一、简单配置，获取单个网页上的内容。
（1）创建scrapy项目
scrapy startproject getblog
（2）编辑 items.py
# -*- coding: utf-8 -*- # Define here the models for your scraped items # # See documentation in: # http://doc.scrapy.org/en/latest/topics/items.html from scrapy.item import Item, Field class BlogItem(Item): title = Field() desc = Field()
（3）在 spiders 文件夹下，创建 blog_spider.py
需要熟悉下xpath选择，感觉跟JQuery选择器差不多，但是不如JQuery选择器用着舒服（ w3school教程： http://www.w3school.com.cn/xpath/ ）。
# coding=utf-8 from scrapy.spider import Spider from getblog.items import BlogItem from scrapy.selector import Selector class BlogSpider(Spider): # 标识名称 name = 'blog' # 起始地址 start_urls = ['http://www.cnblogs.com/'] def parse(self, response): sel = Selector(response) # Xptah 选择器 # 选择所有含有class属性，值为‘post_item'的div 标签内容 # 下面的 第2个div 的 所有内容 sites = sel.xpath('//div[@class="post_item"]/div[2]') items = [] for site in sites: item = BlogItem() # 选取h3标签下，a标签下，的文字内容 ‘text()' item['title'] = site.xpath('h3/a/text()').extract() # 同上，p标签下的 文字内容 ‘text()' item['desc'] = site.xpath('p[@class="post_item_summary"]/text()').extract() items.append(item) return items
（4）运行，
scrapy crawl blog # 即可
（5）输出文件。
在 settings.py 中进行输出配置。
# 输出文件位置 FEED_URI = 'blog.xml' # 输出文件格式 可以为 json，xml，csv FEED_FORMAT = 'xml'
输出位置为项目根文件夹下。
二、基本的 -- scrapy.spider.Spider
（1）使用交互shell
dizzy@dizzy-pc:~$ scrapy shell "http://www.baidu.com/"
2014-08-21 04:09:11+0800 [scrapy] INFO: Scrapy 0.24.4 started (bot: scrapybot) 2014-08-21 04:09:11+0800 [scrapy] INFO: Optional features available: ssl, http11, django 2014-08-21 04:09:11+0800 [scrapy] INFO: Overridden settings: {'LOGSTATS_INTERVAL': 0} 2014-08-21 04:09:11+0800 [scrapy] INFO: Enabled extensions: TelnetConsole, CloseSpider, WebService, CoreStats, SpiderState 2014-08-21 04:09:11+0800 [scrapy] INFO: Enabled downloader middlewares: HttpAuthMiddleware, DownloadTimeoutMiddleware, UserAgentMiddleware, RetryMiddleware, DefaultHeadersMiddleware, MetaRefreshMiddleware, HttpCompressionMiddleware, RedirectMiddleware, CookiesMiddleware, ChunkedTransferMiddleware, DownloaderStats 2014-08-21 04:09:11+0800 [scrapy] INFO: Enabled spider middlewares: HttpErrorMiddleware, OffsiteMiddleware, RefererMiddleware, UrlLengthMiddleware, DepthMiddleware 2014-08-21 04:09:11+0800 [scrapy] INFO: Enabled item pipelines: 2014-08-21 04:09:11+0800 [scrapy] DEBUG: Telnet console listening on 127.0.0.1:6024 2014-08-21 04:09:11+0800 [scrapy] DEBUG: Web service listening on 127.0.0.1:6081 2014-08-21 04:09:11+0800 [default] INFO: Spider opened 2014-08-21 04:09:12+0800 [default] DEBUG: Crawled (200) <GET http://www.baidu.com/> (referer: None) [s] Available Scrapy objects: [s] crawler <scrapy.crawler.Crawler object at 0xa483cec> [s] item {} [s] request <GET http://www.baidu.com/> [s] response <200 http://www.baidu.com/> [s] settings <scrapy.settings.Settings object at 0xa0de78c> [s] spider <Spider 'default' at 0xa78086c> [s] Useful shortcuts: [s] shelp() Shell help (print this help) [s] fetch(req_or_url) Fetch request (or URL) and update local objects [s] view(response) View response in a browser >>> # response.body 返回的所有内容 # response.xpath('//ul/li') 可以测试所有的xpath内容 More important, if you type response.selector you will access a selector object you can use to query the response, and convenient shortcuts like response.xpath() and response.css() mapping to response.selector.xpath() and response.selector.css()
