1，Scrapy安装
windows上，可以试用pycharm安装，但是，无法通过cmd执行scrapy命令。
于是，通过查询资料，通过cmd模式，先卸载scrapy，再安装一次。或者可以直接安装 （可能存在两个的scrapy），只要能执行scrapy命令即可。
scrapy安装完成后，在windows cmd模式里输入scrapy，命令无法识别
http://blog.csdn.net/u012263493/article/details/38071143
2，Scrapy入门demo
第一步，默认的Scrapy项目结构
scrapy startproject myproject
类似下面的项目结构：
tutorial/
scrapy.cfg
tutorial/
__init__.py
items.py
pipelines.py
settings.py
spiders/
__init__.py
...
第二步，定义要抓取的数据
import scrapy
class DmozItem(scrapy.Item):
title = scrapy.Field()
link = scrapy.Field()
desc = scrapy.Field()
第三步，使用项目命令genspider创建Spider
scrapy genspider xxt xxt.cn
$ scrapy genspider -l
Available templates:
basic
crawl
csvfeed
xmlfeed
$ scrapy genspider -d basic
import scrapy
class $classname(scrapy.Spider):
name = "$name"
allowed_domains = ["$domain"]
start_urls = (
'http://www.$domain/',
)
def parse(self, response):
pass
$ scrapy genspider -t basic example example.com
Created spider 'example' using template 'basic' in module:
mybot.spiders.example
第四步，编写提取item数据的Spider
参考下面的代码
import scrapy
class DmozSpider(scrapy.spider.Spider):
name = "dmoz" #唯一标识，启动spider时即指定该名称
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):
filename = response.url.split("/")[-2]
with open(filename, 'wb') as f:
f.write(response.body)
第五步，启动爬取
scrapy crawl dmoz
可以看到scrapy的进程日志如下：
E:\python\tutorial>scrapy crawl dmoz -o items.json
2017-06-29 21:18:30 [scrapy.utils.log] INFO: Scrapy 1.4.0 started (bot: tutorial)
2017-06-29 21:18:30 [scrapy.utils.log] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'tutorial.spiders', 'FEED_URI': 'items.json', 'SPIDER_MODULES': ['tutorial.spiders'], 'BOT_NAME': 'tutorial', 'ROBOTSTXT_OBEY': True, 'FEED_FORMAT': 'json'}
2017-06-29 21:18:30 [scrapy.middleware] INFO: Enabled extensions:
['scrapy.extensions.feedexport.FeedExporter',
'scrapy.extensions.logstats.LogStats',
'scrapy.extensions.telnet.TelnetConsole',
'scrapy.extensions.corestats.CoreStats']
2017-06-29 21:18:31 [scrapy.middleware] INFO: Enabled downloader middlewares:
['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware',
'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware',
'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware',
'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware',
'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware',
'scrapy.downloadermiddlewares.retry.RetryMiddleware',
'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware',
'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware',
'scrapy.downloadermiddlewares.redirect.RedirectMiddleware',
'scrapy.downloadermiddlewares.cookies.CookiesMiddleware',
'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware',
'scrapy.downloadermiddlewares.stats.DownloaderStats']
2017-06-29 21:18:31 [scrapy.middleware] INFO: Enabled spider middlewares:
['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware',
'scrapy.spidermiddlewares.offsite.OffsiteMiddleware',
'scrapy.spidermiddlewares.referer.RefererMiddleware',
'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware',
'scrapy.spidermiddlewares.depth.DepthMiddleware']
2017-06-29 21:18:31 [scrapy.middleware] INFO: Enabled item pipelines:
['tutorial.pipelines.TutorialPipeline', 'tutorial.pipelines.TutorialPipeline1']
2017-06-29 21:18:31 [scrapy.core.engine] INFO: Spider opened
2017-06-29 21:18:31 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min)
2017-06-29 21:18:31 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023
2017-06-29 21:18:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET http://data.caida.org/robots.txt> (referer: None)
2017-06-29 21:18:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET http://data.caida.org/datasets/dns/> (referer: None)
...
3，补充说明，功能升级
通过选择器提取数据，参考下面代码
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
保存数据
最简单存储爬取的数据的方式是使用 Feed exports:
scrapy crawl dmoz -o items.json
该命令将采用 JSON 格式对爬取的数据进行序列化，生成 items.json 文件。
如果需要对爬取到的item做更多更为复杂的操作，您可以编写 Item Pipeline 。类似于我们在创建项目时对Item做的，用于您编写自己的 tutorial/pipelines.py 也被创建。不过如果您仅仅想要保存item，您不需要实现任何的pipeline。
编写pipelines.py，可以入库、写文件等等
首先，打开settings.py的设置
# Configure item pipelines
# See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {
'tutorial.pipelines.TutorialPipeline': 300,
'tutorial.pipelines.TutorialPipeline1': 500,
}
然后，编写pipelines.py
class TutorialPipeline(object):
def process_item(self, item, spider):
print "TutorialPipeline00000000000", item
return item
class TutorialPipeline1(object):
def process_item(self, item, spider):
print "TutorialPipeline11111111111", item
return item
结论：scrapy根据settings.py的配置，先将item抛给高优先级（类后面的数值越小优先级越高）的pipelines类，如上例所示，先执行TutorialPipeline ，后执行TutorialPipeline1
递归爬取网站数据
首先，设置爬虫类的全局变量，保证allowed_domains和start_urls一致，否则，无法递归爬取
allowed_domains = ["caida.org"]
start_urls = [
# "http://data.caida.org/datasets/2013-asrank-data-supplement/",
"http://data.caida.org/datasets/dns/",
# "http://data.caida.org/datasets/2013-asrank-data-supplement/extra/"
]
然后，编写爬虫类的parse成员方法，在必要时候，需要通过yield返回scrapy.Request(response.url + next_url, callback=self.parse)
# 广度优先，递归爬取数据
def parse(self, response):
print '2222222222222222222222222222222',response,response.url
self.log('A response from %s just arrived!' % response.url)
for sel in response.xpath('/html/body/pre/a'):
yield scrapy.Request(response.url + next_url, callback=self.parse)
最后，经过测试，发现默认是广度优先。如果需要深度，应该可以配置。
参考网址：
【scrapy】学习Scrapy入门
http://www.jianshu.com/p/a8aad3bf4dc4
Spiders
http://scrapy-chs.readthedocs.io/zh_CN/0.24/topics/spiders.html
搜索引擎五：Scrapy抓取数据入库
http://blog.csdn.net/ns2250225/article/details/43966671
Python yield 使用浅析
https://www.ibm.com/developerworks/cn/opensource/os-cn-python-yield/
