, 1) book_reslist.append([author, translator, bookname, subtitle, press, publishAt, price, stars, hotcnt, desc]) except Exception as e: logging.error(e) logging.info("insert count: %d" % len(book_reslist)) if len(book_reslist) > 0: save_to_db(tag, book_reslist) book_reslist = [] return len(details)def main(): with open("book_tags.txt") as fd: tags = fd.readlines() for tag in tags: tag = tag.strip() logging.info("current tag url: %s" % tag) for idx in range(0, 1000000, 20): try: url = "%s?start=%d&type=T" % (tag.strip(), idx) cnt = do_parse(tag.split('/')[-1], url) if cnt < 10: break # 睡眠若干秒，降低访问频率 time.sleep(random.randint(10, 15)) except Exception as e: logging.warn("outer_err: %s" % e) time.sleep(300)if __name__ == "__main__": main()

小结

以上代码基于python3环境来运行；
需要首先安装BeautifulSoup: pip install bs4
爬取过程中需要控制好访问频率；
需要对一些信息进行异常处理，比如译者信息、评论人数等。

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持。