python爬虫用scrpy管道爬取二手房信息代码
时间: 2024-10-01 20:03:07 浏览: 39
Python爬虫实例——scrapy框架爬取拉勾网招聘信息
在Python中,Scrapy是一个强大的网络爬虫框架,可以帮助我们高效地抓取网页数据,包括二手房信息。Scrapy Pipeline是其核心特性之一,用于处理爬取的数据。下面是一个简单的例子,展示如何设置Scrapy Pipeline来抓取二手房信息:
```python
# 导入必要的模块
import scrapy
from scrapy.pipelines.images import ImagesPipeline
from scrapy.item import Item, Field
from scrapy.exceptions import DropItem
class HouseInfoItem(scrapy.Item):
# 定义需要保存的信息字段
title = Field()
price = Field()
address = Field()
image_urls = Field(output_field=Field(list()))
class RealEstateSpider(scrapy.Spider):
name = 'realestatespider'
start_urls = ['https://example.com/second-hand-homes'] # 需要爬取的网站URL
def parse(self, response):
# 解析每个二手房页面并获取信息
for house in response.css('div.house-item'):
item = HouseInfoItem()
item['title'] = house.css('h2.title::text').get()
item['price'] = house.css('.price::text').get()
item['address'] = house.css('.address::text').get()
# 使用ImagesPipeline处理图片链接
images = house.css('img::attr(src)').getall()
if images:
item['image_urls'] = images
yield item
# 创建自定义管道
class ImageDownloadPipeline(ImagesPipeline):
def get_media_requests(self, item, info):
if 'image_urls' in item:
return [Request(url) for url in item['image_urls']]
def file_path(self, request, response=None, info=None):
# 自定义图片文件名,这里仅作示例
image_guid = request.url.split('/')[-1]
return f'static/images/{image_guid}'
# 设置pipeline
settings = {
'ITEM_PIPELINES': {'your_project.pipelines.ImageDownloadPipeline': 300},
}
# 运行爬虫
if __name__ == "__main__":
from scrapy.crawler import CrawlerProcess
process = CrawlerProcess(settings)
process.crawl<RealEstateSpider)
process.start() # the script will block here until the crawling is finished
```
在这个例子中,我们首先创建了一个`HouseInfoItem`模型来存储房源信息,包括标题、价格、地址以及可能的图片链接。然后在`RealEstateSpider`中解析HTML,提取信息,并通过`ImageDownloadPipeline`下载图片。最后,我们在`settings.py`中配置了管道。
请注意,实际操作时你需要根据目标网站的具体结构调整CSS选择器,并确保有合法的权限访问网站内容。
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