scrapy

一、介绍

Scrapy一个开源和协作的框架，其最初是为了页面抓取 (更确切来说, 网络抓取 )所设计的，使用它可以以快速、简单、可扩展的方式从网站中提取所需的数据。但目前Scrapy的用途十分广泛，可用于如数据挖掘、监测和自动化测试等领域，也可以应用在获取API所返回的数据(例如 Amazon Associates Web Services ) 或者通用的网络爬虫。

​ Scrapy 是基于twisted框架开发而来，twisted是一个流行的事件驱动的python网络框架。因此Scrapy使用了一种非阻塞（又名异步）的代码来实现并发。整体架构大致如下

img

The data flow in Scrapy is controlled by the execution engine, and goes like this:

1. The Engine gets the initial Requests to crawl from the Spider.（Engine从Spider中获取初始的请求）
2. The Engine schedules the Requests in the Scheduler and asks for the next Requests to crawl.（Engine将请求分发给Scheduler，并去获取下一个待爬取的请求）
3. The Scheduler returns the next Requests to the Engine.（Scheduler将处理过后的请求交给Engine）
4. The Engine sends the Requests to the Downloader, passing through the Downloader Middlewares (see process_request()).（Engine穿过Downloader Middlewares将请求分配给Downloader）
5. Once the page finishes downloading the Downloader generates a Response (with that page) and sends it to the Engine, passing through the Downloader Middlewares (see process_response()).（一旦页面完成下载，Downloader生成一个响应并将这个响应穿过Downloader Middlewares发送给Engine）
6. The Engine receives the Response from the Downloader and sends it to the Spider for processing, passing through the Spider Middleware (see process_spider_input()).（Engine从Downloader接收到响应并将它经过Spider Middleware发送给Spider去处理）
7. The Spider processes the Response and returns scraped items and new Requests (to follow) to the Engine, passing through the Spider Middleware (see process_spider_output()).（Spider处理完这个响应后会生成items和新的请求，将这些结果通过Spider Middleware交给Engine）
8. The Engine sends processed items to Item Pipelines, then send processed Requests to the Scheduler and asks for possible next Requests to crawl.（Engine将items交给Item Pipelines，将处理过的请求交给Scheduler，并且下一个待爬取的请求）
9. The process repeats (from step 1) until there are no more requests from the Scheduler.（重复步骤1直到Scheduler中没有待爬取的请求）

Components：

1. 引擎(EGINE)

   引擎负责控制系统所有组件之间的数据流，并在某些动作发生时触发事件。有关详细信息，请参见上面的数据流部分。

2. 调度器(SCHEDULER)
   用来接受引擎发过来的请求, 压入队列中, 并在引擎再次请求的时候返回. 可以想像成一个URL的优先级队列, 由它来决定下一个要抓取的网址是什么, 同时去除重复的网址

3. 下载器(DOWLOADER)
   用于下载网页内容, 并将网页内容返回给EGINE，下载器是建立在twisted这个高效的异步模型上的

4. 爬虫(SPIDERS)
   SPIDERS是开发人员自定义的类，用来解析responses，并且提取items，或者发送新的请求

5. 项目管道(ITEM PIPLINES)
   在items被提取后负责处理它们，主要包括清理、验证、持久化（比如存到数据库）等操作

6. 下载器中间件(Downloader Middlewares)

   位于Scrapy引擎和下载器之间，主要用来处理从EGINE传到DOWLOADER的请求request，已经从DOWNLOADER传到EGINE的响应response，你可用该中间件做以下几件事

   1. process a request just before it is sent to the Downloader (i.e. right before Scrapy sends the request to the website);
   2. change received response before passing it to a spider;
   3. send a new Request instead of passing received response to a spider;
   4. pass response to a spider without fetching a web page;
   5. silently drop some requests.

7. 爬虫中间件(Spider Middlewares)
   特殊的钩子位于EGINE和SPIDERS之间，主要工作是处理SPIDERS的输入（即responses）和输出（items and requests）。你可用该中间件做以下几件事：

   1. post-process output of spider callbacks - change/add/remove requests or items;
   2. post-process start_requests;
   3. handle spider exceptions;
   4. call errback instead of callback for some of the requests based on response content.

官网：https://docs.scrapy.org/en/latest/topics/architecture.html

二、安装

#Windows平台
    1、pip3 install wheel #安装后，便支持通过wheel文件安装软件，wheel文件官网：https://www.lfd.uci.edu/~gohlke/pythonlibs
    3、pip3 install lxml
    4、pip3 install pyopenssl
    5、下载并安装pywin32：https://sourceforge.net/projects/pywin32/files/pywin32/
    6、下载twisted的wheel文件：http://www.lfd.uci.edu/~gohlke/pythonlibs/#twisted
    7、执行pip3 install 下载目录\Twisted-17.9.0-cp36-cp36m-win_amd64.whl
    8、pip3 install scrapy
  
#Linux平台
    1、pip3 install scrapy

三、命令行工具

#1 查看帮助
    scrapy -h
    scrapy <command> [options] [args]

#2 有两种命令：其中Project-only必须切到项目文件夹下才能执行，而Global的命令则不需要
    Global commands:
        startproject #创建项目
        genspider    #创建爬虫程序
        settings     #如果是在项目目录下，则得到的是该项目的配置
        runspider    #运行一个独立的python文件，不必创建项目
        shell        #scrapy shell url地址  在交互式调试，如选择器规则正确与否
        fetch        #独立于程单纯地爬取一个页面，可以拿到请求头
        view         #下载完毕后直接弹出浏览器，以此可以分辨出哪些数据是ajax请求
        version      #scrapy version 查看scrapy的版本，scrapy version -v查看scrapy依赖库的版本
    Project-only commands:
        crawl        #运行爬虫，必须创建项目才行，确保配置文件中ROBOTSTXT_OBEY = False
        check        #检测项目中有无语法错误
        list         #列出项目中所包含的爬虫名
        edit         #编辑器，一般不用
        parse        #scrapy parse url地址 --callback 回调函数  #以此可以验证我们的回调函数是否正确
        bench        #scrapy bentch压力测试

