Question

我解析网站并且工作正常但我需要添加带有ID的新列以输出。该列保存在带有URL的csv中：

https://www.ceneo.pl/48523541, 1362
https://www.ceneo.pl/46374217, 2457

我的蜘蛛代码：

import scrapy
from ceneo.items import CeneoItem
import csv

class QuotesSpider(scrapy.Spider):
    name = "quotes" 

    def start_requests(self):
        start_urls = []
        f = open('urls.csv', 'r')
        for i in f:
            u = i.split(',')
            start_urls.append(u[0])
        for url in start_urls:
            yield scrapy.Request(url=url, callback=self.parse)

    def parse(self, response):
        all_prices = response.xpath('(//td[@class="cell-price"] /a/span/span/span[@class="value"]/text())[position() <= 10]').extract()
        all_sellers = response.xpath('(//tr/td/div/ul/li/a[@class="js_product-offer-link"]/text())[position()<=10]').extract()

        f = open('urls.csv', 'r')
        id = []
        for i in f:
            u = i.split(',')
            id.append(u[1])

        x = len(all_prices)     
        i = 0

        while (i < x):
            all_sellers[i] = all_sellers[i].replace('Opinie o ', '')
            i += 1

        for urlid, price, seller in zip(id, all_prices, all_sellers):
            yield {'urlid': urlid.strip(), 'price': price.strip(), 'seller': seller.strip()}

在结果中我得到错误的数据，因为（zip功能？）ID是交替进行的：

urlid,price,seller
1362,109,eMAG
1457,116,electro.pl
1362,597,apollo.pl
1457,597,allegro.pl

它应输出：

urlid,price,seller
1362,109,eMAG
1362,116,electro.pl
1457,597,apollo.pl
1457,597,allegro.pl

Answer 1

您可以在ID中获取start_requests并使用meta={'id': id_}分配给请求，稍后在parse中，您可以使用ID获取response.meta['id']。

这样，ID中就会有正确的parse。

我使用字符串data代替文件来创建工作示例。

#!/usr/bin/env python3

import scrapy

data = '''https://www.ceneo.pl/48523541, 1362
https://www.ceneo.pl/46374217, 2457'''

class QuotesSpider(scrapy.Spider):

    name = "quotes" 

    def start_requests(self):
        #f = open('urls.csv', 'r')

        f = data.split('\n')

        for row in f:
            url, id_ = row.split(',')

            url = url.strip()
            id_ = id_.strip()

            #print(url, id_)

            # use meta to assign value 
            yield scrapy.Request(url=url, callback=self.parse, meta={'id': id_})

    def parse(self, response):
        # use meta to receive value
        id_ = response.meta["id"]

        all_prices = response.xpath('(//td[@class="cell-price"] /a/span/span/span[@class="value"]/text())[position() <= 10]').extract()
        all_sellers = response.xpath('(//tr/td/div/ul/li/a[@class="js_product-offer-link"]/text())[position()<=10]').extract()

        all_sellers = [ item.replace('Opinie o ', '') for item in all_sellers ]

        for price, seller in zip(all_prices, all_sellers):
            yield {'urlid': id_, 'price': price.strip(), 'seller': seller.strip()}

# --- it runs without project and saves in `output.csv` ---

from scrapy.crawler import CrawlerProcess

c = CrawlerProcess({
    'USER_AGENT': 'Mozilla/5.0',
    'FEED_FORMAT': 'csv',
    'FEED_URI': 'output.csv', 
})
c.crawl(QuotesSpider)
c.start()

BTW：有标准函数id()所以我使用变量id_代替id

如何从csv的Scrapy输出添加新的colum？

1 个答案: