分布式爬虫

转载自:http://www.cnblogs.com/wupeiqi/articles/6912807.html


scrapy-redis使用以及剖析

scrapy-redis是一个基于redis的scrapy组件,通过它可以快速实现简单分布式爬虫程序,该组件本质上提供了三大功能:

  • scheduler - 调度器
  • dupefilter - URL去重规则(被调度器使用)
  • pipeline   - 数据持久化

scrapy-redis组件

1. URL去重

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定义去重规则(被调度器调用并应用)
 
     a. 内部会使用以下配置进行连接Redis
 
         # REDIS_HOST = 'localhost'                            # 主机名
         # REDIS_PORT = 6379                                   # 端口
         # REDIS_URL = 'redis://user:pass@hostname:9001'       # 连接URL(优先于以上配置)
         # REDIS_PARAMS  = {}                                  # Redis连接参数             默认:REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,})
         # REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定连接Redis的Python模块  默认:redis.StrictRedis
         # REDIS_ENCODING = "utf-8"                            # redis编码类型             默认:'utf-8'
     
     b. 去重规则通过redis的集合完成,集合的Key为:
     
         key  =  defaults.DUPEFILTER_KEY  %  { 'timestamp' int (time.time())}
         默认配置:
             DUPEFILTER_KEY  =  'dupefilter:%(timestamp)s'
              
     c. 去重规则中将url转换成唯一标示,然后在redis中检查是否已经在集合中存在
     
         from  scrapy.utils  import  request
         from  scrapy.http  import  Request
         
         req  =  Request(url = 'http://www.cnblogs.com/wupeiqi.html' )
         result  =  request.request_fingerprint(req)
         print (result)  # 8ea4fd67887449313ccc12e5b6b92510cc53675c
         
         
         PS:
             -  URL参数位置不同时,计算结果一致;
             -  默认请求头不在计算范围,include_headers可以设置指定请求头
             示例:
                 from  scrapy.utils  import  request
                 from  scrapy.http  import  Request
                 
                 req  =  Request(url = 'http://www.baidu.com?name=8&id=1' ,callback = lambda  x: print (x),cookies = { 'k1' : 'vvvvv' })
                 result  =  request.request_fingerprint(req,include_headers = [ 'cookies' ,])
                 
                 print (result)
                 
                 req  =  Request(url = 'http://www.baidu.com?id=1&name=8' ,callback = lambda  x: print (x),cookies = { 'k1' : 666 })
                 
                 result  =  request.request_fingerprint(req,include_headers = [ 'cookies' ,])
                 
                 print (result)
         
"""
# Ensure all spiders share same duplicates filter through redis.
# DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"

2. 调度器

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"""
调度器,调度器使用PriorityQueue(有序集合)、FifoQueue(列表)、LifoQueue(列表)进行保存请求,并且使用RFPDupeFilter对URL去重
     
     a. 调度器
         SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.PriorityQueue'          # 默认使用优先级队列(默认),其他:PriorityQueue(有序集合),FifoQueue(列表)、LifoQueue(列表)
         SCHEDULER_QUEUE_KEY = '%(spider)s:requests'                         # 调度器中请求存放在redis中的key
         SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"                  # 对保存到redis中的数据进行序列化,默认使用pickle
         SCHEDULER_PERSIST = True                                            # 是否在关闭时候保留原来的调度器和去重记录,True=保留,False=清空
         SCHEDULER_FLUSH_ON_START = True                                     # 是否在开始之前清空 调度器和去重记录,True=清空,False=不清空
         SCHEDULER_IDLE_BEFORE_CLOSE = 10                                    # 去调度器中获取数据时,如果为空,最多等待时间(最后没数据,未获取到)。
         SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter'                  # 去重规则,在redis中保存时对应的key
         SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'# 去重规则对应处理的类
 
 
"""
# Enables scheduling storing requests queue in redis.
SCHEDULER  =  "scrapy_redis.scheduler.Scheduler"
 
# Default requests serializer is pickle, but it can be changed to any module
# with loads and dumps functions. Note that pickle is not compatible between
# python versions.
# Caveat: In python 3.x, the serializer must return strings keys and support
# bytes as values. Because of this reason the json or msgpack module will not
# work by default. In python 2.x there is no such issue and you can use
# 'json' or 'msgpack' as serializers.
# SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"
 
# Don't cleanup redis queues, allows to pause/resume crawls.
# SCHEDULER_PERSIST = True
 
# Schedule requests using a priority queue. (default)
# SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.PriorityQueue'
 
# Alternative queues.
# SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.FifoQueue'
# SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.LifoQueue'
 
# Max idle time to prevent the spider from being closed when distributed crawling.
# This only works if queue class is SpiderQueue or SpiderStack,
# and may also block the same time when your spider start at the first time (because the queue is empty).
# SCHEDULER_IDLE_BEFORE_CLOSE = 10  

3. 数据持久化

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2.  定义持久化,爬虫 yield  Item对象时执行RedisPipeline
     
     a. 将item持久化到redis时,指定key和序列化函数
     
         REDIS_ITEMS_KEY  =  '%(spider)s:items'
         REDIS_ITEMS_SERIALIZER  =  'json.dumps'
     
     b. 使用列表保存item数据

4. 起始URL相关

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"""
起始URL相关
 
     a. 获取起始URL时,去集合中获取还是去列表中获取?True,集合;False,列表
         REDIS_START_URLS_AS_SET = False    # 获取起始URL时,如果为True,则使用self.server.spop;如果为False,则使用self.server.lpop
     b. 编写爬虫时,起始URL从redis的Key中获取
         REDIS_START_URLS_KEY = '%(name)s:start_urls'
         
"""
# If True, it uses redis' ``spop`` operation. This could be useful if you
# want to avoid duplicates in your start urls list. In this cases, urls must
# be added via ``sadd`` command or you will get a type error from redis.
# REDIS_START_URLS_AS_SET = False
 
# Default start urls key for RedisSpider and RedisCrawlSpider.
# REDIS_START_URLS_KEY = '%(name)s:start_urls'

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转载自blog.csdn.net/weixin_41988628/article/details/80040465