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

时间：2021-07-27 19:15:32

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。

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

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()

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