Python爬取搜集豆瓣图书集，书荒的朋友们再也不用担心了

0. 前序

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每天迈出一小步，朝着目标迈一大步。

书荒的朋友可以不用担心了，我们可以通过豆瓣图书喜欢的标签，获取相应的图书。把对应的书名，价格，评分等等都归类下载下来。

1. 数据怎么来

首先打开豆瓣读书的官网链接，然后选择对应喜欢的标签，通过F12分析页面数据。

我们会看到搜索出来的结果，大概有五十多页，要是人工一页页翻，不知道翻到啥时候。这时我们可以用爬虫，把这些信息都下载下来。

2. 数据处理

思路如下：

1. 通过requests去获取网站数据，每次拉取15行数据。
2. 豆瓣返回的是html文件，这里通过BeautifulSoup去解析文件。
3. 通过书籍详情链接去获取作者信息。
4. 最后把爬到书籍信息存到excel里。

完整源码如下：

#-*- coding: UTF-8 -*-

import time
import requests
import numpy as np
from bs4 import BeautifulSoup
from openpyxl import Workbook


#Some User Agents
hds=[{'User-Agent':'Mozilla/5.0 (Windows; U; Windows NT 6.1; en-US; rv:1.9.1.6) Gecko/20091201 Firefox/3.5.6'},\
{'User-Agent':'Mozilla/5.0 (Windows NT 6.2) AppleWebKit/535.11 (KHTML, like Gecko) Chrome/17.0.963.12 Safari/535.11'},\
{'User-Agent': 'Mozilla/5.0 (compatible; MSIE 10.0; Windows NT 6.2; Trident/6.0)'}]


def book_spider(book_tag):
    page_num=0;
    book_list=[]
    try_times=0
    
    while(1):
        # url='http://www.douban.com/tag/%E5%B0%8F%E8%AF%B4/book?start=0' # For Test
        # url='http://www.douban.com/tag/'+urllib.quote(book_tag)+'/book?start='+str(page_num*15)
        url='http://www.douban.com/tag/'+book_tag+'/book?start='+str(page_num*15)
        time.sleep(np.random.rand()*5)
        
        #Last Version
        try:
            req = requests.get(url, headers=hds[page_num%len(hds)])
            source_code = req.text
        except Exception as e:
            print(e)
            continue
  
        soup = BeautifulSoup(source_code, "html.parser")
        list_soup = soup.find('div', {'class': 'mod book-list'})
        
        try_times+=1;
        if list_soup is None and try_times<200:
            continue
        elif list_soup is None or len(list_soup)<=1 or page_num == 3:
            break # Break when no informatoin got after 200 times requesting
        
        for book_info in list_soup.findAll('dd'):
            title = book_info.find('a', {'class':'title'}).string.strip()
            desc = book_info.find('div', {'class':'desc'}).string.strip()
            desc_list = desc.split('/')
            book_url = book_info.find('a', {'class':'title'}).get('href')
            
            try:
                author_info = '作者/译者：' + '/'.join(desc_list[0:-3])
            except:
                author_info ='作者/译者：暂无'
            try:
                pub_info = '出版信息：' + '/'.join(desc_list[-3:])
            except:
                pub_info = '出版信息：暂无'
            try:
                rating = book_info.find('span', {'class':'rating_nums'}).string.strip()
            except:
                rating='0.0'
            try:
                #people_num = book_info.findAll('span')[2].string.strip()
                people_num = get_people_num(book_url)
                people_num = people_num.strip('人评价')
            except:
                people_num ='0'
            
            book_list.append([title,rating,people_num,author_info,pub_info])
            try_times=0 #set 0 when got valid information
        page_num += 1
        print('Downloading Information From Page %d' % page_num)
    return book_list


def get_people_num(url):
    #url='http://book.douban.com/subject/6082808/?from=tag_all' # For Test
    req = requests.get(url, headers=hds[np.random.randint(0, len(hds))])
    source_code = req.text
    soup = BeautifulSoup(source_code, "html.parser")
    people_num = soup.find('div', {'class':'rating_sum'}).findAll('span')[1].string.strip()
    return people_num


def do_spider(book_tag_lists):
    book_lists = []
    for book_tag in book_tag_lists:
        book_list = book_spider(book_tag)
        book_list = sorted(book_list, key=lambda x:x[1],reverse=True)
        book_lists.append(book_list)
    return book_lists


def print_book_lists_excel(book_lists, book_tag_lists):
    wb = Workbook()
    ws = []
    for i in range(len(book_tag_lists)):
        ws.append(wb.create_sheet(title=book_tag_lists[i]))
    for i in range(len(book_tag_lists)):
        ws[i].append(['序号', '书名', '评分', '评价人数', '作者', '出版社'])
        count=1
        for bl in book_lists[i]:
            ws[i].append([count, bl[0], float(bl[1]), int(bl[2]), bl[3], bl[4]])
            count += 1
    save_path='book_list'
    for i in range(len(book_tag_lists)):
        save_path += ('-'+book_tag_lists[i])
    save_path += '.xlsx'
    wb.save(save_path)




if __name__=='__main__':
    #book_tag_lists = ['心理','判断与决策','算法','数据结构','经济','历史']
    #book_tag_lists = ['传记','哲学','编程','创业','理财','社会学','佛教']
    #book_tag_lists = ['思想','科技','科学','web','股票','爱情','两性']
    #book_tag_lists = ['计算机','机器学习','linux','android','数据库','互联网']
    #book_tag_lists = ['数学']
    #book_tag_lists = ['摄影','设计','音乐','旅行','教育','成长','情感','育儿','健康','养生']
    #book_tag_lists = ['商业','理财','管理']  
    # book_tag_lists = ['名著']
    #book_tag_lists = ['科普','经典','生活','心灵','文学']
    #book_tag_lists = ['科幻','思维','金融']

    book_tag_lists = ['武侠']
    book_lists=do_spider(book_tag_lists)
    print_book_lists_excel(book_lists, book_tag_lists)

3. 写在最后

代码中加了周期间隔，刚开始验证测试的时候，最好先选取单个标签，防止代码运行过长。

另外，每个标签返回的书籍列表会很多，可以加相应的页数限制，让效果更加明显，当然了想一下子获取全部可以忽略。