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Centos7__Scrapy + Scrapy_redis 用Docker 实现分布式爬虫

时间:2020-02-26 18:27:52      阅读:83      评论:0      收藏:0      [点我收藏+]

标签:div   优先   sch   清理   docker 安装   commit   process   code   settings   

原理:其实就是用到redis的优点及特性,好处自己查---

1,scrapy 分布式爬虫配置:

settings.py

BOT_NAME = first

SPIDER_MODULES = [first.spiders]
NEWSPIDER_MODULE = first.spiders


# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = ‘first (+http://www.yourdomain.com)‘

# Obey robots.txt rules
ROBOTSTXT_OBEY = False

# Configure a delay for requests for the same website (default: 0)
# See https://docs.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


ITEM_PIPELINES = {
   # ‘first.pipelines.FirstPipeline‘: 300,
   scrapy_redis.pipelines.RedisPipeline:300,
   first.pipelines.VideoPipeline: 100,
}

#分布式爬虫
#指定redis数据库的连接参数
REDIS_HOST = 172.17.0.2 
REDIS_PORT = 15672
REDIS_ENCODING = utf-8
# REDIS_PARAMS ={
#     ‘password‘: ‘123456‘,  # 服务器的redis对应密码
# }
#使用了scrapy_redis的调度器,在redis里分配请求
SCHEDULER = "scrapy_redis.scheduler.Scheduler"
# # 确保所有爬虫共享相同的去重指纹
DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"
# Requests的调度策略,默认优先级队列
SCHEDULER_QUEUE_CLASS = scrapy_redis.queue.PriorityQueue
#(可选). 在redis中保持scrapy-redis用到的各个队列,从而允许暂停和暂停后恢复,也就是不清理redis queues
SCHEDULER_PERSIST = True

spider.py

# -*- coding: utf-8 -*-
import scrapy
import redis
from ..items import Video
from scrapy.http import Request
from scrapy_redis.spiders import RedisSpider
class VideoRedis(RedisSpider):
    name = video_redis
    allowed_domains = [zuidazy2.net]
    # start_urls = [‘http://zuidazy2.net/‘]
    redis_key = zuidazy2:start_urls
    def parse(self, response):
        item = Video()
        res= response.xpath(//div[@class="xing_vb"]/ul/li/span[@class="xing_vb4"]/a/text()).extract_first()
        url = response.xpath(//div[@class="xing_vb"]/ul/li/span[@class="xing_vb4"]/a/@href).extract_first()
        v_type = response.xpath(//div[@class="xing_vb"]/ul/li/span[@class="xing_vb5"]/text()).extract_first()
        u_time  = response.xpath(//div[@class="xing_vb"]/ul/li/span[@class="xing_vb6"]/text()).extract_first()
        if res is not None:
            item[name] = res
            item[v_type] = v_type
            item[u_time] = u_time
            url = http://www.zuidazy2.net + url
            yield scrapy.Request(url, callback=self.info_data,meta={item: item},dont_filter=True)
        next_link =  response.xpath(//div[@class="xing_vb"]/ul/li/div[@class="pages"]/a[last()-1]/@href).extract_first()
        if next_link:
            yield scrapy.Request(http://www.zuidazy2.net+next_link,callback=self.parse,dont_filter=True)
            
    def info_data(self,data):
        item = data.meta[item]
        res = data.xpath(//div[@id="play_2"]/ul/li/text()).extract()
        if res:
            item[url] = res
        else:
            item[url] = ‘‘
        yield item

items.py

import scrapy


class FirstItem(scrapy.Item):
    # define the fields for your item here like:
    content = scrapy.Field()

class Video(scrapy.Item):
    name = scrapy.Field()
    url = scrapy.Field()
    v_type = scrapy.Field()
    u_time = scrapy.Field()

pipelines.py

from pymysql import *
import aiomysql
class FirstPipeline(object):
    def process_item(self, item, spider):
        print(**30,item[content])
        return item
  
class VideoPipeline(object):
    def __init__(self): 
        self.conn = connect(host="39.99.37.85",port=3306,user="root",password="",database="queyou")
        self.cur = self.conn.cursor()

    def process_item(self, item, spider):
        
        # print(item)
        try:
            # insert_sql = f"insert into video values(0,‘{item[‘name‘]}‘,‘{item[‘url‘]}‘,‘{item[‘v_type‘]}‘,‘{item[‘u_time‘]}‘)"
            # self.cur.execute(insert_sql)
            # # self.cur.execute("insert into video values(0,‘"+item[‘name‘]+"‘,‘"+item[‘url‘]+"‘,‘"+item[‘v_type‘]+"‘,‘"+item[‘u_time‘]+"‘)")
            self.cur.execute("insert into video values(0,‘"+item[name]+"‘,‘"+item[v_type]+"‘)")
            self.conn.commit()
        except Exception as e:
            print(e)
        finally:
            return item
    def close_spider(self, spider):    
        self.conn.commit()  # 提交数据
        self.cur.close()
        self.conn.close()

2,Docker 安装和pull centos7 及安装依赖  (跳过)

3,cp 宿主机项目到 Centos7 容器中

docker cp /root/first 35fa:/root

4,安装redis 及 开启远程连接服务

具体在 /etc/redis.conf 中设置和开启redis服务

redis-server /etc/redis.conf

5,Docker虚拟主机多个及建立通信容器

运行容器
docker run -tid --name 11  CONTAINER_ID 

建立通信容器
docker run  -tid --name 22 --link 11 CONTAINER_ID

进入容器  docker attach CONTAINER_ID

退出容器,不kill掉容器(通常exit会kill掉的) ctrl+q+p
查看网络情况 cat /etc/hosts

技术图片

 

 5,开启所有容器的spider 及定义start_url

技术图片

 

 完工!

附上打包好的镜像:链接: https://pan.baidu.com/s/1Sj244da0pOZvL3SZ_qagUg 提取码: qp23

Centos7__Scrapy + Scrapy_redis 用Docker 实现分布式爬虫

标签:div   优先   sch   清理   docker 安装   commit   process   code   settings   

原文地址:https://www.cnblogs.com/xcsg/p/12368072.html

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