增量式爬虫的入门框架解析，scrapy-redis 的运行方式 1、创建scrapy项目命令
scrapy startproject myproject 2、在项目中创建一个新的spider文件命令：
scrapy genspider mydomain mydomain.com #mydomain为spider文件名 ，mydomain.com为爬取网站域名 3 、运行项目命令
scrapy crawl scrapy runspider #运行spider第二种方法 4 、检查spider文件有无语法错误
scrapy check 5、其他的语法
scrapy crawl --nolog #运行spider文件 不显示日志 scrapy list #列出spider路径下的spider文件 scrapy fetch #将网页内容下载下来 ，然后在终端打印当前返回的内容，相当于 request 和 urllib 方法 scrapy view #将网页内容保存下来 ，并在浏览器中打开当前网页内容 ，直观呈现要爬取网页的内容 scrapy shell [url] #打开 scrapy 显示台，类似ipython ，可以用来做测试 scrapy parse [options] #输出格式化内容 scrapy settings [options] #返回系统设置信息 scrapy bench #测试电脑当前爬取速度性能 1 、以当当网为例爬取信息如下 ，首先文件的结构目录如下所示
E:. │ dangdang_content.sql │ scrapy.cfg │ ├─.idea │ │ misc.xml │ │ modules.xml │ │ ScrapyRedisPro.iml │ │ workspace.xml │ │ │ └─libraries │ R_User_Library.xml │ └─ScrapyRedisPro │ items.py │ middlewares.py │ pipelines.py │ settings.py │ test.py │ __init__.py │ ├─.idea │ │ misc.xml │ │ modules.xml │ │ ScrapyRedisPro.iml │ │ workspace.xml │ │ │ └─libraries │ R_User_Library.xml │ ├─spiders │ │ test.py │ │ __init__.py │ │ │ └─__pycache__ │ test.cpython-36.pyc │ __init__.cpython-36.pyc │ └─__pycache__ items.cpython-36.pyc middlewares.cpython-36.pyc pipelines.cpython-36.pyc settings.cpython-36.pyc __init__.cpython-36.pyc 2 、mysql数据库数据结构
SET NAMES utf8mb4; SET FOREIGN_KEY_CHECKS = 0; -- ---------------------------- -- Table structure for dangdang_content -- ---------------------------- DROP TABLE IF EXISTS `dangdang_content`; CREATE TABLE `dangdang_content` ( `id` int NOT NULL AUTO_INCREMENT, `b_cate` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL, `m_cate` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL, `s_href` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL, `s_cate` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL, `book_img` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL, `book_name` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL, `book_desc` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL, `book_price` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL, `book_author` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL, `book_publish_date` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL, `book_press` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL, `insert_data` timestamp(0) NULL DEFAULT CURRENT_TIMESTAMP(0) ON UPDATE CURRENT_TIMESTAMP(0), PRIMARY KEY (`id`) USING BTREE ) ENGINE = InnoDB CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic; SET FOREIGN_KEY_CHECKS = 1; 1、spider 爬虫项目文件test.py 如下所示
# -*- coding: utf-8 -*- import scrapy from scrapy_redis.spiders import RedisCrawlSpider from ScrapyRedisPro.items import ScrapyredisproItem from copy import deepcopy import urllib class TestSpider(RedisCrawlSpider): name = 'test' # allowed_domains = ['www.baidu.com'] # start_urls = ['http://www.baidu.com/'] #调度器队列名称 redis_key = 'dangdang' def parse(self, response): """ 逻辑分析 1.通过抓取下一页的链接，交给scrapy实现自动翻页,如果没有下一页则爬取完成 2.将本页面的所有文章url爬下 ，并交给scrapy进行深入详情页的爬取 """ # 大分类分组 div_list = response.xpath("//div[@class='con flq_body']/div") for div in div_list: item = {} item["b_cate"] = div.xpath("./dl/dt//text()").extract() item["b_cate"] = [i.strip() for i in item["b_cate"] if len(i.strip()) > 0] # 中间分类分组 dl_list = div.xpath("./div//dl[@class='inner_dl']") for dl in dl_list: item["m_cate"] = dl.xpath("./dt//text()").extract() item["m_cate"] = [i.strip() for i in item["m_cate"] if len(i.strip()) > 0][0] # 小分类分组 a_list = dl.xpath("./dd/a") for a in a_list: item["s_href"] = a.xpath("./@href").extract_first() item["s_cate"] = a.xpath("./text()").extract_first() if item["s_href"] is not None: # print(item) yield scrapy.Request( item["s_href"], callback=self.parse_book_list, meta={"item": deepcopy(item)} ) def parse_book_list(self, response): """ 将爬虫爬取的数据送到item中进行序列化 这里通过ItemLoader加载item """ item = response.meta["item"] li_list = response.xpath("//ul[@class='bigimg']/li") for li in li_list: item["book_img"] = li.xpath("./a[@class='pic']/img/@src").extract_first() if item["book_img"] == "images/model/guan/url_none.png": item["book_img"] = li.xpath("./a[@class='pic']/img/@data-original").extract_first() item["book_name"] = li.xpath("./p[@class='name']/a/@title").extract_first() item["book_desc"] = li.xpath("./p[@class='detail']/text()").extract_first() item["book_price"] = li.xpath(".//span[@class='search_now_price']/text()").extract_first() item["book_author"] = li.xpath("./p[@class='search_book_author']/span[1]/a/text()").extract() item["book_publish_date"] = li.xpath("./p[@class='search_book_author']/span[2]/text()").extract_first() item["book_press"] = li.xpath("./p[@class='search_book_author']/span[3]/a/text()").extract_first() # print(item) yield item # 下一页 next_url = response.xpath("//li[@class='next']/a/@href").extract_first() if next_url is not None: next_url = urllib.parse.urljoin(response.url, next_url) yield scrapy.Request( next_url, callback=self.parse_book_list, meta={"item": item} ) Middlewware.py 中间件文件
# -*- coding: utf-8 -*- # Define here the models for your spider middleware # # See documentation in: # https://doc.scrapy.org/en/latest/topics/spider-middleware.html from scrapy import signals from scrapy.http import HtmlResponse import time from scrapy.downloadermiddlewares.useragent import UserAgentMiddleware import random class ScrapyredisproSpiderMiddleware(object): # Not all methods need to be defined. If a method is not defined, # scrapy acts as if the spider middleware does not modify the # passed objects. @classmethod def from_crawler(cls, crawler): # This method is used by Scrapy to create your spiders. s = cls() crawler.signals.connect(s.spider_opened, signal=signals.spider_opened) return s def process_spider_input(self, response, spider): # Called for each response that goes through the spider # middleware and into the spider. # Should return None or raise an exception. return None def process_spider_output(self, response, result, spider): # Called with the results returned from the Spider, after # it has processed the response. # Must return an iterable of Request, dict or Item objects. for i in result: yield i def process_spider_exception(self, response, exception, spider): # Called when a spider or process_spider_input() method # (from other spider middleware) raises an exception. # Should return either None or an iterable of Response, dict # or Item objects. pass def process_start_requests(self, start_requests, spider): # Called with the start requests of the spider, and works # similarly to the process_spider_output() method, except # that it doesn’t have a response associated. # Must return only requests (not items). for r in start_requests: yield r def spider_opened(self, spider): spider.logger.info('Spider opened: %s' % spider.name) class ScrapyredisproDownloaderMiddleware(object): # Not all methods need to be defined. If a method is not defined, # scrapy acts as if the downloader middleware does not modify the # passed objects. @classmethod def from_crawler(cls, crawler): # This method is used by Scrapy to create your spiders. s = cls() crawler.signals.connect(s.spider_opened, signal=signals.spider_opened) return s def process_request(self, request, spider): # Called for each request that goes through the downloader # middleware. # Must either: # - return None: continue processing this request # - or return a Response object # - or return a Request object # - or raise IgnoreRequest: process_exception() methods of # installed downloader middleware will be called return None # 拦截到响应对象（下载器传递给Spider的响应对象） # request：响应对象对应的请求对象 # response：拦截到的响应对象 # spider：爬虫文件中对应的爬虫类的实例 def process_response(self, request, response, spider): # 响应对象中存储页面数据的篡改 if request.url in ['http://news.163.com/domestic/', 'http://news.163.com/world/', 'http://news.163.com/air/', 'http://war.163.com/']: spider.bro.get(url=request.url) js = 'window.scrollTo(0,document.body.scrollHeight)' spider.bro.execute_script(js) time.sleep(3) # 一定要给与浏览器一定的缓冲加载数据的时间 # 