zoukankan      html  css  js  c++  java
  • Scrapy:python3下的第一次运行测试

    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FAQstackoverflow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libsitepackages wistedinternet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
  • 相关阅读:
    UVALive 6044(双连通分量的应用)
    hdu 3760(2次bfs求最短路)
    zoj 3370(二分+二分图染色)
    sgu 326(经典网络流构图)
    hdu 4291(矩阵+暴力求循环节)
    uva 11381(神奇的构图、最小费用最大流)
    hdu 4685(匹配+强连通分量)
    hdu 4496(并查集)
    hdu 4722(记忆化搜索)
    Linux安装Nginx使用负载均衡
  • 原文地址:https://www.cnblogs.com/gooseeker/p/5593939.html
Copyright © 2011-2022 走看看