1，引言
《Scrapy的架构初探》一文讲解了Scrapy的架构，本文就实际来安装运行一下Scrapy爬虫。本文以官网的tutorial作为例子，完整的代码可以在github上下载。
2，运行环境配置
- 本次测试的环境是：Windows10， Python3.4.3 32bit
- 安装Scrapy ： $ pip install Scrapy #实际安装时，由于服务器状态的不稳定，出现好几次中途退出的情况
3，编写运行第一个Scrapy爬虫
3.1. 生成一个新项目：tutorial
$ scrapy startproject tutorial
项目目录结构如下：
3.2. 定义要抓取的item
# -*- coding: utf-8 -*- # Define here the models for your scraped items
#
# See documentation in:
# http://doc.scrapy.org/en/latest/topics/items.html import scrapy class DmozItem(scrapy.Item):
title = scrapy.Field()
link = scrapy.Field()
desc = scrapy.Field()
3.3. 定义Spider
import scrapy
from tutorial.items import DmozItem class DmozSpider(scrapy.Spider):
name = "dmoz"
allowed_domains = ["dmoz.org"]
start_urls = [
"http://www.dmoz.org/Computers/Programming/Languages/Python/Books/",
"http://www.dmoz.org/Computers/Programming/Languages/Python/Resources/"
] def parse(self, response):
for sel in response.xpath('//ul/li'):
item = DmozItem()
item['title'] = sel.xpath('a/text()').extract()
item['link'] = sel.xpath('a/@href').extract()
item['desc'] = sel.xpath('text()').extract()
yield item
3.4. 运行
$ scrapy crawl dmoz -o item.json
1) 结果报错：
A) ImportError: cannot import name '_win32stdio'
B) ImportError: No module named 'win32api'
2) 查错过程：查看官方的FAQ和*上的信息，原来是scrapy在python3上测试还不充分，还有小问题。
3) 解决过程：
A) 需要手工去下载twisted/internet下的 _win32stdio 和 _pollingfile，存放到python目录的lib\sitepackages\twisted\internet下
B) 下载并安装pywin32
再次运行，成功！在控制台上可以看到scrapy的输出信息，待运行完成退出后，到项目目录打开结果文件items.json， 可以看到里面以json格式存储的爬取结果
[
{"title": [" About "], "desc": [" ", " "], "link": ["/docs/en/about.html"]},
{"title": [" Become an Editor "], "desc": [" ", " "], "link": ["/docs/en/help/become.html"]},
{"title": [" Suggest a Site "], "desc": [" ", " "], "link": ["/docs/en/add.html"]},
{"title": [" Help "], "desc": [" ", " "], "link": ["/docs/en/help/helpmain.html"]},
{"title": [" Login "], "desc": [" ", " "], "link": ["/editors/"]},
{"title": [], "desc": [" ", " Share via Facebook "], "link": []},
{"title": [], "desc": [" ", " Share via Twitter "], "link": []},
{"title": [], "desc": [" ", " Share via LinkedIn "], "link": []},
{"title": [], "desc": [" ", " Share via e-Mail "], "link": []},
{"title": [], "desc": [" ", " "], "link": []},
{"title": [], "desc": [" ", " "], "link": []},
{"title": [" About "], "desc": [" ", " "], "link": ["/docs/en/about.html"]},
{"title": [" Become an Editor "], "desc": [" ", " "], "link": ["/docs/en/help/become.html"]},
{"title": [" Suggest a Site "], "desc": [" ", " "], "link": ["/docs/en/add.html"]},
{"title": [" Help "], "desc": [" ", " "], "link": ["/docs/en/help/helpmain.html"]},
{"title": [" Login "], "desc": [" ", " "], "link": ["/editors/"]},
{"title": [], "desc": [" ", " Share via Facebook "], "link": []},
{"title": [], "desc": [" ", " Share via Twitter "], "link": []},
{"title": [], "desc": [" ", " Share via LinkedIn "], "link": []},
{"title": [], "desc": [" ", " Share via e-Mail "], "link": []},
{"title": [], "desc": [" ", " "], "link": []},
{"title": [], "desc": [" ", " "], "link": []}
]
第一次运行scrapy的测试成功
4，接下来的工作
接下来，我们将使用GooSeeker API来实现网络爬虫，省掉对每个item人工去生成和测试xpath的工作量。目前有2个计划：
- 在gsExtractor中封装一个方法：从xslt内容中自动提取每个item的xpath
- 从gsExtractor的提取结果中自动提取每个item的结果
具体选择哪个方案，将在接下来的实验中确定，并发布到gsExtractor新版本中
5，文档修改历史
2016-06-17：V1.0，首次发布