页面数据就是包含了动态加载出来的新闻数据对应的页面数据 page_text = spider.bro.page_source # 篡改响应对象 return HtmlResponse(url=spider.bro.current_url, body=page_text, encoding='utf-8', request=request) else: return response def process_exception(self, request, exception, spider): # Called when a download handler or a process_request() # (from other downloader middleware) raises an exception. # Must either: # - return None: continue processing this exception # - return a Response object: stops process_exception() chain # - return a Request object: stops process_exception() chain pass def spider_opened(self, spider): spider.logger.info('Spider opened: %s' % spider.name) #UA池代码的编写（单独给UA池封装一个下载中间件的一个类） #1 ，导包UserAgentMiddlware类 class RandomUserAgent(UserAgentMiddleware): def process_request(self, request, spider): #从列表中随机抽选出一个ua值 ua = random.choice(user_agent_list) #ua值进行当前拦截到请求的ua的写入操作 request.headers.setdefault('User-Agent',ua) #批量对拦截到的请求进行ip更换 class Proxy(object): def process_request(self, request, spider): #对拦截到请求的url进行判断（协议头到底是http还是https） #request.url返回值：http://www.xxx.com h = request.url.split(':')[0] #请求的协议头 if h == 'https': ip = random.choice(PROXY_https) request.meta['proxy'] = 'https://'+ip else: ip = random.choice(PROXY_http) request.meta['proxy'] = 'http://' + ip PROXY_http = [ '153.180.102.104:80', '195.208.131.189:56055', ] PROXY_https = [ '120.83.49.90:9000', '95.189.112.214:35508', ] user_agent_list = [ "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 " "(KHTML, like Gecko) Chrome/22.0.1207.1 Safari/537.1", "Mozilla/5.0 (X11; CrOS i686 2268.111.0) AppleWebKit/536.11 " "(KHTML, like Gecko) Chrome/20.0.1132.57 Safari/536.11", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.6 " "(KHTML, like Gecko) Chrome/20.0.1092.0 Safari/536.6", "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.6 " "(KHTML, like Gecko) Chrome/20.0.1090.0 Safari/536.6", "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.1 " "(KHTML, like Gecko) Chrome/19.77.34.5 Safari/537.1", "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/536.5 " "(KHTML, like Gecko) Chrome/19.0.1084.9 Safari/536.5", "Mozilla/5.0 (Windows NT 6.0) AppleWebKit/536.5 " "(KHTML, like Gecko) Chrome/19.0.1084.36 Safari/536.5", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 " "(KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3", "Mozilla/5.0 (Windows NT 5.1) AppleWebKit/536.3 " "(KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 " "(KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3", "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 " "(KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 " "(KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3", "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 " "(KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 " "(KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3", "Mozilla/5.0 (Windows NT 6.1) AppleWebKit/536.3 " "(KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3", "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 " "(KHTML, like Gecko) Chrome/19.0.1061.0 Safari/536.3", "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.24 " "(KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24", "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/535.24 " "(KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24" ] 3 、items.py 文件
# -*- coding: utf-8 -*- # Define here the models for your scraped items # # See documentation in: # https://doc.scrapy.org/en/latest/topics/items.html import scrapy class ScrapyredisproItem(scrapy.Item): # define the fields for your item here like: # name = scrapy.Field() b_cate = scrapy.Field() m_cate = scrapy.Field() s_href = scrapy.Field() s_cate = scrapy.Field() book_img = scrapy.Field() book_name = scrapy.Field() book_desc = scrapy.Field() book_price = scrapy.Field() book_author = scrapy.Field() book_publish_date = scrapy.Field() book_press = scrapy.Field() 4 、pipelines.py 管道文件
注意 一般下载方式有两种，异步与同步下载方式（下列两种方式都有）
