Redis实现分布式爬虫

redis分布式爬虫 

概念：多台机器上可以执行同一个爬虫程序,实现网站数据的爬取
原生的scrapy是不可以实现分布式爬虫, 原因如下：

• 调度器无法共享
• 管道无法共享

scrapy-redis组件：专门为scrapy开发的一套组件。 该组件可以让scrapy实现分布式 pip install scrapy-redis

分布式爬取的流程：

1 redis配置文件的配置

• 　将 bind 127.0.0.1 进行注释
• 　将 protected-mode no 关闭保护模式

2 redis服务器的开启：基于配置文件的开启

3 创建scrapy工程后， 创建基于crawlSpider的爬虫文件

4 导入RedisCrawSpider类 from scrapy_redis.spiders import RedisCrawlSpider

5 将start_url修改成redis_key = 'xxx'

6 解析代码编写

7 将项目的管道和调度器配置成基于scrapy-redis组件中

ITEM_PIPELINES = {
    'scrapy_redis.pipelines.RedisPipeline': 400
}
# 使用scrapy-redis组件的去重队列
DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"
# 使用scrapy-redis组件自己的调度器
SCHEDULER = "scrapy_redis.scheduler.Scheduler"
# 是否允许暂停
SCHEDULER_PERSIST = True

 8 配置Redis服务器地址和端口

# 如果redis服务器不在本机，则需如下配置
REDIS_HOST = '192.168.0.108'
REDIS_PORT = 6379
REDIS_PARAMS = {"password":123456}

9 执行爬虫文件

scrapy runspider qiubai

10 向调度器队列中扔入一个起始url（在redis客户端中操作）：lpush redis_key属性值 起始url

lpush qiubaispider https://www.qiushibaike.com/pic/

实现代码

class QiubaiSpider(RedisCrawlSpider):
    name = 'qiubai'
    # allowed_domains = ['www.qiushibaike.com/pic']
    # start_urls = ['http://www.qiushibaike.com/pic/']
    redis_key = 'qiubaispider'  # 表示跟start_urls含义一样
    link = LinkExtractor(allow=r'/pic/page/d+')
    rules = (
        Rule(link, callback='parse_item', follow=True),
    )

    def parse_item(self, response):
        print('开始爬虫')
        div_list = response.xpath('//*[@id="content-left"]/div')
        for div in div_list:
            print(div)
            img_url = "http://" + div.xpath('.//div[@class="thumb"]/a/img/@src').extract_first()
            item = RedisproItem()
            item['img_url'] = img_url
            yield item

基于RedisSpider的分布式爬虫

案例需求：爬取的是基于文字的新闻数据(国内, 国际，军师， 航空)

• 1 在爬虫文件中导入webdriver类
• 2 在爬虫文件的爬虫类的构造方法中进行了浏览器实例化操作
• 3 在爬虫类的closed方法中进行浏览器的关闭操作
• 4 在下载中间件的process_response方法中编写执行浏览器自动化操作

wangyi.py：

# -*- coding: utf-8 -*-
import scrapy
from selenium import webdriver
from wanyiPro.items import WanyiproItem
from scrapy_redis.spiders import RedisSpider


class WangyiSpider(RedisSpider):
    name = 'wangyi'
    # allowed_domains = ['news.163.com']
    # start_urls = ['https://news.163.com/']
    redis_key = "wangyi"

    def __init__(self):
        # 实例化一个浏览器对象
        self.bro = webdriver.Chrome(executable_path='G:myprogram路飞学城第七模块wanyiProchromedriver.exe')