#3 官网链接
    https://docs.scrapy.org/en/latest/topics/commands.html

示范用法：

#1、执行全局命令：请确保不在某个项目的目录下，排除受该项目配置的影响
scrapy startproject MyProject

cd MyProject
scrapy genspider baidu www.baidu.com

scrapy settings --get XXX #如果切换到项目目录下，看到的则是该项目的配置

scrapy runspider baidu.py

scrapy shell https://www.baidu.com
    response
    response.status
    response.body
    view(response)
    
scrapy view https://www.taobao.com #如果页面显示内容不全，不全的内容则是ajax请求实现的，以此快速定位问题

scrapy fetch --nolog --headers https://www.taobao.com

scrapy version #scrapy的版本

scrapy version -v #依赖库的版本

#2、执行项目命令：切到项目目录下
scrapy crawl baidu
scrapy check
scrapy list
scrapy parse http://quotes.toscrape.com/ --callback parse
scrapy bench

四、项目结构以及爬虫应用简介

project_name/
   scrapy.cfg
   project_name/
       __init__.py
       items.py
       pipelines.py
       settings.py
       spiders/
           __init__.py
           爬虫1.py
           爬虫2.py
           爬虫3.py

文件说明：

• scrapy.cfg 项目的主配置信息，用来部署scrapy时使用，爬虫相关的配置信息在settings.py文件中。
• items.py 设置数据存储模板，用于结构化数据，如：Django的Model
• pipelines 数据处理行为，如：一般结构化的数据持久化
• settings.py 配置文件，如：递归的层数、并发数，延迟下载等。强调:配置文件的选项必须大写否则视为无效****，正确写法USER_AGENT='xxxx'
• spiders 爬虫目录，如：创建文件，编写爬虫规则

注意：一般创建爬虫文件时，以网站域名命名

# 默认只能在cmd中执行爬虫，如果想在pycharm中执行需要做
#在项目目录下新建：entrypoint.py
from scrapy.cmdline import execute
execute(['scrapy', 'crawl', 'xiaohua'])

关于windows编码

import sys,os
sys.stdout=io.TextIOWrapper(sys.stdout.buffer,encoding='gb18030')

五、Spiders

1、介绍

Spiders是由一系列类（定义了一个网址或一组网址将被爬取）组成，具体包括如何执行爬取任务并且如何从页面中提取结构化的数据。

换句话说，Spiders是你为了一个特定的网址或一组网址自定义爬取和解析页面行为的地方

2、Spiders会循环做如下事情

#1、生成初始的Requests来爬取第一个URLS，并且标识一个回调函数
第一个请求定义在start_requests()方法内默认从start_urls列表中获得url地址来生成Request请求，默认的回调函数是parse方法。回调函数在下载完成返回response时自动触发

#2、在回调函数中，解析response并且返回值
返回值可以4种：
        包含解析数据的字典
        Item对象
        新的Request对象（新的Requests也需要指定一个回调函数）
        或者是可迭代对象（包含Items或Request）

#3、在回调函数中解析页面内容
通常使用Scrapy自带的Selectors，但很明显你也可以使用Beutifulsoup，lxml或其他你爱用啥用啥。

#4、最后，针对返回的Items对象将会被持久化到数据库
通过Item Pipeline组件存到数据库：https://docs.scrapy.org/en/latest/topics/item-pipeline.html#topics-item-pipeline）
或者导出到不同的文件（通过Feed exports：https://docs.scrapy.org/en/latest/topics/feed-exports.html#topics-feed-exports）

3、Spiders总共提供了五种类：

#1、scrapy.spiders.Spider #scrapy.Spider等同于scrapy.spiders.Spider
#2、scrapy.spiders.CrawlSpider
#3、scrapy.spiders.XMLFeedSpider
#4、scrapy.spiders.CSVFeedSpider
#5、scrapy.spiders.SitemapSpider

4、导入使用

# -*- coding: utf-8 -*-
import scrapy
from scrapy.spiders import Spider,CrawlSpider,XMLFeedSpider,CSVFeedSpider,SitemapSpider

class AmazonSpider(scrapy.Spider): #自定义类，继承Spiders提供的基类
    name = 'amazon'
    allowed_domains = ['www.amazon.cn']
    start_urls = ['http://www.amazon.cn/']
    
    def parse(self, response):
        pass

5、class scrapy.spiders.Spider

这是最简单的spider类，任何其他的spider类都需要继承它（包含你自己定义的）。

该类不提供任何特殊的功能，它仅提供了一个默认的start_requests方法默认从start_urls中读取url地址发送requests请求，并且默认parse作为回调函数。

class AmazonSpider(scrapy.Spider):
    name = 'amazon' 
    allowed_domains = ['www.amazon.cn'] 
    start_urls = ['http://www.amazon.cn/']
    
    custom_settings = {
        'BOT_NAME' : 'Egon_Spider_Amazon',
        'REQUEST_HEADERS' : {
          'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
          'Accept-Language': 'en',
        }
    }
    
    def parse(self, response):
        pass

定制scrapy.spider属性与方法详解

#1、name = 'amazon' 
定义爬虫名，scrapy会根据该值定位爬虫程序
所以它必须要有且必须唯一（In Python 2 this must be ASCII only.）

#2、allowed_domains = ['www.amazon.cn'] 
定义允许爬取的域名，如果OffsiteMiddleware启动（默认就启动），
那么不属于该列表的域名及其子域名都不允许爬取
如果爬取的网址为：https://www.example.com/1.html，那就添加'example.com'到列表.

#3、start_urls = ['http://www.amazon.cn/']
如果没有指定url，就从该列表中读取url来生成第一个请求

#4、custom_settings
值为一个字典，定义一些配置信息，在运行爬虫程序时，这些配置会覆盖项目级别的配置
所以custom_settings必须被定义成一个类属性，由于settings会在类实例化前被加载

#5、settings
通过self.settings['配置项的名字']可以访问settings.py中的配置，如果自己定义了custom_settings还是以自己的为准

#6、logger
日志名默认为spider的名字
self.logger.debug('=============>%s' %self.settings['BOT_NAME'])

#5、crawler：了解
该属性必须被定义到类方法from_crawler中

#6、from_crawler(crawler, *args, **kwargs)：了解
You probably won’t need to override this directly  because the default implementation acts as a proxy to the __init__() method, calling it with the given arguments args and named arguments kwargs.

#7、start_requests()
该方法用来发起第一个Requests请求，且必须返回一个可迭代的对象。它在爬虫程序打开时就被Scrapy调用，Scrapy只调用它一次。
默认从start_urls里取出每个url来生成Request(url, dont_filter=True)

#针对参数dont_filter,请看自定义去重规则

如果你想要改变起始爬取的Requests，你就需要覆盖这个方法，例如你想要起始发送一个POST请求，如下
class MySpider(scrapy.Spider):
    name = 'myspider'

    def start_requests(self):
        return [scrapy.FormRequest("http://www.example.com/login",
                                   formdata={'user': 'john', 'pass': 'secret'},
                                   callback=self.logged_in)]

    def logged_in(self, response):
        # here you would extract links to follow and return Requests for
        # each of them, with another callback
        pass
        
#8、parse(response)
这是默认的回调函数，所有的回调函数必须返回an iterable of Request and/or dicts or Item objects.

