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'])