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

python36requestsbs4csvmultiprocessing">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。

在这里插入图片描述

2.使用requests库获取页面和使用bs4库来解析页面内容

html = requests.get(url, headers=headers)
selector = BeautifulSoup(html.text, 'lxml')
names = selector.select(
'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')
writers = selector.select(
'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')
sign1s = selector.select(
'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)')
sign2s = selector.select(
'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')
types = selector.select(
'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')
traductions = selector.select(
'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')
words = selector.select(
'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

head = ['title', 'author', 'sign1', 'sign2', 'type', 'traduction', 'words']
f = open('_06_qidian.csv', 'a+')
csv_writer = csv.writer(f)
csv_writer.writerow(head)
for info in range(len(names)):
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。

pool = Pool(processes=multiprocessing.cpu_count())
pool.map(get_info, urls)
pool.close()
pool.join()

5.完整代码

import requests
from bs4 import BeautifulSoup
import xlwt
from multiprocessing import Pool
import multiprocessing
import csv
def get_info(url):
print(url)
global i
html = requests.get(url, headers=headers)
selector = BeautifulSoup(html.text, 'lxml')
names = selector.select(
'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')
writers = selector.select(
'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')
sign1s = selector.select(
'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)')
sign2s = selector.select(
'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')
types = selector.select(
'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')
traductions = selector.select(
'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')
words = selector.select(
'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')
for info in range(len(names)):
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()))
if __name__ == '__main__':
head = ['title', 'author', 'sign1', 'sign2', 'type', 'traduction', 'words']
f = open('_06_qidian.csv', 'a+')
csv_writer = csv.writer(f)
csv_writer.writerow(head)
headers = {
'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.86 Safari/537.36',
}
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)]
pool = Pool(processes=multiprocessing.cpu_count())
pool.map(get_info, urls)
f.close()