#9、log(message[, level, component])：了解
Wrapper that sends a log message through the Spider’s logger, kept for backwards compatibility. For more information see Logging from Spiders.

#10、closed(reason)
爬虫程序结束时自动触发
复制代码

去重规则：去除重复的url

去重规则应该多个爬虫共享的，但凡一个爬虫爬取了，其他都不要爬了，实现方式如下

#方法一：
1、新增类属性
visited=set() #类属性

2、回调函数parse方法内：
def parse(self, response):
    if response.url in self.visited:
        return None
    .......

    self.visited.add(response.url) 

#方法一改进：针对url可能过长，所以我们存放url的hash值
def parse(self, response):
        url=md5(response.request.url)
    if url in self.visited:
        return None
    .......

    self.visited.add(url) 

#方法二：Scrapy自带去重功能
配置文件：
DUPEFILTER_CLASS = 'scrapy.dupefilter.RFPDupeFilter' #默认的去重规则帮我们去重，去重规则在内存中
DUPEFILTER_DEBUG = False
JOBDIR = "保存范文记录的日志路径，如：/root/"  # 最终路径为 /root/requests.seen，去重规则放文件中

scrapy自带去重规则默认为RFPDupeFilter，只需要我们指定
Request(...,dont_filter=False) ，如果dont_filter=True则告诉Scrapy这个URL不参与去重。

#方法三：
我们也可以仿照RFPDupeFilter自定义去重规则，

from scrapy.dupefilter import RFPDupeFilter，看源码，仿照BaseDupeFilter

#步骤一：在项目目录下自定义去重文件dup.py
class UrlFilter(object):
    def __init__(self):
        self.visited = set() #或者放到数据库

    @classmethod
    def from_settings(cls, settings):
        return cls()

    def request_seen(self, request):
        if request.url in self.visited:
            return True
        self.visited.add(request.url)

    def open(self):  # can return deferred
        pass

    def close(self, reason):  # can return a deferred
        pass

    def log(self, request, spider):  # log that a request has been filtered
        pass

#步骤二：配置文件settings.py：
DUPEFILTER_CLASS = '项目名.dup.UrlFilter'


# 源码分析：
from scrapy.core.scheduler import Scheduler
见Scheduler下的enqueue_request方法：self.df.request_seen(request)

例子

import scrapy

class MySpider(scrapy.Spider):
    name = 'example.com'
    allowed_domains = ['example.com']
    start_urls = [
        'http://www.example.com/1.html',
        'http://www.example.com/2.html',
        'http://www.example.com/3.html',
    ]

    def parse(self, response):
        self.logger.info('A response from %s just arrived!', response.url)
    
#例二：一个回调函数返回多个Requests和Items
import scrapy

class MySpider(scrapy.Spider):
    name = 'example.com'
    allowed_domains = ['example.com']
    start_urls = [
        'http://www.example.com/1.html',
        'http://www.example.com/2.html',
        'http://www.example.com/3.html',
    ]

    def parse(self, response):
        for h3 in response.xpath('//h3').extract():
            yield {"title": h3}

        for url in response.xpath('//a/@href').extract():
            yield scrapy.Request(url, callback=self.parse)
            
            
#例三：在start_requests()内直接指定起始爬取的urls，start_urls就没有用了，

import scrapy
from myproject.items import MyItem

class MySpider(scrapy.Spider):
    name = 'example.com'
    allowed_domains = ['example.com']

    def start_requests(self):
        yield scrapy.Request('http://www.example.com/1.html', self.parse)
        yield scrapy.Request('http://www.example.com/2.html', self.parse)
        yield scrapy.Request('http://www.example.com/3.html', self.parse)

    def parse(self, response):
        for h3 in response.xpath('//h3').extract():
            yield MyItem(title=h3)

        for url in response.xpath('//a/@href').extract():
            yield scrapy.Request(url, callback=self.parse)

参数传递

我们可能需要在命令行为爬虫程序传递参数，比如传递初始的url，像这样
#命令行执行
scrapy crawl myspider -a category=electronics

#在__init__方法中可以接收外部传进来的参数
import scrapy

class MySpider(scrapy.Spider):
    name = 'myspider'

    def __init__(self, category=None, *args, **kwargs):
        super(MySpider, self).__init__(*args, **kwargs)
        self.start_urls = ['http://www.example.com/categories/%s' % category]
        #...

#注意接收的参数全都是字符串，如果想要结构化的数据，你需要用类似json.loads的方法

6、其他通用Spiders

https://docs.scrapy.org/en/latest/topics/spiders.html#generic-spiders

六、Selectors

#1 //与/
#2 text
#3、extract与extract_first:从selector对象中解出内容
#4、属性：xpath的属性加前缀@
#4、嵌套查找
#5、设置默认值
#4、按照属性查找
#5、按照属性模糊查找
#6、正则表达式
#7、xpath相对路径
#8、带变量的xpath

response.selector.css()
response.selector.xpath()
可简写为
response.css()
response.xpath()

#1 //与/
response.xpath('//body/a/')#
response.css('div a::text')

>>> response.xpath('//body/a') #开头的//代表从整篇文档中寻找,body之后的/代表body的儿子
[]
>>> response.xpath('//body//a') #开头的//代表从整篇文档中寻找,body之后的//代表body的子子孙孙
[<Selector xpath='//body//a' data='<a href="image1.html">Name: My image 1 <'>, <Selector xpath='//body//a' data='<a href="image2.html">Name: My image 2 <'>, <Selector xpath='//body//a' data='<a href="
image3.html">Name: My image 3 <'>, <Selector xpath='//body//a' data='<a href="image4.html">Name: My image 4 <'>, <Selector xpath='//body//a' data='<a href="image5.html">Name: My image 5 <'>]

#2 text
>>> response.xpath('//body//a/text()')
>>> response.css('body a::text')

