Python Scrapy每页只有两个结果

首先非常感谢你的帮助

我不知道为什么我每页只能得到两个结果。你能帮帮我吗？代码如下：

# -*- coding: utf-8 -*-
import scrapy
from scrapy.spiders import CrawlSpider, Rule
from scrapy.linkextractors import LinkExtractor
from mercado.items import MercadoItem


class MercadoSpider(CrawlSpider):
    name = 'mercado'
    item_count = 0
    allowed_domain = ['https://www.amazon.es']
    start_urls = ['https://www.amazon.es/s/ref=sr_pg_2rh=n%3A1951051031%2Cn%3A2424922031%2Ck%3Afe bi&page=1&keywords=febi&ie=UTF8&qid=1 535314254']

rules = {

    Rule(LinkExtractor(allow =(), restrict_xpaths = ('//*[h2]')),
                    callback = 'parse_item', follow = False)
}

def start_requests(self):
    yield scrapy.Request("https://www.amazon.es/s/ref=sr_pg_2?rh=n%3A1951051031%2Cn%3A2424922031%2Ck%3Afebi&page=1&keywords=febi&ie=UTF8&qid=1535314254",self.parse_item)

    for i in range(2,400):
        yield scrapy.Request("https://www.amazon.es/s/ref=sr_pg_2?rh=n%3A1951051031%2Cn%3A2424922031%2Ck%3Afebi&page="+str(i)+"&keywords=febi&ie=UTF8&qid=1535314254",self.parse_item)


def parse_item(self, response):

    for mercado in response.xpath('//*[h2]'):
        ml_item = MercadoItem()

        ml_item['articulo'] = response.xpath("@title").extract()[0]
        ml_item['precio'] = response.xpath("@href").extract()[0]

        yield ml_item        

# -*- coding: utf-8 -*-
import scrapy
from scrapy.spiders import CrawlSpider
import urllib
from mercado.items import MercadoItem


class MercadoSpider(CrawlSpider):
name = 'mercado'
item_count = 0
allowed_domain = ['https://www.amazon.es']
start_urls = ['https://www.amazon.es/s/ref=sr_pg_2rh=n%3A1951051031%2Cn%3A2424922031%2Ck%3Afebi&page=1&keywords=febi&ie=UTF8&qid=1 535314254']



def start_requests(self):
    yield scrapy.Request("https://www.amazon.es/s/ref=sr_pg_2?rh=n%3A1951051031%2Cn%3A2424922031%2Ck%3Afebi&page=1&keywords=febi&ie=UTF8&qid=1535314254",self.parse_item)

    for i in range(2,400):
        yield scrapy.Request("https://www.amazon.es/s/ref=sr_pg_2?rh=n%3A1951051031%2Cn%3A2424922031%2Ck%3Afebi&page="+str(i)+"&keywords=febi&ie=UTF8&qid=1535314254",self.parse_item)

def parse_item(self, response):


        namelist = response.xpath('//a[@class="a-link-normal s-access-detail-page  s-color-twister-title-link a-text-normal"]/@title').extract()
        #precio = response.xpath('//a/span[@class="a-size-base a-color-price s-price a-text-bold"]').extract()
        listlength = len(namelist)

        for i in range(0,listlength):
           ml_item = MercadoItem()
           ml_item['articulo'] = response.xpath('//a[@class="a-link-normal s-access-detail-page  s-color-twister-title-link a-text-normal"]/@title').extract()
           #ml_item['precio'] = response.xpath('//a/span[@class="a-size-base a-color-price s-price a-text-bold"]').extract()

        yield ml_item   

---

您需要相对于

mercado

元素进行搜索：

def parse_item(self, response):

    for mercado in response.xpath('//*[h2]'):
        ml_item = MercadoItem()

        ml_item['articulo'] = mercado.xpath("@title").extract()[0]
        ml_item['precio'] = mercado.xpath("@href").extract()[0]

        yield ml_item   

---

我已经能够导入两个以上的结果。 看看代码：

# -*- coding: utf-8 -*-
import scrapy
from scrapy.spiders import CrawlSpider, Rule
from scrapy.linkextractors import LinkExtractor
from mercado.items import MercadoItem


class MercadoSpider(CrawlSpider):
    name = 'mercado'
    item_count = 0
    allowed_domain = ['https://www.amazon.es']
    start_urls = ['https://www.amazon.es/s/ref=sr_pg_2rh=n%3A1951051031%2Cn%3A2424922031%2Ck%3Afe bi&page=1&keywords=febi&ie=UTF8&qid=1 535314254']

rules = {

    Rule(LinkExtractor(allow =(), restrict_xpaths = ('//*[h2]')),
                    callback = 'parse_item', follow = False)
}

def start_requests(self):
    yield scrapy.Request("https://www.amazon.es/s/ref=sr_pg_2?rh=n%3A1951051031%2Cn%3A2424922031%2Ck%3Afebi&page=1&keywords=febi&ie=UTF8&qid=1535314254",self.parse_item)

    for i in range(2,400):
        yield scrapy.Request("https://www.amazon.es/s/ref=sr_pg_2?rh=n%3A1951051031%2Cn%3A2424922031%2Ck%3Afebi&page="+str(i)+"&keywords=febi&ie=UTF8&qid=1535314254",self.parse_item)


def parse_item(self, response):

    for mercado in response.xpath('//*[h2]'):
        ml_item = MercadoItem()

        ml_item['articulo'] = response.xpath("@title").extract()[0]
        ml_item['precio'] = response.xpath("@href").extract()[0]

        yield ml_item        

# -*- coding: utf-8 -*-
import scrapy
from scrapy.spiders import CrawlSpider
import urllib
from mercado.items import MercadoItem


class MercadoSpider(CrawlSpider):
name = 'mercado'
item_count = 0
allowed_domain = ['https://www.amazon.es']
start_urls = ['https://www.amazon.es/s/ref=sr_pg_2rh=n%3A1951051031%2Cn%3A2424922031%2Ck%3Afebi&page=1&keywords=febi&ie=UTF8&qid=1 535314254']



def start_requests(self):
    yield scrapy.Request("https://www.amazon.es/s/ref=sr_pg_2?rh=n%3A1951051031%2Cn%3A2424922031%2Ck%3Afebi&page=1&keywords=febi&ie=UTF8&qid=1535314254",self.parse_item)

    for i in range(2,400):
        yield scrapy.Request("https://www.amazon.es/s/ref=sr_pg_2?rh=n%3A1951051031%2Cn%3A2424922031%2Ck%3Afebi&page="+str(i)+"&keywords=febi&ie=UTF8&qid=1535314254",self.parse_item)

def parse_item(self, response):


        namelist = response.xpath('//a[@class="a-link-normal s-access-detail-page  s-color-twister-title-link a-text-normal"]/@title').extract()
        #precio = response.xpath('//a/span[@class="a-size-base a-color-price s-price a-text-bold"]').extract()
        listlength = len(namelist)

        for i in range(0,listlength):
           ml_item = MercadoItem()
           ml_item['articulo'] = response.xpath('//a[@class="a-link-normal s-access-detail-page  s-color-twister-title-link a-text-normal"]/@title').extract()
           #ml_item['precio'] = response.xpath('//a/span[@class="a-size-base a-color-price s-price a-text-bold"]').extract()

        yield ml_item   

现在，在每一行csv中，我都会获得每页的所有结果。我现在的问题是把每件商品的价格加起来。我在这里被绊倒了。我如何添加它