python书籍信息爬虫实例

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-8

import re
import logging
import requests
import pymysql
import random
import time
import datetime
from hashlib import md5
from bs4 import BeautifulSoup

logging.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 conn

def 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我们。

您可能感兴趣的文章:

• 零基础写python爬虫之爬虫编写全记录
• Python爬虫框架Scrapy安装使用步骤
• 零基础写python爬虫之使用urllib2组件抓取网页内容
• 使用Python编写简单网络爬虫抓取视频下载资源
• Python爬虫模拟登录带验证码网站
• 零基础写python爬虫之使用Scrapy框架编写爬虫
• python模拟新浪微博登陆功能(新浪微博爬虫)
• python抓取网页图片示例(python爬虫)
• Python实现抓取页面上链接的简单爬虫分享
• 零基础写python爬虫之HTTP异常处理