#3、extract与extract_first:从selector对象中解出内容
>>> response.xpath('//div/a/text()').extract()
['Name: My image 1 ', 'Name: My image 2 ', 'Name: My image 3 ', 'Name: My image 4 ', 'Name: My image 5 ']
>>> response.css('div a::text').extract()
['Name: My image 1 ', 'Name: My image 2 ', 'Name: My image 3 ', 'Name: My image 4 ', 'Name: My image 5 ']

>>> response.xpath('//div/a/text()').extract_first()
'Name: My image 1 '
>>> response.css('div a::text').extract_first()
'Name: My image 1 '

#4、属性：xpath的属性加前缀@
>>> response.xpath('//div/a/@href').extract_first()
'image1.html'
>>> response.css('div a::attr(href)').extract_first()
'image1.html'

#4、嵌套查找
>>> response.xpath('//div').css('a').xpath('@href').extract_first()
'image1.html'

#5、设置默认值
>>> response.xpath('//div[@id="xxx"]').extract_first(default="not found")
'not found'

#4、按照属性查找
response.xpath('//div[@id="images"]/a[@href="image3.html"]/text()').extract()
response.css('#images a[@href="image3.html"]/text()').extract()

#5、按照属性模糊查找
response.xpath('//a[contains(@href,"image")]/@href').extract()
response.css('a[href*="image"]::attr(href)').extract()

response.xpath('//a[contains(@href,"image")]/img/@src').extract()
response.css('a[href*="imag"] img::attr(src)').extract()

response.xpath('//*[@href="image1.html"]')
response.css('*[href="image1.html"]')

#6、正则表达式
response.xpath('//a/text()').re(r'Name: (.*)')
response.xpath('//a/text()').re_first(r'Name: (.*)')

#7、xpath相对路径
>>> res=response.xpath('//a[contains(@href,"3")]')[0]
>>> res.xpath('img')
[<Selector xpath='img' data='<img src="image3_thumb.jpg">'>]
>>> res.xpath('./img')
[<Selector xpath='./img' data='<img src="image3_thumb.jpg">'>]
>>> res.xpath('.//img')
[<Selector xpath='.//img' data='<img src="image3_thumb.jpg">'>]
>>> res.xpath('//img') #这就是从头开始扫描
[<Selector xpath='//img' data='<img src="image1_thumb.jpg">'>, <Selector xpath='//img' data='<img src="image2_thumb.jpg">'>, <Selector xpath='//img' data='<img src="image3_thumb.jpg">'>, <Selector xpa
th='//img' data='<img src="image4_thumb.jpg">'>, <Selector xpath='//img' data='<img src="image5_thumb.jpg">'>]

#8、带变量的xpath
>>> response.xpath('//div[@id=$xxx]/a/text()',xxx='images').extract_first()
'Name: My image 1 '
>>> response.xpath('//div[count(a)=$yyy]/@id',yyy=5).extract_first() #求有5个a标签的div的id
'images'

https://docs.scrapy.org/en/latest/topics/selectors.htm

七、Items

https://docs.scrapy.org/en/latest/topics/items.html

八、Item Pipeline

当Item在Spider中被收集之后，它将会被传递到Item Pipeline，一些组件会按照一定的顺序执行对Item的处理。

每个item pipeline组件(有时称之为“Item Pipeline”)是实现了简单方法的Python类。他们接收到Item并通过它执行一些行为，同时也决定此Item是否继续通过pipeline，或是被丢弃而不再进行处理。

以下是item pipeline的一些典型应用：

• 清理HTML数据
• 验证爬取的数据(检查item包含某些字段)
• 查重(并丢弃)
• 将爬取结果保存到数据库中

每个item pipiline组件是一个独立的Python类，同时必须实现以下方法:

process_item(self, item, spider)
    每个item pipeline组件都需要调用该方法，这个方法必须返回一个具有数据的dict，或是 Item (或任何继承类)对象， 或是抛出 DropItem 异常，被丢弃的item将不会被之后的pipeline组件所处理。
参数：
    item (Item 对象或者一个dict) – 被爬取的item
    spider (Spider 对象) – 爬取该item的spider

此外,他们也可以实现以下方法:

open_spider(self, spider)
    当spider被开启时，这个方法被调用。
    参数: spider (Spider 对象) – 被开启的spider
    
close_spider(self, spider)
    当spider被关闭时，这个方法被调用
    参数: spider (Spider 对象) – 被关闭的spider
    
from_crawler(cls, crawler)
    If present, this classmethod is called to create a pipeline instance from a Crawler. It must return a new instance of the pipeline. Crawler object provides access to all Scrapy core components like settings and signals; it is a way for pipeline to access them and hook its functionality into Scrapy.
    参数: crawler (Crawler object) – crawler that uses this pipeline

Item pipeline 样例

验证价格，同时丢弃没有价格的Item

让我们来看一下以下这个假设的pipeline，它为那些不含税(price_excludes_vat 属性)的item调整了 price 属性，同时丢弃了那些没有价格的item:

from scrapy.exceptions import DropItem

class PricePipeline(object):

    vat_factor = 1.15

    def process_item(self, item, spider):
        if item['price']:
            if item['price_excludes_vat']:
                item['price'] = item['price'] * self.vat_factor
            return item
        else:
            raise DropItem("Missing price in %s" % item)

将item写入文件

以下pipeline将所有(从所有spider中)爬取到的item，存储到一个独立地 items.jl 文件，每行包含一个序列化为JSON格式的item:

import json

class JsonWriterPipeline(object):

    def __init__(self):
        self.file = open('items.jl', 'wb')

    def process_item(self, item, spider):
        line = json.dumps(dict(item)) + "\n"
        self.file.write(line)
        return item

Write items to MongoDB

In this example we’ll write items to MongoDB using pymongo. MongoDB address and database name are specified in Scrapy settings; MongoDB collection is named after item class.

