不一样操做系统安装操做不一样,能够直接看官方文档Install Scrapycss
在命令行输入html
scrapy startproject tutorial
进入项目目录建立一个spiderpython
cd tutorial scrapy genspider quotes domain.com
import scrapy class QuotesSpider(scrapy.Spider): name = "quotes" def start_requests(self): urls = [ 'http://quotes.toscrape.com/page/1/', 'http://quotes.toscrape.com/page/2/', ] for url in urls: yield scrapy.Request(url=url, callback=self.parse) def parse(self, response): page = response.url.split("/")[-2] filename = 'quotes-%s.html' % page with open(filename, 'wb') as f: f.write(response.body) self.log('Saved file %s' % filename)
运行scrapy,在项目顶级目录下输入命令web
scrapy crawl quotes
在QuotesSpider这个类里,name指明spider的名称,在start_requests函数里发出请求,用parse函数处理请求返回的结果,start_requests函数能够替换为start_urls列表,scrapy会自动帮咱们发出请求,并默认用parse函数处理,还能够设置一些其它参数,详见Document正则表达式
scrapy内置css选择器和xpath选择器,固然你也能够选择使用其余的解析库,好比BeautifulSoup,咱们简单用scrapy shell展现一下scrapy内置选择器的用法,在命令行中输入shell
scrapy shell https://docs.scrapy.org/en/latest/_static/selectors-sample1.html
示例代码dom
<html> <head> <base href='http://example.com/' /> <title>Example website</title> </head> <body> <div id='images'> <a href='image1.html'>Name: My image 1 <br /><img src='image1_thumb.jpg' /></a> <a href='image2.html'>Name: My image 2 <br /><img src='image2_thumb.jpg' /></a> <a href='image3.html'>Name: My image 3 <br /><img src='image3_thumb.jpg' /></a> <a href='image4.html'>Name: My image 4 <br /><img src='image4_thumb.jpg' /></a> <a href='image5.html'>Name: My image 5 <br /><img src='image5_thumb.jpg' /></a> </div> </body> </html>
# 获取标题 # selector能够去掉 # extract返回的是列表 response.selector.xpath('//title/text()').extract_first() response.selector.css('title::text').extract_first() # 获取a标签里href参数内容 response.xpath('//a/@href').extract() response.css('a::attr(href)').extract() # 混合获取img标签的src属性 response.xpath('//div[@id="images"]').css('img::attr(src)').extract() # 获取a标签中包含image的href属性 response.xpath('//a[contains(@href, "image")]/@href').extract() response.css('a[href*=image]::attr(href)').extract() # 使用正则表达式 response.css('a::text').re('Name\:(.*)') response.css('a::text').re_first('Name\:(.*)') # 添加default参数指定默认提取信息 response.css('aa').extract_first(default='')
经过parse处理函数返回的Item能够用Item Pipeline进行加工处理,主要是数据清洗,格式化。scrapy
# 过滤掉相同的item class DuplicatePipeline(object): def __init__(self): self.items = set() def process_item(self, item, spider): if item['id'] in self.items: raise DropItem('Duplicate item found: %s' % item['id']) else: self.items.add(item['id']) return item
须要在settings里的注册一下自定义的Pipelineide
ITEM_PIPELINES = { 'tutorial.pipelines.TutorialPipeline': 300, 'tutorial.pipelines.DuplicatePipeline': 200, }
数字越小,优先级越高函数