    # 必须在整个爬虫结束后关闭浏览器
    def closed(self, spider):
        print('爬虫结束')
        self.bro.quit()

    def parse(self, response):
        lis = response.xpath('//div[@class="ns_area list"]/ul/li')
        indexs = [3, 4, 6, 7]
        li_list = []  # 存储的就是国内 国际 军事 航空四个板块对应的li标签对象
        for index in indexs:
            li_list.append(lis[index])
        # 获取四个板块中的链接和文字标题

        for li in li_list:
            url = li.xpath('./a/@href').extract_first()
            title = li.xpath('./a/text()').extract_first()
            # print(url+":"+title)
            # 对每一个板块对应的url发起请求，获取页面数据(标题， 缩略图， 关键字， 发布时间，  url)
            yield scrapy.Request(url=url, callback=self.parseSecond, meta={'title': title})

    def parseSecond(self, response):
        div_list = response.xpath('//div[@class="data_row news_article clearfix "]')
        for div in div_list:
            head = div.xpath('.//div[@class="news_title"]/h3/a/text()').extract_first()
            url = div.xpath('.//div[@class="news_title"]/h3/a/@href').extract_first()
            img_url = div.xpath('./a/img/@src').extract_first()
            tag_list = div.xpath('.//div[@class="news_tag"]//text()').extract()
            tags = []
            for t in tag_list:
                t = t.strip('
 	')
                tags.append(t)
            tag = "".join(tags)
            # 获取meta传递的数据值title
            title = response.meta['title']
            print(head + ":" + url + ":" + img_url)
            # 实例化item对象, 将解析到的数据值存储在item中
            item = WanyiproItem()
            item['head'] = head
            item['url'] = url
            item['imgUrl'] = img_url
            item['tag'] = tag
            item['title'] = title
            # 对url发起请求 解析新闻详细内容
            yield scrapy.Request(url=url, callback=self.getContent, meta={'item': item})

    def getContent(self, response):
        # 获取传递过来的item
        item = response.meta['item']
        # 解析当前页面中存储的新闻数据
        content_list = response.xpath('//div[@class="post_text"]/p/text()').extract()
        content = "".join(content_list)
        item['content'] = content
        yield item

middlewares.py:

from scrapy import signals
from scrapy.http import HtmlResponse
class WanyiproDownloaderMiddleware(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.

    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

    def process_response(self, request, response, spider):
        # 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: 爬虫文件对应的爬虫类的实例
        print(request.url + "这是下载中间件")
        # 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://war.163.com/',
                           'http://news.163.com/air/']:
            spider.bro.get(url=request.url)
            js = 'window.scrollTo(0,document.body.scrollHeight)'
            spider.bro.execute_script(js)
            time.sleep(2)  # 一定要给与浏览器一定的缓冲加载数据的时间
            # 页面数据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
            return HtmlResponse(url=spider.bro.current_url, body=page_text, encoding='utf-8', request=request)
        else:
            return response

UA池和地址池：

from scrapy import signals
from scrapy.http import HtmlResponse
from scrapy.downloadermiddlewares.useragent import UserAgentMiddleware
import random

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"
]

# 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）
# 导包UserAgentMiddleware类
class RandomUserAgent(UserAgentMiddleware):
    def process_request(self, request, spider):
        # 从列表中随机抽选一个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)


# 可被选用的代理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',
]

# 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

基于RedisSpider实现分布式爬虫步骤

1 导包：from scrapy_redis.spiders import RedisSpider
2 将爬虫类的父类修改成RedisSpider
3 将起始URL列表注释, 添加一个redis_key(调度器队列的名称)的属性
4 进行redis数据库配置文件的配置：

• 将 bind 127.0.0.1 进行注释
• 将 protected-mode no 关闭保护模式

5 settings中配置redis

REDIS_HOST = '192.168.0.108'
REDIS_PORT = 6379
REDIS_PARAMS = {"password": 123456}

# 使用scrapy-redis组件的去重队列
DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"
# 使用scrapy-redis组件自己的调度器
SCHEDULER = "scrapy_redis.scheduler.Scheduler"
# 是否允许暂停
SCHEDULER_PERSIST = True

ITEM_PIPELINES = {
    'scrapy_redis.pipelines.RedisPipeline': 400
}

6  执行爬虫文件

scrapy runspider wangyi.py

7 向调度器的管道中扔一个起始url

lpush wangyi https://news.163.com/