The main point of this example is to show how to use from_crawler() method and how to clean up the resources properly.

import pymongo

class MongoPipeline(object):

    collection_name = 'scrapy_items'

    def __init__(self, mongo_uri, mongo_db):
        self.mongo_uri = mongo_uri
        self.mongo_db = mongo_db

    @classmethod
    def from_crawler(cls, crawler):
        return cls(
            mongo_uri=crawler.settings.get('MONGO_URI'),
            mongo_db=crawler.settings.get('MONGO_DATABASE', 'items')
        )

    def open_spider(self, spider):
        self.client = pymongo.MongoClient(self.mongo_uri)
        self.db = self.client[self.mongo_db]

    def close_spider(self, spider):
        self.client.close()

    def process_item(self, item, spider):
        self.db[self.collection_name].insert(dict(item))
        return item

去重

一个用于去重的过滤器，丢弃那些已经被处理过的item。让我们假设我们的item有一个唯一的id，但是我们spider返回的多个item中包含有相同的id:

from scrapy.exceptions import DropItem

class DuplicatesPipeline(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

启用一个Item Pipeline组件

为了启用一个Item Pipeline组件，你必须将它的类添加到 ITEM_PIPELINES 配置，就像下面这个例子:

ITEM_PIPELINES = {
    'myproject.pipelines.PricePipeline': 300,
    'myproject.pipelines.JsonWriterPipeline': 800,
}

分配给每个类的整型值，确定了他们运行的顺序，item按数字从低到高的顺序，通过pipeline，通常将这些数字定义在0-1000范围内。

自定义pipeline

#一：可以写多个Pipeline类
#1、如果优先级高的Pipeline的process_item返回一个值或者None，会自动传给下一个pipline的process_item,
#2、如果只想让第一个Pipeline执行，那得让第一个pipline的process_item抛出异常raise DropItem()
#3、可以用spider.name == '爬虫名' 来控制哪些爬虫用哪些pipeline

二：示范
from scrapy.exceptions import DropItem

class CustomPipeline(object):
    def __init__(self,v):
        self.value = v

    @classmethod
    def from_crawler(cls, crawler):
        """
        Scrapy会先通过getattr判断我们是否自定义了from_crawler,有则调它来完
        成实例化
        """
        val = crawler.settings.getint('MMMM')
        return cls(val)

    def open_spider(self,spider):
        """
        爬虫刚启动时执行一次
        """
        print('000000')

    def close_spider(self,spider):
        """
        爬虫关闭时执行一次
        """
        print('111111')

    def process_item(self, item, spider):
        # 操作并进行持久化

        # return表示会被后续的pipeline继续处理
        return item

        # 表示将item丢弃，不会被后续pipeline处理
        # raise DropItem()

示例

#1、settings.py
HOST="127.0.0.1"
PORT=27017
USER="root"
PWD="123"
DB="amazon"
TABLE="goods"


ITEM_PIPELINES = {
   'Amazon.pipelines.CustomPipeline': 200,
}

#2、pipelines.py
class CustomPipeline(object):
    def __init__(self,host,port,user,pwd,db,table):
        self.host=host
        self.port=port
        self.user=user
        self.pwd=pwd
        self.db=db
        self.table=table

    @classmethod
    def from_crawler(cls, crawler):
        """
        Scrapy会先通过getattr判断我们是否自定义了from_crawler,有则调它来完
        成实例化
        """
        HOST = crawler.settings.get('HOST')
        PORT = crawler.settings.get('PORT')
        USER = crawler.settings.get('USER')
        PWD = crawler.settings.get('PWD')
        DB = crawler.settings.get('DB')
        TABLE = crawler.settings.get('TABLE')
        return cls(HOST,PORT,USER,PWD,DB,TABLE)

    def open_spider(self,spider):
        """
        爬虫刚启动时执行一次
        """
        self.client = MongoClient('mongodb://%s:%s@%s:%s' %(self.user,self.pwd,self.host,self.port))

    def close_spider(self,spider):
        """
        爬虫关闭时执行一次
        """
        self.client.close()


    def process_item(self, item, spider):
        # 操作并进行持久化

        self.client[self.db][self.table].save(dict(item))

https://docs.scrapy.org/en/latest/topics/item-pipeline.html

九、Dowloader Middeware

下载器中间件

class DownMiddleware1(object):
    def process_request(self, request, spider):
        """
        请求需要被下载时，经过所有下载器中间件的process_request调用
        :param request: 
        :param spider: 
        :return:  
            None,继续后续中间件去下载；
            Response对象，停止process_request的执行，开始执行process_response
            Request对象，停止中间件的执行，将Request重新调度器
            raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception
        """
        pass



    def process_response(self, request, response, spider):
        """
        spider处理完成，返回时调用
        :param response:
        :param result:
        :param spider:
        :return: 
            Response 对象：转交给其他中间件process_response
            Request 对象：停止中间件，request会被重新调度下载
            raise IgnoreRequest 异常：调用Request.errback
        """
        print('response1')
        return response

    def process_exception(self, request, exception, spider):
        """
        当下载处理器(download handler)或 process_request() (下载中间件)抛出异常
        :param response:
        :param exception:
        :param spider:
        :return: 
            None：继续交给后续中间件处理异常；
            Response对象：停止后续process_exception方法
            Request对象：停止中间件，request将会被重新调用下载
        """
        return None

https://docs.scrapy.org/en/latest/topics/downloader-middleware.html

class DownMiddleware1(object):
    @staticmethod
    def get_proxy():
        return requests.get("http://127.0.0.1:5010/get/").text

    @staticmethod
    def delete_proxy(proxy):
        requests.get("http://127.0.0.1:5010/delete/?proxy={}".format(proxy))

    def process_request(self, request, spider):
        """
        请求需要被下载时，经过所有下载器中间件的process_request调用
        :param request:
        :param spider:
        :return:
            None,继续后续中间件去下载；
            Response对象，停止process_request的执行，开始执行process_response
            Request对象，停止中间件的执行，将Request重新调度器
            raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception
        """

        if not hasattr(DownMiddleware1,'proxy_addr'):
            DownMiddleware1.proxy_addr = self.get_proxy()
        request.meta['download_timeout'] = 5
        request.meta["proxy"] = "http://" + self.proxy_addr

        print('元数据',request.meta)

        if request.meta.get('depth') == 10 or request.meta.get('retry_times') == 2:
            request.meta['depth'] = 0
            request.meta['retry_times']=0
            self.delete_proxy(self.proxy_addr)

            DownMiddleware1.proxy_addr=self.get_proxy()
            request.meta["proxy"] = "http://" + self.proxy_addr
            print('============>',request.meta)
            return request

        return None

十、Spider Middleware

爬虫中间件

class SpiderMiddleware(object):

    def process_spider_input(self,response, spider):
        """
        下载完成，执行，然后交给parse处理
        :param response: 
        :param spider: 
        :return: 
        """
        pass

    def process_spider_output(self,response, result, spider):
        """
        spider处理完成，返回时调用
        :param response:
        :param result:
        :param spider:
        :return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)
        """
        return result

    def process_spider_exception(self,response, exception, spider):
        """
        异常调用
        :param response:
        :param exception:
        :param spider:
        :return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline
        """
        return None


    def process_start_requests(self,start_requests, spider):
        """
        爬虫启动时调用
        :param start_requests:
        :param spider:
        :return: 包含 Request 对象的可迭代对象
        """
        return start_requests

https://docs.scrapy.org/en/latest/topics/spider-middleware.html

十一、settings.py

# -*- coding: utf-8 -*-

# Scrapy settings for step8_king project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
#     http://doc.scrapy.org/en/latest/topics/settings.html
#     http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
#     http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html

