scrapy rabbitmq 分布式爬虫

对于没接触过rabbitmq的同学，可以看这个文章：https://blog.csdn.net/hellozpc/article/details/81436980
rabbitmq是个不错的消息队列服务，可以配合scrapy作为消息队列.
 
下面是一个简单的demo：

import re

import requests

import scrapy

from scrapy import Request

from rabbit_spider import settings

from scrapy.log import logger

import json

from rabbit_spider.items import RabbitSpiderItem

import datetime

from scrapy.selector import Selector

import pika



# from scrapy_rabbitmq.spiders import RabbitMQMixin

# from scrapy.contrib.spiders import CrawlSpider



class Website(scrapy.Spider):

    name = "rabbit"



    def start_requests(self):

        headers = {'Accept': '*/*',

                   'Accept-Encoding': 'gzip, deflate, br',

                   'Accept-Language': 'en-US,en;q=0.9,zh-CN;q=0.8,zh;q=0.7',

                   'Host': '36kr.com',

                   'Referer': 'https://36kr.com/information/web_news',

                   'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.108 Safari/537.36'

                   }



        url = 'https://36kr.com/information/web_news'

        



        yield Request(url=url,

                      headers=headers)



    def parse(self, response):

       



        credentials = pika.PlainCredentials('admin', 'admin')

        connection = pika.BlockingConnection(pika.ConnectionParameters('192.168.1.101', 5672, '/', credentials))



        channel = connection.channel()

        channel.exchange_declare(exchange='direct_log', exchange_type='direct')



        result = channel.queue_declare(exclusive=True, queue='')



        queue_name = result.method.queue



        # print(queue_name)

        # infos = sys.argv[1:] if len(sys.argv)>1 else ['info']

        info = 'info'



        # 绑定多个值



        channel.queue_bind(

            exchange='direct_log',

            routing_key=info,

            queue=queue_name

        )

        print('start to receive [{}]'.format(info))



        channel.basic_consume(

            on_message_callback=self.callback_func,

            queue=queue_name,

            auto_ack=True,

        )



        channel.start_consuming()





    def callback_func(self, ch, method, properties, body):

        print(body)

 启动spider：

from scrapy import cmdline

cmdline.execute('scrapy crawl rabbit'.split())

 然后往rabbitmq里面推送数据：

import pika

import settings



credentials = pika.PlainCredentials('admin','admin')

connection = pika.BlockingConnection(pika.ConnectionParameters('192.168.1.101',5672,'/',credentials))



channel = connection.channel()

channel.exchange_declare(exchange='direct_log',exchange_type='direct') # fanout 就是组播



routing_key = 'info'

message='https://36kr.com/pp/api/aggregation-entity?type=web_latest_article&b_id=59499&per_page=30'

channel.basic_publish(

	exchange='direct_log',

	routing_key=routing_key,

	body=message

	)



print('sending message {}'.format(message))

connection.close()

 
推送数据后，scrapy会马上接受到队里里面的数据。
注意不能在start_requests里面写等待队列的命令，因为start_requests函数需要返回一个生成器，否则程序会报错。
 
待续。。。
###### 2019-08-29 更新 ################### 
发现一个坑，就是rabbitMQ在接受到数据后，无法在回调函数里面使用yield生成器。