也就是可以很方便的，以交互的形式来查看xpath选择是否正确。之前是用FireFox的F12来选择的，但是并不能保证每次都能正确的选择出内容。
也可使用：
scrapy shell 'http://scrapy.org' --nolog # 参数 --nolog 没有日志
（2）示例
from scrapy import Spider from scrapy_test.items import DmozItem class DmozSpider(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）保存文件
可以使用，保存文件。格式可以 json，xml，csv
scrapy crawl -o 'a.json' -t 'json'
（4）使用模板创建spider
scrapy genspider baidu baidu.com # -*- coding: utf-8 -*- import scrapy class BaiduSpider(scrapy.Spider): name = "baidu" allowed_domains = ["baidu.com"] start_urls = ( 'http://www.baidu.com/', ) def parse(self, response): pass
这段先这样吧，记得之前5个的，现在只能想起4个来了. :-(
千万记得随手点下保存按钮。否则很是影响心情的(⊙o⊙)！
三、高级 -- scrapy.contrib.spiders.CrawlSpider
例子
#coding=utf-8 from scrapy.contrib.spiders import CrawlSpider, Rule from scrapy.contrib.linkextractors import LinkExtractor import scrapy class TestSpider(CrawlSpider): name = 'test' allowed_domains = ['example.com'] start_urls = ['http://www.example.com/'] rules = ( # 元组 Rule(LinkExtractor(allow=('category.php', ), deny=('subsection.php', ))), Rule(LinkExtractor(allow=('item.php', )), callback='pars_item'), ) def parse_item(self, response): self.log('item page : %s' % response.url) item = scrapy.Item() item['id'] = response.xpath('//td[@id="item_id"]/text()').re('ID：(d+)') item['name'] = response.xpath('//td[@id="item_name"]/text()').extract() item['description'] = response.xpath('//td[@id="item_description"]/text()').extract() return item
其他的还有 XMLFeedSpider
class scrapy.contrib.spiders.XMLFeedSpider class scrapy.contrib.spiders.CSVFeedSpider class scrapy.contrib.spiders.SitemapSpider
四、选择器
>>> from scrapy.selector import Selector >>> from scrapy.http import HtmlResponse
可以灵活的使用 .css() 和 .xpath() 来快速的选取目标数据
关于选择器，需要好好研究一下。xpath() 和 css() ，还要继续熟悉 正则.
当通过class来进行选择的时候，尽量使用 css() 来选择，然后再用 xpath() 来选择元素的熟悉
五、Item Pipeline
Typical use for item pipelines are:
• cleansing HTML data # 清除HTML数据
• validating scraped data (checking that the items contain certain fields) # 验证数据
• checking for duplicates (and dropping them) # 检查重复
• storing the scraped item in a database # 存入数据库
（1）验证数据
from scrapy.exceptions import DropItem class PricePipeline(object): vat_factor = 1.5 def process_item(self, item, spider): if item['price']: if item['price_excludes_vat']: item['price'] *= self.vat_factor else: raise DropItem('Missing price in %s' % item)
（2）写Json文件
import json class JsonWriterPipeline(object): def __init__(self): self.file = open('json.jl', 'wb') def process_item(self, item, spider): line = json.dumps(dict(item)) + 'n' self.file.write(line) return item
（3）检查重复
from scrapy.exceptions import DropItem class Duplicates(object): def __init__(self): self.ids_seen = set() def process_item(self, item, spider): if item['id'] in self.ids_seen: raise DropItem('Duplicate item found : %s' % item) else: self.ids_seen.add(item['id']) return item
至于将数据写入数据库，应该也很简单。在 process_item 函数中，将 item 存入进去即可了。
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