# 1. 爬虫名称
BOT_NAME = 'step8_king'

# 2. 爬虫应用路径
SPIDER_MODULES = ['step8_king.spiders']
NEWSPIDER_MODULE = 'step8_king.spiders'

# Crawl responsibly by identifying yourself (and your website) on the user-agent
# 3. 客户端 user-agent请求头
# USER_AGENT = 'step8_king (+http://www.yourdomain.com)'

# Obey robots.txt rules
# 4. 禁止爬虫配置
# ROBOTSTXT_OBEY = False

# Configure maximum concurrent requests performed by Scrapy (default: 16)
# 5. 并发请求数
# CONCURRENT_REQUESTS = 4

# Configure a delay for requests for the same website (default: 0)
# See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
# 6. 延迟下载秒数
# DOWNLOAD_DELAY = 2


# The download delay setting will honor only one of:
# 7. 单域名访问并发数，并且延迟下次秒数也应用在每个域名
# CONCURRENT_REQUESTS_PER_DOMAIN = 2
# 单IP访问并发数，如果有值则忽略：CONCURRENT_REQUESTS_PER_DOMAIN，并且延迟下次秒数也应用在每个IP
# CONCURRENT_REQUESTS_PER_IP = 3

# Disable cookies (enabled by default)
# 8. 是否支持cookie，cookiejar进行操作cookie
# COOKIES_ENABLED = True
# COOKIES_DEBUG = True

# Disable Telnet Console (enabled by default)
# 9. Telnet用于查看当前爬虫的信息，操作爬虫等...
#    使用telnet ip port ，然后通过命令操作
# TELNETCONSOLE_ENABLED = True
# TELNETCONSOLE_HOST = '127.0.0.1'
# TELNETCONSOLE_PORT = [6023,]


# 10. 默认请求头
# Override the default request headers:
# DEFAULT_REQUEST_HEADERS = {
#     'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
#     'Accept-Language': 'en',
# }


# Configure item pipelines
# See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
# 11. 定义pipeline处理请求
# ITEM_PIPELINES = {
#    'step8_king.pipelines.JsonPipeline': 700,
#    'step8_king.pipelines.FilePipeline': 500,
# }



# 12. 自定义扩展，基于信号进行调用
# Enable or disable extensions
# See http://scrapy.readthedocs.org/en/latest/topics/extensions.html
# EXTENSIONS = {
#     # 'step8_king.extensions.MyExtension': 500,
# }


# 13. 爬虫允许的最大深度，可以通过meta查看当前深度；0表示无深度
# DEPTH_LIMIT = 3

# 14. 爬取时，0表示深度优先Lifo(默认)；1表示广度优先FiFo

# 后进先出，深度优先
# DEPTH_PRIORITY = 0
# SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleLifoDiskQueue'
# SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.LifoMemoryQueue'
# 先进先出，广度优先

# DEPTH_PRIORITY = 1
# SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleFifoDiskQueue'
# SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.FifoMemoryQueue'

# 15. 调度器队列
# SCHEDULER = 'scrapy.core.scheduler.Scheduler'
# from scrapy.core.scheduler import Scheduler


# 16. 访问URL去重
# DUPEFILTER_CLASS = 'step8_king.duplication.RepeatUrl'


# Enable and configure the AutoThrottle extension (disabled by default)
# See http://doc.scrapy.org/en/latest/topics/autothrottle.html

"""
17. 自动限速算法
    from scrapy.contrib.throttle import AutoThrottle
    自动限速设置
    1. 获取最小延迟 DOWNLOAD_DELAY
    2. 获取最大延迟 AUTOTHROTTLE_MAX_DELAY
    3. 设置初始下载延迟 AUTOTHROTTLE_START_DELAY
    4. 当请求下载完成后，获取其"连接"时间 latency，即：请求连接到接受到响应头之间的时间
    5. 用于计算的... AUTOTHROTTLE_TARGET_CONCURRENCY
    target_delay = latency / self.target_concurrency
    new_delay = (slot.delay + target_delay) / 2.0 # 表示上一次的延迟时间
    new_delay = max(target_delay, new_delay)
    new_delay = min(max(self.mindelay, new_delay), self.maxdelay)
    slot.delay = new_delay
"""

# 开始自动限速
# AUTOTHROTTLE_ENABLED = True
# The initial download delay
# 初始下载延迟
# AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
# 最大下载延迟
# AUTOTHROTTLE_MAX_DELAY = 10
# The average number of requests Scrapy should be sending in parallel to each remote server
# 平均每秒并发数
# AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0

# Enable showing throttling stats for every response received:
# 是否显示
# AUTOTHROTTLE_DEBUG = True

# Enable and configure HTTP caching (disabled by default)
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings


"""
18. 启用缓存
    目的用于将已经发送的请求或相应缓存下来，以便以后使用
    
    from scrapy.downloadermiddlewares.httpcache import HttpCacheMiddleware
    from scrapy.extensions.httpcache import DummyPolicy
    from scrapy.extensions.httpcache import FilesystemCacheStorage
"""
# 是否启用缓存策略
# HTTPCACHE_ENABLED = True

# 缓存策略：所有请求均缓存，下次在请求直接访问原来的缓存即可
# HTTPCACHE_POLICY = "scrapy.extensions.httpcache.DummyPolicy"
# 缓存策略：根据Http响应头：Cache-Control、Last-Modified 等进行缓存的策略
# HTTPCACHE_POLICY = "scrapy.extensions.httpcache.RFC2616Policy"

# 缓存超时时间
# HTTPCACHE_EXPIRATION_SECS = 0

# 缓存保存路径
# HTTPCACHE_DIR = 'httpcache'

# 缓存忽略的Http状态码
# HTTPCACHE_IGNORE_HTTP_CODES = []

# 缓存存储的插件
# HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'


"""
19. 代理，需要在环境变量中设置
    from scrapy.contrib.downloadermiddleware.httpproxy import HttpProxyMiddleware
    
