爬虫 之 scrapy-redis组件

 scrapy-redis组件

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

基于scrapy-redis的去重规则

方案

#- 完全自定义 
from scrapy.dupefilter import BaseDupeFilter
import redis
from scrapy.utils.request import request_fingerprint

class DupFilter(BaseDupeFilter):
	def __init__(self):
		self.conn = redis.Redis(host='140.143.227.206',port=8888,password='beta')

	def request_seen(self, request):
		"""
		检测当前请求是否已经被访问过
		:param request: 
		:return: True表示已经访问过;False表示未访问过
		"""
		fid = request_fingerprint(request)
		result = self.conn.sadd('visited_urls', fid)
		if result == 1:
			return False
		return True

#- 使用scrapy-redis 
#时间戳一直变,不方便查找

#- 继承scrapy-redis 实现自定制 

from scrapy_redis.dupefilter import RFPDupeFilter
from scrapy_redis.connection import get_redis_from_settings
from scrapy_redis import defaults

class RedisDupeFilter(RFPDupeFilter):
	@classmethod
	def from_settings(cls, settings):
		"""Returns an instance from given settings.

		This uses by default the key ``dupefilter:<timestamp>``. When using the
		``scrapy_redis.scheduler.Scheduler`` class, this method is not used as
		it needs to pass the spider name in the key.

		Parameters
		----------
		settings : scrapy.settings.Settings

		Returns
		-------
		RFPDupeFilter
			A RFPDupeFilter instance.


		"""
		server = get_redis_from_settings(settings)
		# XXX: This creates one-time key. needed to support to use this
		# class as standalone dupefilter with scrapy's default scheduler
		# if scrapy passes spider on open() method this wouldn't be needed
		# TODO: Use SCRAPY_JOB env as default and fallback to timestamp.
		key = defaults.DUPEFILTER_KEY % {'timestamp': 'xiaodongbei'}
		debug = settings.getbool('DUPEFILTER_DEBUG')
		return cls(server, key=key, debug=debug)

配置

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"

不写方法,直接在settings中修改配置就可以用。 

调度器

"""
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  

示例

找到 SCHEDULER = "scrapy_redis.scheduler.Scheduler" 配置并实例化调度器对象
- 执行Scheduler.from_crawler
- 执行Scheduler.from_settings
	- 读取配置文件:
		SCHEDULER_PERSIST			 # 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     # 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  # 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)。
	- 读取配置文件:	
		SCHEDULER_QUEUE_KEY			 # %(spider)s:requests
		SCHEDULER_QUEUE_CLASS		 # scrapy_redis.queue.FifoQueue
		SCHEDULER_DUPEFILTER_KEY     # '%(spider)s:dupefilter'
		DUPEFILTER_CLASS			 # 'scrapy_redis.dupefilter.RFPDupeFilter'
		SCHEDULER_SERIALIZER		 # "scrapy_redis.picklecompat"

	- 读取配置文件:
		REDIS_HOST = '140.143.227.206'                            # 主机名
		REDIS_PORT = 8888                                   # 端口
		REDIS_PARAMS  = {'password':'beta'}                                  # Redis连接参数             默认:REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,})
		REDIS_ENCODING = "utf-8"      
- 示例Scheduler对象

数据持久化

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  

起始URL相关

"""
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'

示例 

- 调用 scheduler.enqueue_requests()
	def enqueue_request(self, request):
		# 请求是否需要过滤?
		# 去重规则中是否已经有?(是否已经访问过,如果未访问添加到去重记录中。)
		if not request.dont_filter and self.df.request_seen(request):
			self.df.log(request, self.spider)
			# 已经访问过就不要再访问了
			return False
		
		if self.stats:
			self.stats.inc_value('scheduler/enqueued/redis', spider=self.spider)
		# print('未访问过,添加到调度器', request)
		self.queue.push(request)
		return True  

下载器

- 调用 scheduler.next_requests()
	def next_request(self):
		block_pop_timeout = self.idle_before_close
		request = self.queue.pop(block_pop_timeout)
		if request and self.stats:
			self.stats.inc_value('scheduler/dequeued/redis', spider=self.spider)
		return request

  

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转载自www.cnblogs.com/gaoya666/p/9255864.html