scrapy 爬虫并把所有网址和所有图片对应起来写入到Excel中

标签：write   extra   img   row   for   process   mpi   app   setting   

items.py 数据条目

import scrapy

class DangdangItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    title=scrapy.Field()
    link =scrapy.Field()
    comment=scrapy.Field()
    pic_addr=scrapy.Field()


dd.py 数据分析

# -*- coding: utf-8 -*-
import scrapy
import re
from dangdang.items import  DangdangItem
from scrapy.http import Request

class DdSpider(scrapy.Spider):
    name = ‘dd‘
    allowed_domains = [‘dangdang.com‘]
    start_urls = [‘http://category.dangdang.com/pg1-cid4003844.html‘]

    def parse(self, response):
        item=DangdangItem()
        item[‘title‘]=response.xpath(‘//a[@name="itemlist-title"]/@title‘).extract()
        item[‘link‘]=response.xpath(‘//a[@name="itemlist-title"]/@href‘).extract()
        item[‘comment‘] = response.xpath(‘//a[@name="itemlist-review"]/text()‘).extract()
        item[‘pic_addr‘] = response.xpath(‘//a/img/@data-original‘).extract()
        lst=item[‘pic_addr‘]
        lnk=item[‘link‘]
        #相同图片地址整理到一起
        i = 0
        lst1 = []
        while i < len(lst):
            pat = ‘http://.*?/.*?/.*?/([0-9]{5})‘
            data = re.compile(pat).findall(lst[i])
            k = 0
            j = 0
            ll = []
            while j < len(lst):
                data1 = re.compile(pat).findall(lst[j])
                if (data == data1):
                    ll.append(lst[j])

                    k += 1
                    if k > 1:
                        lst.pop(j)
                        j = j - 1
                j += 1
            lst1.append(ll)
            i += 1
        #网页链接和图片链接序号相匹配，为写入数据进行整理
        lst = []
        for m in range(0, len(lnk)):
            pat1 = ‘http://.*?/([0-9]{5})‘
            d = re.compile(pat1).findall(lnk[m])

            for n in range(0, len(lst1)):
                pat2 = ‘http://.*?/.*?/.*?/([0-9]{5})‘
                d1 = re.compile(pat2).findall(lst1[n][0])

                if d == d1:
                    lst.append(lst1[n])
                    break
        item[‘pic_addr‘]=lst

        yield item
        for page in range(2,81):
            url=‘http://category.dangdang.com/pg‘+str(page)+‘-cid4003844.html‘
            yield Request(url,callback=self.parse)

创建Excel表

import xlwt
book = xlwt.Workbook(encoding="utf-8")
sht = book.add_sheet("publisher", cell_overwrite_ok=True)
sht.write(0,0,u‘序号‘)
sht.write(0,1,u‘标题‘)
sht.write(0,2,u‘链接‘)
sht.write(0,3,u‘评论‘)
sht.write(0,4,u‘图片链接1‘)
sht.write(0,5,u‘图片链接2‘)
sht.write(0,6,u‘图片链接3‘)
sht.write(0,7,u‘图片链接4‘)
sht.write(0,8,u‘图片链接5‘)
book.save("d:\\data\\dangdang\\dangdang.xls")

pipelines.py 数据写入

# -*- coding: utf-8 -*-

# Define your item pipelines here
#
# Don‘t forget to add your pipeline to the ITEM_PIPELINES setting
# See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html
import xlrd
from xlutils.copy import copy


class DangdangPipeline(object):
    def process_item(self, item,spider):
        rb = xlrd.open_workbook(‘d:\\data\\dangdang\\dangdang.xls‘)
        sht = rb.sheets()[0]
        nrows = sht.nrows
        # ncols = sht.ncols+1
        wb = copy(rb)
        ws = wb.get_sheet(0)
        for i in range(0,len(item[‘title‘])):
            title=item[‘title‘][i]
            link=item[‘link‘][i]
            comment=item[‘comment‘][i]
            pic_addr = item[‘pic_addr‘][i]
            try:
                ws.write(nrows,0,nrows)
                ws.write(nrows, 1, title)
                ws.write(nrows, 2, link)
                ws.write(nrows, 3, comment)
                for j in range(0,len(pic_addr)):
                    ws.write(nrows,4+j,pic_addr[j])
                nrows += 1
            except Exception as err:
                print(err)
        wb.save(‘d:\\data\\dangdang\\dangdang.xls‘)
        return item

scrapy 爬虫并把所有网址和所有图片对应起来写入到Excel中

标签：write   extra   img   row   for   process   mpi   app   setting   

原文地址：http://www.cnblogs.com/xiesongyou/p/7899104.html