    方式一：使用默认
        os.environ
        {
            http_proxy:http://root:woshiniba@192.168.11.11:9999/
            https_proxy:http://192.168.11.11:9999/
        }
    方式二：使用自定义下载中间件
    
    def to_bytes(text, encoding=None, errors='strict'):
        if isinstance(text, bytes):
            return text
        if not isinstance(text, six.string_types):
            raise TypeError('to_bytes must receive a unicode, str or bytes '
                            'object, got %s' % type(text).__name__)
        if encoding is None:
            encoding = 'utf-8'
        return text.encode(encoding, errors)
        
    class ProxyMiddleware(object):
        def process_request(self, request, spider):
            PROXIES = [
                {'ip_port': '111.11.228.75:80', 'user_pass': ''},
                {'ip_port': '120.198.243.22:80', 'user_pass': ''},
                {'ip_port': '111.8.60.9:8123', 'user_pass': ''},
                {'ip_port': '101.71.27.120:80', 'user_pass': ''},
                {'ip_port': '122.96.59.104:80', 'user_pass': ''},
                {'ip_port': '122.224.249.122:8088', 'user_pass': ''},
            ]
            proxy = random.choice(PROXIES)
            if proxy['user_pass'] is not None:
                request.meta['proxy'] = to_bytes（"http://%s" % proxy['ip_port']）
                encoded_user_pass = base64.encodestring(to_bytes(proxy['user_pass']))
                request.headers['Proxy-Authorization'] = to_bytes('Basic ' + encoded_user_pass)
                print "**************ProxyMiddleware have pass************" + proxy['ip_port']
            else:
                print "**************ProxyMiddleware no pass************" + proxy['ip_port']
                request.meta['proxy'] = to_bytes("http://%s" % proxy['ip_port'])
    
    DOWNLOADER_MIDDLEWARES = {
       'step8_king.middlewares.ProxyMiddleware': 500,
    }
    
"""

"""
20. Https访问
    Https访问时有两种情况：
    1. 要爬取网站使用的可信任证书(默认支持)
        DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"
        DOWNLOADER_CLIENTCONTEXTFACTORY = "scrapy.core.downloader.contextfactory.ScrapyClientContextFactory"
        
    2. 要爬取网站使用的自定义证书
        DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"
        DOWNLOADER_CLIENTCONTEXTFACTORY = "step8_king.https.MySSLFactory"
        
        # https.py
        from scrapy.core.downloader.contextfactory import ScrapyClientContextFactory
        from twisted.internet.ssl import (optionsForClientTLS, CertificateOptions, PrivateCertificate)
        
        class MySSLFactory(ScrapyClientContextFactory):
            def getCertificateOptions(self):
                from OpenSSL import crypto
                v1 = crypto.load_privatekey(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.key.unsecure', mode='r').read())
                v2 = crypto.load_certificate(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.pem', mode='r').read())
                return CertificateOptions(
                    privateKey=v1,  # pKey对象
                    certificate=v2,  # X509对象
                    verify=False,
                    method=getattr(self, 'method', getattr(self, '_ssl_method', None))
                )
    其他：
        相关类
            scrapy.core.downloader.handlers.http.HttpDownloadHandler
            scrapy.core.downloader.webclient.ScrapyHTTPClientFactory
            scrapy.core.downloader.contextfactory.ScrapyClientContextFactory
        相关配置
            DOWNLOADER_HTTPCLIENTFACTORY
            DOWNLOADER_CLIENTCONTEXTFACTORY

"""



"""
21. 爬虫中间件
    class SpiderMiddleware(object):

        def process_spider_input(self,response, spider):
            '''
            下载完成，执行，然后交给parse处理
            :param response: 
            :param spider: 
            :return: 
            '''
            pass
    
        def process_spider_output(self,response, result, spider):
            '''
            spider处理完成，返回时调用
            :param response:
            :param result:
            :param spider:
            :return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)
            '''
            return result
    
        def process_spider_exception(self,response, exception, spider):
            '''
            异常调用
            :param response:
            :param exception:
            :param spider:
            :return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline
            '''
            return None
    
    
        def process_start_requests(self,start_requests, spider):
            '''
            爬虫启动时调用
            :param start_requests:
            :param spider:
            :return: 包含 Request 对象的可迭代对象
            '''
            return start_requests
    
    内置爬虫中间件：
        'scrapy.contrib.spidermiddleware.httperror.HttpErrorMiddleware': 50,
        'scrapy.contrib.spidermiddleware.offsite.OffsiteMiddleware': 500,
        'scrapy.contrib.spidermiddleware.referer.RefererMiddleware': 700,
        'scrapy.contrib.spidermiddleware.urllength.UrlLengthMiddleware': 800,
        'scrapy.contrib.spidermiddleware.depth.DepthMiddleware': 900,

"""
# from scrapy.contrib.spidermiddleware.referer import RefererMiddleware
# Enable or disable spider middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
SPIDER_MIDDLEWARES = {
   # 'step8_king.middlewares.SpiderMiddleware': 543,
}


"""
22. 下载中间件
    class DownMiddleware1(object):
        def process_request(self, request, spider):
            '''
            请求需要被下载时，经过所有下载器中间件的process_request调用
            :param request:
            :param spider:
            :return:
                None,继续后续中间件去下载；
                Response对象，停止process_request的执行，开始执行process_response
                Request对象，停止中间件的执行，将Request重新调度器
                raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception
            '''
            pass
    
    
    
        def process_response(self, request, response, spider):
            '''
            spider处理完成，返回时调用
            :param response:
            :param result:
            :param spider:
            :return:
                Response 对象：转交给其他中间件process_response
                Request 对象：停止中间件，request会被重新调度下载
                raise IgnoreRequest 异常：调用Request.errback
            '''
            print('response1')
            return response
    
        def process_exception(self, request, exception, spider):
            '''
            当下载处理器(download handler)或 process_request() (下载中间件)抛出异常
            :param response:
            :param exception:
            :param spider:
            :return:
                None：继续交给后续中间件处理异常；
                Response对象：停止后续process_exception方法
                Request对象：停止中间件，request将会被重新调用下载
            '''
            return None

