Scrapy框架下载一个意大利网站所有植物图片并重命名归科

先上网址：http://www.plantarium.ru/page/samples/taxon/41302.html  一个意大利的植物网站。

刚刚搭建完了Scrapy框架，于是打算拿这个网站来练练手。

1.首先scrapy startproject plant 建立一个名为plant的项目

2.然后明确自己需要提取的内容：图片的网址，图片的科，图片所示植物的名字

所以修改items.py文件：

from scrapy.item import Item,Field

class PlantItem(Item):
    picture_name=Field()
    picture_url=Field()
    picture_family=Field()
    
 
  
 
  
3.核心内容当然是蜘蛛本身，在spiders文件夹下新建文件plant_spider.py:
 
  
 
  
# -*- coding:utf-8 -*-
from scrapy.spiders import Spider  
from plant.items import PlantItem
from scrapy.selector import Selector
from scrapy.http import Request  
import re
import os
import sys
import time
import requests
reload(sys)
sys.setdefaultencoding('utf-8')  
  
class PlantSpider(Spider):
    name = "plant"  
    start_urls = [  
        "http://dryades.units.it/euganei/index.php?procedure=list"  
    ]
    
    def parse(self, response):
        sel=Selector(response)
        sites=sel.xpath('//tr').extract()
        sites.pop()
        sites.pop()
        for site in sites:
            image_url='http://dryades.units.it/euganei/'+site.split('href="')[1].split('">')[0].replace('amp;','')
            open('url_content.txt', 'a').write(image_url+'\n')
            yield Request(image_url,callback=self.parse_item)
            
    def parse_item(self,response):
        path='D:\\Italy_Plant\\'
        self.create_folder(path)
        sel=Selector(response)
        images=sel.xpath('//a[contains(@href,".jpg")]/@href').extract()
        for image in images:
            item=PlantItem()
            item['picture_url']=image
            item['picture_name']=sel.xpath('//title/text()').extract()[0].split('-')[0].replace('.','').strip()
            item['picture_family']=sel.xpath('//td/b[contains(text(),"ACEAE")]/text()').extract()[0].split(' ')[0].capitalize()
            open('image_url.txt', 'a').write(item['picture_url']+'★'+item['picture_name']+'★'+item['picture_family']+'\n')
            self.create_folder(path+item['picture_family'])
            self.create_folder(path+item['picture_family']+'\\'+item['picture_name'])
            self.download_image(item['picture_url'],path+item['picture_family']+'\\'+item['picture_name']+'\\'+item['picture_url'].split('/')[-1])
            yield item

    def create_folder(self,path):
        if not os.path.exists(path):
            os.mkdir(path)

    def download_image(self,imageurl,imagename):
        i=0
        p=True
        while p and i<=10:
            try:
                data=requests.get(imageurl,timeout=20).content
                with open(imagename,'wb') as f:
                    f.write(data)
                p=False
            except:
                i+=1
                print 'save picture wrong,please wait 2 seconds'
                time.sleep(2)
 
  
 4.设置管道，处理保存爬去的信息。所以修改pipelines.py. 
  
 
  
 
  
import json
import codecs

class PlantPipeline(object):
    def __init__(self):
        self.file=codecs.open('italy_data.json',mode='wb',encoding='utf-8')
        
    def process_item(self, item, spider):
        line = json.dumps(dict(item)) + '\n'  
        self.file.write(line.decode("unicode_escape"))
        return item

    def close_spider(self,spider):
        print 'over'
 
  
 5.设置配置文件settings.py. 
  
 
  
 
  
BOT_NAME = 'plant'

SPIDER_MODULES = ['plant.spiders']
NEWSPIDER_MODULE = 'plant.spiders'
CONCURRENT_REQUESTS = 1

COOKIES_ENABLED=True

ITEM_PIPELINES={
    'plant.pipelines.PlantPipeline':300
}
 
  
 
  
6.最后scrapy crawl plant。（然而这三个字母在调试过程中可是打了上百遍才成功。。。）
 
  

 
  
优化：为了解决防止网站连接超时，添加重新请求：在setting.py中添加RETRY_ENABLED=True，RETRY_TIMES=10