45 lines
1.6 KiB
Python
45 lines
1.6 KiB
Python
import scrapy
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class PAPSpider(scrapy.Spider):
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name = "pap"
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baseurl = 'https://www.pap.fr'
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ads_css_sel = '.search-list-item-alt'
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url_css_sel = '.item-title::attr(href)'
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price_css_sel = '.item-price::text'
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infos_css_sel = '.item-tags' # Contains Rooms, bedrooms, area
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next_page_xpath = '//a[@id="pagination-next"]/@href'
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def start_requests(self):
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urls = [
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'https://www.pap.fr/annonce/vente-appartement-immeuble-maison-vienne-38200-g21767-jusqu-a-300000-euros',
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'https://www.pap.fr/annonce/vente-appartement-immeuble-maison-saint-etienne-42-g43641-jusqu-a-300000-euros'
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]
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for url in urls:
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yield scrapy.Request(url=url, callback=self.parse)
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def parse(self, response):
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ads = response.css(self.ads_css_sel)
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for ad in ads:
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infos = ad.css(self.infos_css_sel)
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url = ad.css(self.url_css_sel).get()
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if url[0] != '/': # If url starts with / : on website, else: advertisement
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break
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yield {
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'url': self.baseurl + url,
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'type': 'Unknown',
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'price': ad.css(self.price_css_sel).get(),
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'rooms': infos.xpath('./li[contains(., "pièces")]/text()').get(),
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'bedrooms': infos.xpath('./li[contains(., "chambres")]/text()').get(),
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'area': infos.xpath('./li[contains(small, "m")]/text()').get()
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}
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next_page = response.xpath(self.next_page_xpath).get()
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if next_page:
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yield response.follow(next_page, callback=self.parse)
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