# -*- coding: utf-8 -*- # Define your item pipelines here # # Don't forget to add your pipeline to the ITEM_PIPELINES setting # See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html import pymysql.cursors from twisted.enterprise import adbapi class ScrapyredisproPipeline(object): # def process_item(self, item, spider): # return item # class MysqlTwistedPipeline(object): ''' 异步机制将数据写入到mysql数据库中 ''' # 创建初始化函数 ，当通过此类创建对象时首先被调用的方法 def __init__(self, dbpool): self.dbpool = dbpool # 创建一个静态方法,静态方法的加载内存优先级高于init方法 ， # 在创建这个类的对之前就已将加载到了内存中，所以init这个方法可以调用这个方法产生的对象 @classmethod # 名称固定的 def from_settings(cls, settings): # 先将setting中连接数据库所需内容取出，构造一个地点 dbparms = dict( host=settings["MYSQL_HOST"], port=settings["MYSQL_PORT"], db=settings["MYSQL_DBNAME"], user=settings["MYSQL_USER"], password=settings["MYSQL_PASSWORD"], charset='utf8', # 游标设置 cursorclass=pymysql.cursors.DictCursor, # 设置编码是否使用Unicode use_unicode=True ) # 通过Twisted框架提供的容器连接数据库,pymysql是数据库模块名 dbpool = adbapi.ConnectionPool("pymysql",**dbparms) print("连接成功！") # 无需直接导入 dbmodule. 只需要告诉 adbapi.ConnectionPool 构造器你用的数据库模块的名称比如pymysql. return cls(dbpool) def process_item(self, item, spider): # 使用Twisted异步的将Item数据插入数据库 query = self.dbpool.runInteraction(self.do_insert, item) query.addErrback(self.handle_error, item, spider) # 这里不往下传入item,spider ，handle_error则不需接受,item,spider) def do_insert(self, cursor, item): # 执行具体的插入语句,不需要commit操作,Twisted会自动进行 insert_sql = """ insert into dangdang_content(b_cate, m_cate, s_href, s_cate, book_img, book_name, book_desc, book_price, book_author, book_publish_date, book_press) VALUES(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s) """ cursor.execute(insert_sql, (item["b_cate"][0], item["m_cate"], item["book_img"], item["s_href"], item["s_cate"], item["book_name"], item["book_desc"], item["book_price"], item["book_author"][0], item["book_publish_date"], item["book_press"])) print("------------------------------数据插入成功！") def handle_error(self, failure, item, spider): # 异步插入异常 if failure: print(failure) # class MysqlTwistedPipeline(object): # ''' # 同步步机制将数据写入到mysql数据库中 # ''' # # # 创建初始化函数 ，当通过此类创建对象时首先被调用的方法 # def __init__(self, conn, cursor): # self.conn = conn # self.cursor = cursor # # # 创建一个静态方法,静态方法的加载内存优先级高于init方法， # # 在创建这个类的对之前就已将加载到了内存中 ，所以init这个方法可以调用这个方法产生的对象 # @classmethod # # 名称固定的 # def from_settings(cls, settings): # # 先将setting中连接数据库所需内容取出 ，构造一个地点 # dbparms = dict( # host=settings["MYSQL_HOST"], # port=settings["MYSQL_PORT"], # db=settings["MYSQL_DBNAME"], # user=settings["MYSQL_USER"], # password=settings["MYSQL_PASSWORD"], # charset='utf8', # # 游标设置 # cursorclass=pymysql.cursors.DictCursor, # # 设置编码是否使用Unicode # use_unicode=True # ) # conn = pymysql.connect(**dbparms) # cursor = conn.cursor() # # 无需直接导入 dbmodule. 只需要告诉 adbapi.ConnectionPool 构造器你用的数据库模块的名称比如pymysql. # return cls(conn, cursor) # # def process_item(self, item, spider): # insert_sql = 'insert into dangdang_content(b_cate[0], m_cate, s_href, s_cate, book_img, book_name, book_desc, book_price, book_author, book_publish_date, book_press) VALUES(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)'.format(item["b_cate"], item["m_cate"], item["book_img"], item["s_href"], item["s_cate"], item["book_name"], item["book_desc"], item["book_price"], item["book_author"][0], item["book_publish_date"], item["book_press"]) # print(insert_sql) # self.cursor.execute(insert_sql) # self.conn.commit() # print("------------------------------数据插入成功！") # # def handle_error(self, failure, item, spider): # # 异步插入异常 # if failure: # print(failure) # # def close_spider(self, spider): # """ # 清理 # :param spider: # :return: # """ # self.cursor.close() # self.conn.close() 5、settings.py 配置文件
# -*- coding: utf-8 -*- # Scrapy settings for ScrapyRedisPro project # # For simplicity, this file contains only settings considered important or # commonly used. You can find more settings consulting the documentation: # # https://doc.scrapy.org/en/latest/topics/settings.html # https://doc.scrapy.org/en/latest/topics/downloader-middleware.html # https://doc.scrapy.org/en/latest/topics/spider-middleware.html BOT_NAME = 'ScrapyRedisPro' SPIDER_MODULES = ['ScrapyRedisPro.spiders'] NEWSPIDER_MODULE = 'ScrapyRedisPro.spiders' # Crawl responsibly by identifying yourself (and your website) on the user-agent #USER_AGENT = 'ScrapyRedisPro (+http://www.yourdomain.com)' USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.198 Safari/537.36' # 伪装请求载体身份 # Obey robots.txt rules ROBOTSTXT_OBEY = False #可以忽略或者不遵守robots协议 #只显示指定类型的日志信息 LOG_LEVEL='ERROR' # Configure maximum concurrent requests performed by Scrapy (default: 16) #CONCURRENT_REQUESTS = 32 # Configure a delay for requests for the same website (default: 0) # See https://doc.scrapy.org/en/latest/topics/settings.html#download-delay # See also autothrottle settings and docs #DOWNLOAD_DELAY = 3 # The download delay setting will honor only one of: #CONCURRENT_REQUESTS_PER_DOMAIN = 16 #CONCURRENT_REQUESTS_PER_IP = 16 # Disable cookies (enabled by default) #COOKIES_ENABLED = False # Disable Telnet Console (enabled by default) #TELNETCONSOLE_ENABLED = False # 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', #} # Enable or disable spider middlewares # See https://doc.scrapy.org/en/latest/topics/spider-middleware.html #SPIDER_MIDDLEWARES = { # 'ScrapyRedisPro.middlewares.ScrapyredisproSpiderMiddleware': 543, #} # Enable or disable downloader middlewares # See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html DOWNLOADER_MIDDLEWARES = { 'ScrapyRedisPro.middlewares.ScrapyredisproDownloaderMiddleware': 543, 'ScrapyRedisPro.middlewares.RandomUserAgent': 542, } # Enable or disable extensions # See https://doc.scrapy.org/en/latest/topics/extensions.html #EXTENSIONS = { # 'scrapy.extensions.telnet.TelnetConsole': None, #} # Configure item pipelines # See https://doc.scrapy.org/en/latest/topics/item-pipeline.html ITEM_PIPELINES = { 'ScrapyRedisPro.pipelines.ScrapyredisproPipeline': 300, 'scrapy_redis.pipelines.RedisPipeline': 400 , # 'ScrapyRedisPro.pipelines.MysqlTwistedPipeline': 301, } # Enable and configure the AutoThrottle extension (disabled by default) # See https://doc.scrapy.org/en/latest/topics/autothrottle.html #AUTOTHROTTLE_ENABLED = True # The initial download delay #AUTOTHROTTLE_START_DELAY = 5 # The maximum download delay to be set in case of high latencies #AUTOTHROTTLE_MAX_DELAY = 60 # The average number of requests Scrapy should be sending in parallel to # each remote server #AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0 # Enable showing throttling stats for every response received: #AUTOTHROTTLE_DEBUG = False # Enable and configure HTTP caching (disabled by default) # See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings #HTTPCACHE_ENABLED = True #HTTPCACHE_EXPIRATION_SECS = 0 #HTTPCACHE_DIR = 'httpcache' #HTTPCACHE_IGNORE_HTTP_CODES = [] #HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage' """ scrapy-redis配置 """ # Enables scheduling storing requests queue in redis. # 使用scrapy-redis组件自己的调度器 SCHEDULER = "scrapy_redis.scheduler.Scheduler" # 增加了一个去重容器类的配置, 作用使用Redis的set集合来存储请求的指纹数据, 从而实现请求去重的持久化 # Ensure all spiders share same duplicates filter through redis. DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter" # 配置调度器是否要持久化, 也就是当爬虫结束了, 要不要清空Redis中请求队列和去重指纹的set。如果是True, 就表示要持久化存储, 就不清空数据, 否则清空数据 SCHEDULER_PERSIST = True # 为false Redis关闭了 Redis数据也会被清空 # redis的配置 REDIS_HOST = '127.0.0.1' REDIS_PORT = 6379 REDIS_ENCODING ='utf8' REDIS_PARAMS = {'password':'xhw123'} MYSQL_HOST = '127.0.0.1' MYSQL_PORT = 3306 MYSQL_DBNAME = 'spidertest' MYSQL_USER = 'root' MYSQL_PASSWORD = 'xhw123' # 增加了一个去重容器类的配置, 作用使用Redis的set集合来存储请求的指纹数据, 从而实现请求去重的持久化 DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter" # 使用scrapy-redis组件自己的调度器 SCHEDULER = "scrapy_redis.scheduler.Scheduler" # 配置调度器是否要持久化, 也就是当爬虫结束了, 要不要清空Redis中请求队列和去重指纹的set 。如果是True, 就表示要持久化存储, 就不清空数据, 否则清空数据 SCHEDULER_PERSIST = True 注意 启动项目后需要在redis的客户端执行如下命令
127.0.0.1:6379> lpush dangdang http://book.dangdang.com/ 