scrapy爬取美女图片

使用scrapy爬取整个网站的图片数据。并且使用 CrawlerProcess 启动。 1 # -*- coding: utf-8 -* 2 import scrapy 3 import requests

 4 from bs4 import BeautifulSoup
 5 
 6 from meinr.items import MeinrItem
 7 
 8 
 9 class Meinr1Spider(scrapy.Spider):
10     name = 'meinr1'
11     # allowed_domains = ['www.baidu.com']
12     # start_urls = ['http://m.tupianzj.com/meinv/xiezhen/']
13     headers = {
14     'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36',
15 }
16     def num(self,url,headers): #获取网页每个分类的页数和URL格式
17         html = requests.get(url=url,headers=headers)
18         if html.status_code != 200:
19             return '',''
20         soup = BeautifulSoup(html.text,'html.parser')
21         nums = soup.select('#pageNum li')[3]
22         nums = nums.select('a')[0].attrs.get('href')
23         num = str(nums[:-5]).split('_')[-1]
24         papa = str(nums[:-5]).split('_')[:-1]
25         papa = '_'.join(papa)+'_'
26         return int(num),papa
27 
28 
29     def start_requests(self):
　　　　　　#这是网站的所有分类
30         urls = ['http://m.tupianzj.com/meinv/xiezhen/','http://m.tupianzj.com/meinv/xinggan/','http://m.tupianzj.com/meinv/guzhuang/','http://m.tupianzj.com/meinv/siwa/','http://m.tupianzj.com/meinv/chemo/','http://m.tupianzj.com/meinv/qipao/','http://m.tupianzj.com/meinv/mm/']
31         num = 0
32         for url in urls:
33             num,papa = self.num(url,self.headers)
34             for i in range(1,num):
35                 if i != 1:
36                     urlzz = url + papa + str(i) + '.html' #拼装每页URL
37                 else:
38                     urlzz = url
39                 yield scrapy.Request(url=urlzz,headers=self.headers,callback=self.parse)
40     def parse(self, response):
41         # print(response.body)
42         htmllist = response.xpath('//div[@class="IndexList"]/ul[@class="IndexListult"]/li')#获取每页的图集URL和title
43         # print(htmllist)
44         for html in htmllist:
45             url = html.xpath('./a/@href').extract()
46             title = html.xpath('./a/span[1]/text()').extract()
47             # print(url)
48             # print(title)
49             yield scrapy.Request(url=url[0],meta={
50                         'url':url[0],
51                         'title':title[0]},
52                         headers=self.headers,
53                         callback=self.page
54              )
55     def page(self,response):
56         is_it = response.xpath('//div[@class="m-article"]/h1/text()').extract()
57         if is_it:
58             is_it = is_it[0].strip()
59             num = int(is_it[-4])
60             a = 0
61             for i in range(1,int(num)):
62                 a += 1
63                 url = str(response.url)[:-5] + '_' + str(i) + '.html' #拼装图集内的URL分页
64                 yield scrapy.Request(url=url, headers=self.headers, callback=self.download, meta={
65                     'url': response.meta.get('url'),
66                     'title': response.meta.get('title'),
67                     'num':a
68 
69                 },dont_filter=True） #使用了dont_filter取消去重是因为我们需要进入第一页获取总页数
70 
71     def download(self,response):
72         img = response.xpath("//img[@id='bigImg']/@src").extract() #获取每个页面里的img
73         if img:
74             time = MeinrItem()
75             time['img'] = img[0]
76             time['title'] = response.meta.get('title')
77             time['num'] = response.meta.get('num')
78             yield time

上面的是spider文件

import scrapy


class MeinrItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    title = scrapy.Field()
    img = scrapy.Field()
    num = scrapy.Field()
    pass

上面的是item文件

 1 import os
 2 import requests
 3 
 4 class MeinrPipeline(object):
 5     def open_spider(self,spider):#打开spider时启动。获取下载地址
 6         self.path = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) + os.sep + 'download'
 7         # print(self.path)
 8     def process_item(self, item, spider):
 9         title = item['title']
10         img = item['img']
11         num = item['num']
12         path = self.path + os.sep + title #将图集的title设置为每个图集的文件夹的名字
13         if not os.path.exists(path): #没有则创建
14             os.makedirs(path)
15         html = requests.get(url=img,headers=spider.headers).content
16         path = path + os.sep + str(num) + '.jpg' #这是每个图集内的图片是第几页
17         with open(path,'wb')as f:
18             f.write(html)
19         return item

这上面是管道文件

1 import datetime,os
2 time = datetime.datetime.now().strftime('%Y_%m_%H_%M_%S')
3 LOG_FILE = 'logs'+ os.sep +str(time) + '_' + "meinr.log"
4 LOG_LEVEL = "INFO"

这是在setting里面的，设置的日志信息和保存的位置以及消息的级别

 1 # -*- coding: utf-8 -*-
 2 import sys,datetime
 3 import os
 4 
 5 from meinr.spiders.meinr1 import Meinr1Spider
 6 from scrapy.crawler import CrawlerProcess
 7 from scrapy.utils.project import get_project_settings
 8 
 9 
10 process = CrawlerProcess(get_project_settings()) #这里获取spider里面的setting
11 process.crawl(Meinr1Spider) #使用crawl启动Meinr1Spider爬虫
12 process.start() #开始运行