爬虫简单之二---使用进程爬取起点中文网的六万多也页小说的名字，作者，等一些基本信息，并存入csv中

爬虫简单之二---使用进程爬取起点中文网的六万多也页小说的名字，作者，等一些基本信息，并存入csv中

准备使用的环境和库Python3.6 + requests + bs4 + csv + multiprocessing

库的说明

• requests模拟计算机对服务器发送requests请求
• bs4：页面分析功能，分析页面找到所需要的特定内容
• xlwt：把爬取的内容存入csv文件中
• multiprocessing：开启多进程爬取

1.准备URLs

起点中文网 起点中文网的URL：https://www.qidian.com/all?orderId=&style=1&pageSize=20&siteid=1&pubflag=0&hiddenField=0&page=2 发现通过改变最后以为数字可以变换页数，由主页内容可知一共有61732页。 使用 urls = ['https://www.qidian.com/all?orderId=&style=1&pageSize=20&siteid=1&pubflag=0&hiddenField=0&page=' + str(k) for k in range(1, 61723)]这个语句可以构造一个所有连接的列表，供后面多进程使用。

2.使用requests库获取页面和使用bs4库来解析页面内容

1. html = requests.get(url, headers=headers)
2. selector = BeautifulSoup(html.text, 'lxml')
3. names = selector.select(
4. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > h4 > a')
5. writers = selector.select(
6. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > p.author > a.name')
7. sign1s = selector.select(
8. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > p.author > a:nth-child(4)')
9. sign2s = selector.select(
10. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > p.author > a.go-sub-type')
11. types = selector.select(
12. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > p.author > span')
13. traductions = selector.select(
14. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > p.intro')
15. words = selector.select(
16. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > p.update > span > span')

3.把信息存储到xls中

1. head = ['title', 'author', 'sign1', 'sign2', 'type', 'traduction', 'words']
2. f = open('_06_qidian.csv', 'a+')
3. csv_writer = csv.writer(f)
4. csv_writer.writerow(head)
7. for info in range(len(names)):
8. csv_writer.writerow((names[info].get_text(), writers[info].get_text(), sign1s[info].get_text(), sign2s[info].get_text(), types[info].get_text(), traductions[info].get_text(), words[info].get_text()))

4.最后就可以开足马力使用多进程进行爬取了，这里使用的进程数正好是cpu核心的数量。

1. pool = Pool(processes=multiprocessing.cpu_count())
2. pool.map(get_info, urls)
3. pool.close()
4. pool.join()

5.完整代码

1. import requests
2. from bs4 import BeautifulSoup
3. import xlwt
4. from multiprocessing import Pool
5. import multiprocessing
6. import csv
9. def get_info(url):
10. print(url)
11. global i
12. html = requests.get(url, headers=headers)
13. selector = BeautifulSoup(html.text, 'lxml')
14. names = selector.select(
15. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > h4 > a')
16. writers = selector.select(
17. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > p.author > a.name')
18. sign1s = selector.select(
19. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > p.author > a:nth-child(4)')
20. sign2s = selector.select(
21. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > p.author > a.go-sub-type')
22. types = selector.select(
23. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > p.author > span')
24. traductions = selector.select(
25. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > p.intro')
26. words = selector.select(
27. 'body > div.wrap > div.all-pro-wrap.box-center.cf > div.main-content-wrap.fl > div.all-book-list > div > ul > li > div.book-mid-info > p.update > span > span')
28. for info in range(len(names)):
29. csv_writer.writerow((names[info].get_text(), writers[info].get_text(), sign1s[info].get_text(), sign2s[info].get_text(), types[info].get_text(), traductions[info].get_text(), words[info].get_text()))
33. if __name__ == '__main__':
34. head = ['title', 'author', 'sign1', 'sign2', 'type', 'traduction', 'words']
35. f = open('_06_qidian.csv', 'a+')
36. csv_writer = csv.writer(f)
37. csv_writer.writerow(head)
40. headers = {
41. 'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.86 Safari/537.36',
43. }
44. urls = ['https://www.qidian.com/all?orderId=&style=1&pageSize=20&siteid=1&pubflag=0&hiddenField=0&page=' + str(k) for k in range(1, 61728)]
45. pool = Pool(processes=multiprocessing.cpu_count())
46. pool.map(get_info, urls)
48. f.close()