    
    默认下载中间件
    {
        'scrapy.contrib.downloadermiddleware.robotstxt.RobotsTxtMiddleware': 100,
        'scrapy.contrib.downloadermiddleware.httpauth.HttpAuthMiddleware': 300,
        'scrapy.contrib.downloadermiddleware.downloadtimeout.DownloadTimeoutMiddleware': 350,
        'scrapy.contrib.downloadermiddleware.useragent.UserAgentMiddleware': 400,
        'scrapy.contrib.downloadermiddleware.retry.RetryMiddleware': 500,
        'scrapy.contrib.downloadermiddleware.defaultheaders.DefaultHeadersMiddleware': 550,
        'scrapy.contrib.downloadermiddleware.redirect.MetaRefreshMiddleware': 580,
        'scrapy.contrib.downloadermiddleware.httpcompression.HttpCompressionMiddleware': 590,
        'scrapy.contrib.downloadermiddleware.redirect.RedirectMiddleware': 600,
        'scrapy.contrib.downloadermiddleware.cookies.CookiesMiddleware': 700,
        'scrapy.contrib.downloadermiddleware.httpproxy.HttpProxyMiddleware': 750,
        'scrapy.contrib.downloadermiddleware.chunked.ChunkedTransferMiddleware': 830,
        'scrapy.contrib.downloadermiddleware.stats.DownloaderStats': 850,
        'scrapy.contrib.downloadermiddleware.httpcache.HttpCacheMiddleware': 900,
    }

"""
# from scrapy.contrib.downloadermiddleware.httpauth import HttpAuthMiddleware
# Enable or disable downloader middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
# DOWNLOADER_MIDDLEWARES = {
#    'step8_king.middlewares.DownMiddleware1': 100,
#    'step8_king.middlewares.DownMiddleware2': 500,
# }

十二、爬取亚马逊商品信息

1、
scrapy startproject Amazon
cd Amazon
scrapy genspider spider_goods www.amazon.cn

2、settings.py
ROBOTSTXT_OBEY = False
#请求头
DEFAULT_REQUEST_HEADERS = {
    'Referer':'https://www.amazon.cn/',
    'User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.75 Safari/537.36'
}
#打开注释
HTTPCACHE_ENABLED = True
HTTPCACHE_EXPIRATION_SECS = 0
HTTPCACHE_DIR = 'httpcache'
HTTPCACHE_IGNORE_HTTP_CODES = []
HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'

3、items.py
class GoodsItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    #商品名字
    goods_name = scrapy.Field()
    #价钱
    goods_price = scrapy.Field()
    #配送方式
    delivery_method=scrapy.Field()

4、spider_goods.py
# -*- coding: utf-8 -*-
import scrapy

from Amazon.items import  GoodsItem
from scrapy.http import Request
from urllib.parse import urlencode

class SpiderGoodsSpider(scrapy.Spider):
    name = 'spider_goods'
    allowed_domains = ['www.amazon.cn']
    # start_urls = ['http://www.amazon.cn/']


    def __int__(self,keyword=None,*args,**kwargs):
        super(SpiderGoodsSpider).__init__(*args,**kwargs)
        self.keyword=keyword

    def start_requests(self):
        url='https://www.amazon.cn/s/ref=nb_sb_noss_1?'
        paramas={
            '__mk_zh_CN': '亚马逊网站',
            'url': 'search - alias = aps',
            'field-keywords': self.keyword
        }
        url=url+urlencode(paramas,encoding='utf-8')
        yield Request(url,callback=self.parse_index)


    def parse_index(self, response):
        print('解析索引页:%s' %response.url)

        urls=response.xpath('//*[contains(@id,"result_")]/div/div[3]/div[1]/a/@href').extract()
        for url in urls:
            yield Request(url,callback=self.parse_detail)

        next_url=response.urljoin(response.xpath('//*[@id="pagnNextLink"]/@href').extract_first())
        print('下一页的url',next_url)
        yield Request(next_url,callback=self.parse_index)

    def parse_detail(self,response):
        print('解析详情页:%s' %(response.url))

        item=GoodsItem()
        # 商品名字
        item['goods_name'] = response.xpath('//*[@id="productTitle"]/text()').extract_first().strip()
        # 价钱
        item['goods_price'] = response.xpath('//*[@id="priceblock_ourprice"]/text()').extract_first().strip()
        # 配送方式
        item['delivery_method'] = ''.join(response.xpath('//*[@id="ddmMerchantMessage"]//text()').extract())
        return item

5、自定义pipelines
#sql.py
import pymysql
import settings


MYSQL_HOST=settings.MYSQL_HOST
MYSQL_PORT=settings.MYSQL_PORT
MYSQL_USER=settings.MYSQL_USER
MYSQL_PWD=settings.MYSQL_PWD
MYSQL_DB=settings.MYSQL_DB

conn=pymysql.connect(
    host=MYSQL_HOST,
    port=int(MYSQL_PORT),
    user=MYSQL_USER,
    password=MYSQL_PWD,
    db=MYSQL_DB,
    charset='utf8'
)
cursor=conn.cursor()

class Mysql(object):
    @staticmethod
    def insert_tables_goods(goods_name,goods_price,deliver_mode):
        sql='insert into goods(goods_name,goods_price,delivery_method) values(%s,%s,%s)'
        cursor.execute(sql,args=(goods_name,goods_price,deliver_mode))
        conn.commit()

    @staticmethod
    def is_repeat(goods_name):
        sql='select count(1) from goods where goods_name=%s'
        cursor.execute(sql,args=(goods_name,))
        if cursor.fetchone()[0] >= 1:
            return True

if __name__ == '__main__':
    cursor.execute('select * from goods;')
    print(cursor.fetchall())


#pipelines.py
from Amazon.mysqlpipelines.sql import Mysql


class AmazonPipeline(object):
    def process_item(self, item, spider):
        goods_name=item['goods_name']
        goods_price=item['goods_price']
        delivery_mode=item['delivery_method']
        if not Mysql.is_repeat(goods_name):
            Mysql.insert_table_goods(goods_name,goods_price,delivery_mode)


6、创建数据库表
create database amazon charset utf8;
create table goods(
    id int primary key auto_increment,
    goods_name char(30),
    goods_price char(20),
    delivery_method varchar(50)
);

7、settings.py
MYSQL_HOST='localhost'
MYSQL_PORT='3306'
MYSQL_USER='root'
MYSQL_PWD='123'
MYSQL_DB='amazon'


#数字代表优先级程度（1-1000随意设置，数值越低，组件的优先级越高）
ITEM_PIPELINES = {
   'Amazon.mysqlpipelines.pipelines.mazonPipeline': 1,
}


#8、在项目目录下新建：entrypoint.py
from scrapy.cmdline import execute
execute(['scrapy', 'crawl', 'spider_goods','-a','keyword=iphone8'])

https://pan.baidu.com/s/1boCEBT1