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
一、scrapy-redis组件
1. URL去重
1 定义去重规则（被调度器调用并应用） 2 3 a. 内部会使用以下配置进行连接Redis 4 5 # REDIS_HOST = 'localhost' # 主机名 6 # REDIS_PORT = 6379 # 端口 7 # REDIS_URL = 'redis://user:pass@hostname:9001' # 连接URL（优先于以上配置） 8 # 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,}） 9 # REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定连接Redis的Python模块 默认：redis.StrictRedis 10 # REDIS_ENCODING = "utf-8" # redis编码类型 默认：'utf-8' 11 12 b. 去重规则通过redis的集合完成，集合的Key为： 13 14 key = defaults.DUPEFILTER_KEY % {'timestamp': int(time.time())} 15 默认配置： 16 DUPEFILTER_KEY = 'dupefilter:%(timestamp)s' 17 18 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 19 20 from scrapy.utils import request 21 from scrapy.http import Request 22 23 req = Request(url='http://www.cnblogs.com/wupeiqi.html') 24 result = request.request_fingerprint(req) 25 print(result) # 8ea4fd67887449313ccc12e5b6b92510cc53675c 26 27 28 PS: 29 - URL参数位置不同时，计算结果一致； 30 - 默认请求头不在计算范围，include_headers可以设置指定请求头 31 示例： 32 from scrapy.utils import request 33 from scrapy.http import Request 34 35 req = Request(url='http://www.baidu.com?name=8&id=1',callback=lambda x:print(x),cookies={'k1':'vvvvv'}) 36 result = request.request_fingerprint(req,include_headers=['cookies',]) 37 38 print(result) 39 40 req = Request(url='http://www.baidu.com?id=1&name=8',callback=lambda x:print(x),cookies={'k1':666}) 41 42 result = request.request_fingerprint(req,include_headers=['cookies',]) 43 44 print(result) 45 46 """ 47 # Ensure all spiders share same duplicates filter through redis. 48 # DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"
2. 调度器
1 """ 2 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 3 4 a. 调度器 5 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） 6 SCHEDULER_QUEUE_KEY = '%(spider)s:requests' # 调度器中请求存放在redis中的key 7 SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat" # 对保存到redis中的数据进行序列化，默认使用pickle 8 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 9 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 10 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）。 11 SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter' # 去重规则，在redis中保存时对应的key 12 SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'# 去重规则对应处理的类 13 14 15 """ 16 # Enables scheduling storing requests queue in redis. 17 SCHEDULER = "scrapy_redis.scheduler.Scheduler" 18 19 # Default requests serializer is pickle, but it can be changed to any module 20 # with loads and dumps functions. Note that pickle is not compatible between 21 # python versions. 22 # Caveat: In python 3.x, the serializer must return strings keys and support 23 # bytes as values. Because of this reason the json or msgpack module will not 24 # work by default. In python 2.x there is no such issue and you can use 25 # 'json' or 'msgpack' as serializers. 26 # SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat" 27 28 # Don't cleanup redis queues, allows to pause/resume crawls. 29 # SCHEDULER_PERSIST = True 30 31 # Schedule requests using a priority queue. (default) 32 # SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.PriorityQueue' 33 34 # Alternative queues. 35 # SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.FifoQueue' 36 # SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.LifoQueue' 37 38 # Max idle time to prevent the spider from being closed when distributed crawling. 39 # This only works if queue class is SpiderQueue or SpiderStack, 40 # and may also block the same time when your spider start at the first time (because the queue is empty). 41 # SCHEDULER_IDLE_BEFORE_CLOSE = 10
3. 数据持久化
1 2. 定义持久化，爬虫yield Item对象时执行RedisPipeline 2 3 a. 将item持久化到redis时，指定key和序列化函数 4 5 REDIS_ITEMS_KEY = '%(spider)s:items' 6 REDIS_ITEMS_SERIALIZER = 'json.dumps' 7 8 b. 使用列表保存item数据
4. 起始URL相关
1 """ 2 起始URL相关 3 4 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 5 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 6 b. 编写爬虫时，起始URL从redis的Key中获取 7 REDIS_START_URLS_KEY = '%(name)s:start_urls' 8 9 """ 10 # If True, it uses redis' ``spop`` operation. This could be useful if you 11 # want to avoid duplicates in your start urls list. In this cases, urls must 12 # be added via ``sadd`` command or you will get a type error from redis. 13 # REDIS_START_URLS_AS_SET = False 14 15 # Default start urls key for RedisSpider and RedisCrawlSpider. 16 # REDIS_START_URLS_KEY = '%(name)s:start_urls'
二、scrapy-redis示例
1 # DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter" 2 # 3 # 4 # from scrapy_redis.scheduler import Scheduler 5 # from scrapy_redis.queue import PriorityQueue 6 # SCHEDULER = "scrapy_redis.scheduler.Scheduler" 7 # 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） 8 # SCHEDULER_QUEUE_KEY = '%(spider)s:requests' # 调度器中请求存放在redis中的key 9 # SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat" # 对保存到redis中的数据进行序列化，默认使用pickle 10 # 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 11 # SCHEDULER_FLUSH_ON_START = False # 是否在开始之前清空 调度器和去重记录，True=清空，False=不清空 12 # 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）。 13 # SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter' # 去重规则，在redis中保存时对应的key 14 # SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'# 去重规则对应处理的类 15 # 16 # 17 # 18 # REDIS_HOST = '10.211.55.13' # 主机名 19 # REDIS_PORT = 6379 # 端口 20 # # REDIS_URL = 'redis://user:pass@hostname:9001' # 连接URL（优先于以上配置） 21 # # 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,}） 22 # # REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定连接Redis的Python模块 默认：redis.StrictRedis 23 # REDIS_ENCODING = "utf-8" # redis编码类型 默认：'utf-8'
1 import scrapy 2 3 4 class ChoutiSpider(scrapy.Spider): 5 name = "chouti" 6 allowed_domains = ["chouti.com"] 7 start_urls = ( 8 'http://www.chouti.com/', 9 ) 10 11 def parse(self, response): 12 for i in range(0,10): 13 yield
