scrapy-redis使用以及剖析

scrapy-redis是一個(gè)基于redis的scrapy組件，通過它可以快速實(shí)現(xiàn)簡單分布式爬蟲程序，該組件本質(zhì)上提供了三大功能：

• scheduler - 調(diào)度器
• dupefilter - URL去重規(guī)則（被調(diào)度器使用）
• pipeline ? - 數(shù)據(jù)持久化

scrapy-redis組件

1. URL去重

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定義去重規(guī)則（被調(diào)度器調(diào)用并應(yīng)用） ????a. 內(nèi)部會使用以下配置進(jìn)行連接Redis ????????# REDIS_HOST = 'localhost'??????????????????????????? # 主機(jī)名 ????????# REDIS_PORT = 6379?????????????????????????????????? # 端口 ????????# REDIS_URL = 'redis://user:pass@hostname:9001'?????? # 連接URL（優(yōu)先于以上配置） ????????# REDIS_PARAMS? = {}????????????????????????????????? # Redis連接參數(shù)???????????? 默認(rèn)：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}） ????????# REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定連接Redis的Python模塊? 默認(rèn)：redis.StrictRedis ????????# REDIS_ENCODING = "utf-8"??????????????????????????? # redis編碼類型???????????? 默認(rèn)：'utf-8' ????? ????b. 去重規(guī)則通過redis的集合完成，集合的Key為： ????? ????????key?=?defaults.DUPEFILTER_KEY?%?{'timestamp':?int(time.time())} ????????默認(rèn)配置： ????????????DUPEFILTER_KEY?=?'dupefilter:%(timestamp)s' ?????????????? ????c. 去重規(guī)則中將url轉(zhuǎn)換成唯一標(biāo)示，然后在redis中檢查是否已經(jīng)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參數(shù)位置不同時(shí)，計(jì)算結(jié)果一致； ????????????-?默認(rèn)請求頭不在計(jì)算范圍，include_headers可以設(shè)置指定請求頭 ????????????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. 調(diào)度器

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""" 調(diào)度器，調(diào)度器使用PriorityQueue（有序集合）、FifoQueue（列表）、LifoQueue（列表）進(jìn)行保存請求，并且使用RFPDupeFilter對URL去重 ????? ????a. 調(diào)度器 ????????SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.PriorityQueue'????????? # 默認(rèn)使用優(yōu)先級隊(duì)列（默認(rèn)），其他：PriorityQueue（有序集合），FifoQueue（列表）、LifoQueue（列表） ????????SCHEDULER_QUEUE_KEY = '%(spider)s:requests'???????????????????????? # 調(diào)度器中請求存放在redis中的key ????????SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"????????????????? # 對保存到redis中的數(shù)據(jù)進(jìn)行序列化，默認(rèn)使用pickle ????????SCHEDULER_PERSIST = True??????????????????????????????????????????? # 是否在關(guān)閉時(shí)候保留原來的調(diào)度器和去重記錄，True=保留，False=清空 ????????SCHEDULER_FLUSH_ON_START = True???????????????????????????????????? # 是否在開始之前清空 調(diào)度器和去重記錄，True=清空，False=不清空 ????????SCHEDULER_IDLE_BEFORE_CLOSE = 10??????????????????????????????????? # 去調(diào)度器中獲取數(shù)據(jù)時(shí)，如果為空，最多等待時(shí)間（最后沒數(shù)據(jù)，未獲取到）。 ????????SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter'????????????????? # 去重規(guī)則，在redis中保存時(shí)對應(yīng)的key ????????SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'# 去重規(guī)則對應(yīng)處理的類 """ # 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. 數(shù)據(jù)持久化

　from scrapy_redis.pipelines import RedisPipelines

　ITEM_PIPELINES=[

　　'scrapy_redis.pipelines.RedisPipelines':300,

]　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　

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2.?定義持久化，爬蟲yield?Item對象時(shí)執(zhí)行RedisPipeline ????? ????a. 將item持久化到redis時(shí)，指定key和序列化函數(shù) ????? ????????REDIS_ITEMS_KEY?=?'%(spider)s:items' ????????REDIS_ITEMS_SERIALIZER?=?'json.dumps' ?????　　　　 ????b. 使用列表保存item數(shù)據(jù)

4. 起始URL相關(guān)

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""" 起始URL相關(guān) ????a. 獲取起始URL時(shí)，去集合中獲取還是去列表中獲取？True，集合；False，列表 ????????REDIS_START_URLS_AS_SET = False??? # 獲取起始URL時(shí)，如果為True，則使用self.server.spop；如果為False，則使用self.server.lpop ????b. 編寫爬蟲時(shí)，起始URL從redis的Key中獲取 ????????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'

scrapy-redis示例

# DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter" # # # from scrapy_redis.scheduler import Scheduler # from scrapy_redis.queue import PriorityQueue # SCHEDULER = "scrapy_redis.scheduler.Scheduler" # SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.PriorityQueue' # 默認(rèn)使用優(yōu)先級隊(duì)列（默認(rèn)），其他：PriorityQueue（有序集合），FifoQueue（列表）、LifoQueue（列表） # SCHEDULER_QUEUE_KEY = '%(spider)s:requests' # 調(diào)度器中請求存放在redis中的key # SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat" # 對保存到redis中的數(shù)據(jù)進(jìn)行序列化，默認(rèn)使用pickle # SCHEDULER_PERSIST = True # 是否在關(guān)閉時(shí)候保留原來的調(diào)度器和去重記錄，True=保留，False=清空 # SCHEDULER_FLUSH_ON_START = False # 是否在開始之前清空 調(diào)度器和去重記錄，True=清空，False=不清空 # SCHEDULER_IDLE_BEFORE_CLOSE = 10 # 去調(diào)度器中獲取數(shù)據(jù)時(shí)，如果為空，最多等待時(shí)間（最后沒數(shù)據(jù)，未獲取到）。 # SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter' # 去重規(guī)則，在redis中保存時(shí)對應(yīng)的key # SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'# 去重規(guī)則對應(yīng)處理的類 # # # # REDIS_HOST = '10.211.55.13' # 主機(jī)名 # REDIS_PORT = 6379 # 端口 # # REDIS_URL = 'redis://user:pass@hostname:9001' # 連接URL（優(yōu)先于以上配置） # # REDIS_PARAMS = {} # Redis連接參數(shù) 默認(rèn)：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}） # # REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定連接Redis的Python模塊 默認(rèn)：redis.StrictRedis # REDIS_ENCODING = "utf-8" # redis編碼類型 默認(rèn)：'utf-8' View Code import scrapyclass ChoutiSpider(scrapy.Spider):name = "chouti"allowed_domains = ["chouti.com"]start_urls = ('http://www.chouti.com/',)def parse(self, response):for i in range(0,10):yield View Code

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轉(zhuǎn)載于:https://www.cnblogs.com/Hessen/p/10816411.html

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