更新了Scrapy的相关文档
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## 解析动态内容
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### JavaScript逆向工程
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### 使用Selenium
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## 表单交互和验证码处理
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### 提交表单
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#### 手动提交
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#### 自动提交
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### 验证码处理
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#### 加载验证码
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#### 光学字符识别
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光学字符识别(OCR)是从图像中抽取文本的工具,可以应用于公安、电信、物流、金融等诸多行业,例如识别车牌,身份证扫描识别、名片信息提取等。在爬虫开发中,如果遭遇了有文字验证码的表单,就可以利用OCR来进行验证码处理。Tesseract-OCR引擎最初是由惠普公司开发的光学字符识别系统,目前发布在Github上,由Google赞助开发。
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![](./res/tesseract.gif)
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#### 改善OCR
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#### 处理更复杂的验证码
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#### 验证码处理服务
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### Scrapy概述
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Scrapy是Python开发的一个非常流行的网络爬虫框架,可以用来抓取Web站点并从页面中提取结构化的数据,被广泛的用于数据挖掘、数据监测和自动化测试等领域。下图展示了Scrapy的基本架构,其中包含了主要组件和系统的数据处理流程(图中的绿色箭头)。
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Scrapy是Python开发的一个非常流行的网络爬虫框架,可以用来抓取Web站点并从页面中提取结构化的数据,被广泛的用于数据挖掘、数据监测和自动化测试等领域。下图展示了Scrapy的基本架构,其中包含了主要组件和系统的数据处理流程(图中带数字的红色箭头)。
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![](./res/scrapy-architecture.jpg)
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![](./res/scrapy-architecture.png)
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#### 组件
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Scrapy的整个数据处理流程由Scrapy引擎进行控制,通常的运转流程包括以下的步骤:
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1. 引擎询问蜘蛛需要处理哪个网站,并让蜘蛛将第一个需要处理的URL交给它。
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2. 引擎让调度器将需要处理的URL放在队列中。
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3. 引擎从调度那获取接下来进行爬取的页面。
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4. 调度将下一个爬取的URL返回给引擎,引擎将它通过下载中间件发送到下载器。
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5. 当网页被下载器下载完成以后,响应内容通过下载中间件被发送到引擎;如果下载失败了,引擎会通知调度器记录这个URL,待会再重新下载。
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6. 引擎收到下载器的响应并将它通过蜘蛛中间件发送到蜘蛛进行处理。
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7. 蜘蛛处理响应并返回爬取到的数据条目,此外还要将需要跟进的新的URL发送给引擎。
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8. 引擎将抓取到的数据条目送入条目管道,把新的URL发送给调度器放入队列中。
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9. 上述操作会一直重复直到调度器中没有需要请求的URL,爬虫停止工作。
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上述操作中的2-8步会一直重复直到调度器中没有需要请求的URL,爬虫停止工作。
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### 安装和使用Scrapy
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@ -45,7 +53,7 @@ $
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(venv) $ tree
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.
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|____ scrapy.cfg
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|____ qianmu
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|____ douban
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| |____ spiders
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| | |____ __init__.py
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| | |____ __pycache__
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根据刚才描述的数据处理流程,基本上需要我们做的有以下几件事情:
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1. 在items.py文件中定义字段,这些字段用来保存数据,方便后续的操作。
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```Python
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# -*- coding: utf-8 -*-
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# Define here the models for your scraped items
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#
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# See documentation in:
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# https://doc.scrapy.org/en/latest/topics/items.html
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import scrapy
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class DoubanItem(scrapy.Item):
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name = scrapy.Field()
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year = scrapy.Field()
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score = scrapy.Field()
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director = scrapy.Field()
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classification = scrapy.Field()
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actor = scrapy.Field()
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```
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2. 在spiders文件夹中编写自己的爬虫。
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```Python
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# -*- coding: utf-8 -*-
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import scrapy
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from scrapy.selector import Selector
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from scrapy.linkextractors import LinkExtractor
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from scrapy.spiders import CrawlSpider, Rule
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from douban.items import DoubanItem
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class MovieSpider(CrawlSpider):
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name = 'movie'
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allowed_domains = ['movie.douban.com']
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start_urls = ['https://movie.douban.com/top250']
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rules = (
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Rule(LinkExtractor(allow=(r'https://movie.douban.com/top250\?start=\d+.*'))),
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Rule(LinkExtractor(allow=(r'https://movie.douban.com/subject/\d+')), callback='parse_item'),
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)
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def parse_item(self, response):
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sel = Selector(response)
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item = DoubanItem()
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item['name']=sel.xpath('//*[@id="content"]/h1/span[1]/text()').extract()
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item['year']=sel.xpath('//*[@id="content"]/h1/span[2]/text()').re(r'\((\d+)\)')
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item['score']=sel.xpath('//*[@id="interest_sectl"]/div/p[1]/strong/text()').extract()
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item['director']=sel.xpath('//*[@id="info"]/span[1]/a/text()').extract()
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item['classification']= sel.xpath('//span[@property="v:genre"]/text()').extract()
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item['actor']= sel.xpath('//*[@id="info"]/span[3]/a[1]/text()').extract()
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return item
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```
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3. 在pipelines.py中完成对数据进行持久化的操作。
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```Python
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# -*- coding: utf-8 -*-
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# Define your item pipelines here
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#
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# Don't forget to add your pipeline to the ITEM_PIPELINES setting
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# See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html
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import pymongo
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from scrapy.exceptions import DropItem
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from scrapy.conf import settings
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from scrapy import log
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class DoubanPipeline(object):
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def __init__(self):
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connection = pymongo.MongoClient(settings['MONGODB_SERVER'], settings['MONGODB_PORT'])
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db = connection[settings['MONGODB_DB']]
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self.collection = db[settings['MONGODB_COLLECTION']]
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def process_item(self, item, spider):
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#Remove invalid data
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valid = True
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for data in item:
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if not data:
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valid = False
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raise DropItem("Missing %s of blogpost from %s" %(data, item['url']))
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if valid:
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#Insert data into database
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new_moive=[{
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"name":item['name'][0],
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"year":item['year'][0],
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"score":item['score'],
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"director":item['director'],
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"classification":item['classification'],
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"actor":item['actor']
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}]
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self.collection.insert(new_moive)
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log.msg("Item wrote to MongoDB database %s/%s" %
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(settings['MONGODB_DB'], settings['MONGODB_COLLECTION']),
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level=log.DEBUG, spider=spider)
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return item
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```
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4. 修改settings.py文件对项目进行配置。
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```Python
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# -*- coding: utf-8 -*-
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# Scrapy settings for douban project
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#
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# For simplicity, this file contains only settings considered important or
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# commonly used. You can find more settings consulting the documentation:
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#
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# https://doc.scrapy.org/en/latest/topics/settings.html
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# https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
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# https://doc.scrapy.org/en/latest/topics/spider-middleware.html
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BOT_NAME = 'douban'
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SPIDER_MODULES = ['douban.spiders']
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NEWSPIDER_MODULE = 'douban.spiders'
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# Crawl responsibly by identifying yourself (and your website) on the user-agent
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USER_AGENT = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_3) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.54 Safari/536.5'
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# Obey robots.txt rules
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ROBOTSTXT_OBEY = True
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# Configure maximum concurrent requests performed by Scrapy (default: 16)
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# CONCURRENT_REQUESTS = 32
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# Configure a delay for requests for the same website (default: 0)
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# See https://doc.scrapy.org/en/latest/topics/settings.html#download-delay
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# See also autothrottle settings and docs
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DOWNLOAD_DELAY = 3
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RANDOMIZE_DOWNLOAD_DELAY = True
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# The download delay setting will honor only one of:
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# CONCURRENT_REQUESTS_PER_DOMAIN = 16
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# CONCURRENT_REQUESTS_PER_IP = 16
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# Disable cookies (enabled by default)
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COOKIES_ENABLED = True
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MONGODB_SERVER = '120.77.222.217'
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MONGODB_PORT = 27017
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MONGODB_DB = 'douban'
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MONGODB_COLLECTION = 'movie'
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# Disable Telnet Console (enabled by default)
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# TELNETCONSOLE_ENABLED = False
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# Override the default request headers:
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# DEFAULT_REQUEST_HEADERS = {
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# 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
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# 'Accept-Language': 'en',
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# }
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# Enable or disable spider middlewares
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# See https://doc.scrapy.org/en/latest/topics/spider-middleware.html
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# SPIDER_MIDDLEWARES = {
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# 'douban.middlewares.DoubanSpiderMiddleware': 543,
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# }
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# Enable or disable downloader middlewares
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# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
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# DOWNLOADER_MIDDLEWARES = {
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# 'douban.middlewares.DoubanDownloaderMiddleware': 543,
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# }
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# Enable or disable extensions
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# See https://doc.scrapy.org/en/latest/topics/extensions.html
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# EXTENSIONS = {
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# 'scrapy.extensions.telnet.TelnetConsole': None,
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# }
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# Configure item pipelines
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# See https://doc.scrapy.org/en/latest/topics/item-pipeline.html
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ITEM_PIPELINES = {
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'douban.pipelines.DoubanPipeline': 400,
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}
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LOG_LEVEL = 'DEBUG'
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# Enable and configure the AutoThrottle extension (disabled by default)
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# See https://doc.scrapy.org/en/latest/topics/autothrottle.html
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#AUTOTHROTTLE_ENABLED = True
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# The initial download delay
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#AUTOTHROTTLE_START_DELAY = 5
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# The maximum download delay to be set in case of high latencies
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#AUTOTHROTTLE_MAX_DELAY = 60
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# The average number of requests Scrapy should be sending in parallel to
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# each remote server
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#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
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# Enable showing throttling stats for every response received:
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#AUTOTHROTTLE_DEBUG = False
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# Enable and configure HTTP caching (disabled by default)
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# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
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HTTPCACHE_ENABLED = True
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HTTPCACHE_EXPIRATION_SECS = 0
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HTTPCACHE_DIR = 'httpcache'
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HTTPCACHE_IGNORE_HTTP_CODES = []
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HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
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```
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