[英]loop through multiple URLs to scrape from a CSV file in Scrapy is not working
[英]How to loop through multiple URLs to scrape from a CSV file in Scrapy?
我从阿里巴巴网站抓取数据的代码:
import scrapy
class IndiamartSpider(scrapy.Spider):
name = 'alibot'
allowed_domains = ['alibaba.com']
start_urls = ['https://www.alibaba.com/showroom/acrylic-wine-box_4.html']
def parse(self, response):
Title = response.xpath('//*[@class="title three-line"]/a/@title').extract()
Price = response.xpath('//div[@class="price"]/b/text()').extract()
Min_order = response.xpath('//div[@class="min-order"]/b/text()').extract()
Response_rate = response.xpath('//i[@class="ui2-icon ui2-icon-skip"]/text()').extract()
for item in zip(Title,Price,Min_order,Response_rate):
scraped_info = {
'Title':item[0],
'Price': item[1],
'Min_order':item[2],
'Response_rate':item[3]
}
yield scraped_info
注意起始 url,它只抓取给定的 URL,但我希望此代码抓取我的 csv 文件中存在的所有 url。 我的 csv 文件包含大量 URL。 data.csv 文件示例::
'https://www.alibaba.com/showroom/shock-absorber.html',
'https://www.alibaba.com/showroom/shock-wheel.html',
'https://www.alibaba.com/showroom/shoes-fastener.html',
'https://www.alibaba.com/showroom/shoes-women.html',
'https://www.alibaba.com/showroom/shoes.html',
'https://www.alibaba.com/showroom/shoulder-long-strip-bag.html',
'https://www.alibaba.com/showroom/shower-hair-band.html',
...........
我如何一次导入代码中的所有 csv 文件链接?
要正确循环文件而不将所有文件加载到内存中,您应该使用生成器,因为 python/scrapy 中的文件对象和 start_requests 方法都是生成器:
class MySpider(Spider):
name = 'csv'
def start_requests(self):
with open('file.csv') as f:
for line in f:
if not line.strip():
continue
yield Request(line)
进一步解释:Scrapy 引擎使用start_requests
生成请求。 它将继续生成请求,直到并发请求限制已满(设置如CONCURRENT_REQUESTS
)。
还值得注意的是,默认情况下,scrapy 爬行深度优先 - 较新的请求优先,因此 start_requests 循环将最后完成。
你快到了。 唯一的变化是在start_urls
,您希望它成为“*.csv 文件中的所有 url”。 以下代码可轻松实现该更改。
with open('data.csv') as file:
start_urls = [line.strip() for line in file]
让我们假设您已经以数据帧的形式存储了 url 列表,并且您想要遍历数据帧中存在的每个 URL。 下面给出了我的方法,它对我有用。
class IndiamartSpider(scrapy.Spider):
name = 'alibot'
#allowed_domains = ['alibaba.com']
#start_urls = ['https://www.alibaba.com/showroom/acrylic-wine-box_4.html']
def start_requests(self):
df = pd.read_csv('fileContainingUrls.csv')
#Here fileContainingUrls.csv is a csv file which has a column named as 'URLS'
# contains all the urls which you want to loop over.
urlList = df['URLS'].to_list()
for i in urlList:
yield scrapy.Request(url = i, callback=self.parse)
def parse(self, response):
Title = response.xpath('//*[@class="title three-line"]/a/@title').extract()
Price = response.xpath('//div[@class="price"]/b/text()').extract()
Min_order = response.xpath('//div[@class="min-order"]/b/text()').extract()
for item in zip(Title,Price,Min_order,Response_rate):
scraped_info = {
'Title':item[0],
'Price': item[1],
'Min_order':item[2],
'Response_rate':item[3]
}
yield scraped_info
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