解析多个URL和存储数据时的艰巨困难

时间:2018-08-29 04:58:38

标签: regex python-3.x scrapy

我使用Regex从多个URL的脚本标签中检索数据。我有一个csv文件('links.csv'),其中包含我需要抓取的所有网址。我设法读取了csv,并将所有网址存储在名为“ start_urls”的变量中。我的问题是我需要一种方法可以一次从“ start_urls”中读取URL,然后执行我的代码的下一部分。当我在终端中执行代码时,它返回2个错误:

1. for pvi_subtype_name,pathIndicator.depth_5,model_name in zip(source): ValueError: not enough values to unpack (expected 3, got 1)
2. source = response.xpath("//script[contains(., 'COUNTRY_SHOP_STATUS')]/text()").extract()[0] IndexError: list index out of range

以下是我存储在初始csv('links.csv')中的url的一些示例:

"https://www.samsung.com/uk/smartphones/galaxy-note8/"
"https://www.samsung.com/uk/smartphones/galaxy-s8/"
"https://www.samsung.com/uk/smartphones/galaxy-s9/"

这是我的代码:

import scrapy
import csv
import re

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

    def start_requests(self):
        with open('links.csv','r') as csvf:
            for url in csvf:
                yield scrapy.Request(url.strip())

    def parse(self, response):
        source = response.xpath("//script[contains(., 'COUNTRY_SHOP_STATUS')]/text()").extract()[0]
        def get_values(parameter, script):
            return re.findall('%s = "(.*)"' % parameter, script)[0]

        with open('baza.csv', 'w') as csvfile:
            fieldnames = ['Category', 'Type', 'SK']
            writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
            writer.writeheader()
            for pvi_subtype_name,pathIndicator.depth_5,model_name in zip(source):
                writer.writerow({'Category': get_values("pvi_subtype_name", source), 'Type': get_values("pathIndicator.depth_5", source), 'SK': get_values("model_name", source)})

1 个答案:

答案 0 :(得分:1)

S9的站点与S8的站点结构不同,因此总会出现错误,因为在S9中找不到COUNTRY_SHOP_STATUS。

直接使用csv-writer并不容易。您多次覆盖结果。因为您为每个产品打开了一个新的csv文件。如果您真的想那样做。在start_requests中打开csv文件,并在解析后追加。但是看看项目管道。 我用zip删除了循环,因为解析已经处于最低级别。

  import scrapy
  import csv
  import re

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

      def start_requests(self):
          with open('so_52069753.csv','r') as csvf:
              urlreader = csv.reader(csvf, delimiter=',',quotechar='"')
              for url in urlreader:
                  if url[0]=="y":
                      yield scrapy.Request(url[1])
          with open('so_52069753_out.csv', 'w') as csvfile:
                  fieldnames = ['Category', 'Type', 'SK']
                  writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
                  writer.writeheader()

      def parse(self, response):
          def get_values(parameter, script):
              return re.findall('%s = "(.*)"' % parameter, script)[0]
          source_arr = response.xpath("//script[contains(., 'COUNTRY_SHOP_STATUS')]/text()").extract()
          if source_arr:
              source = source_arr[0]
              #yield ({'Category': get_values("pvi_subtype_name", source), 'Type': get_values("pathIndicator.depth_5", source), 'SK': get_values("model_name", source)})
              with open('so_52069753_out.csv', 'a') as csvfile:
                  fieldnames = ['Category', 'Type', 'SK']
                  writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
                  writer.writerow({'Category': get_values("pvi_subtype_name", source), 'Type': get_values("pathIndicator.depth_5", source), 'SK': get_values("model_name", source)})

我也更改了输入csv_file(so_52069753.csv):

y,https://www.samsung.com/uk/smartphones/galaxy-note8/
y,https://www.samsung.com/uk/smartphones/galaxy-s8/
y,https://www.samsung.com/uk/smartphones/galaxy-s9/

因此可以配置是否处理了url。