我们在写普通脚本的时候，从一个网站拿到一个文件的下载url，然后下载，直接将数据写入文件或者保存下来，但是这个需要我们自己一点一点的写出来，而且反复利用率并不高，为了不重复造轮子，scrapy提供很流畅的下载文件方式，只需要随便写写便可用了。
mat.py文件
1 # -*- coding: utf-8 -*- 2 import scrapy 3 from scrapy.linkextractor import LinkExtractor 4 from weidashang.items import matplotlib 5 6 class MatSpider(scrapy.Spider): 7 name = "mat" 8 allowed_domains = ["matplotlib.org"] 9 start_urls = [‘https://matplotlib.org/examples‘] 10 11 def parse(self, response):
#抓取每个脚本文件的访问页面，拿到后下载 12 link = LinkExtractor(restrict_css=‘div.toctree-wrapper.compound li.toctree-l2‘) 13 for link in link.extract_links(response): 14 yield scrapy.Request(url=link.url,callback=self.example) 15 16 def example(self,response):
#进入每个脚本的页面，抓取源码文件按钮，并和base_url结合起来形成一个完整的url 17 href = response.css(‘a.reference.external::attr(href)‘).extract_first() 18 url = response.urljoin(href) 19 example = matplotlib() 20 example[‘file_urls‘] = [url] 21 return example
pipelines.py
1 class MyFilePlipeline(FilesPipeline): 2 def file_path(self, request, response=None, info=None): 3 path = urlparse(request.url).path 4 return join(basename(dirname(path)),basename(path))
settings.py
1 ITEM_PIPELINES = { 2 ‘weidashang.pipelines.MyFilePlipeline‘: 1, 3 } 4 FILES_STORE = ‘examples_src‘
items.py
class matplotlib(Item): file_urls = Field() files = Field()
run.py
1 from scrapy.cmdline import execute 2 execute([‘scrapy‘, ‘crawl‘, ‘mat‘,‘-o‘,‘example.json‘])
