API例子：用Python驱动Firefox采集网页数据 | 一起学习Python网络爬虫

1，引言本次测试的环境是：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：...

1，引言

• 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'

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

2016-11-04：V1.0，首次发布