scrapy-redis

scrapy-redis是一個基於redis的scrapy組件，經過它能夠快速實現簡單分佈式爬蟲程序，該組件本質上提供了三大功能：

• scheduler - 調度器
• dupefilter - URL去重規則（被調度器使用）
• pipeline   - 數據持久化

scrapy-redis組件

1. URL去重

Bloomfilter+Redis 優化去重：https://blog.csdn.net/bone_ace/article/details/53099042

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定義去重規則（被調度器調用並應用）        a. 內部會使用如下配置進行鏈接Redis            # REDIS_HOST = 'localhost'                            # 主機名          # REDIS_PORT = 6379                                   # 端口          # REDIS_URL = 'redis://user:pass@hostname:9001'       # 鏈接URL（優先於以上配置）          # REDIS_PARAMS  = {}                                  # Redis鏈接參數             默認：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}）          # REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定鏈接Redis的Python模塊  默認：redis.StrictRedis          # REDIS_ENCODING = "utf-8"                            # redis編碼類型             默認：'utf-8'            b. 去重規則經過redis的集合完成，集合的Key爲：                key  =  defaults.DUPEFILTER_KEY  %  { 'timestamp' :  int (time.time())}          默認配置：              DUPEFILTER_KEY  =  'dupefilter:%(timestamp)s'                     c. 去重規則中將url轉換成惟一標示，而後在redis中檢查是否已經在集合中存在                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參數位置不一樣時，計算結果一致；              -  默認請求頭不在計算範圍，include_headers能夠設置指定請求頭              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. 調度器

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""" 調度器，調度器使用PriorityQueue（有序集合）、FifoQueue（列表）、LifoQueue（列表）進行保存請求，而且使用RFPDupeFilter對URL去重            a. 調度器          SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.PriorityQueue'          # 默認使用優先級隊列（默認），其餘：PriorityQueue（有序集合），FifoQueue（列表）、LifoQueue（列表）          SCHEDULER_QUEUE_KEY = '%(spider)s:requests'                         # 調度器中請求存放在redis中的key          SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"                  # 對保存到redis中的數據進行序列化，默認使用pickle          SCHEDULER_PERSIST = True                                            # 是否在關閉時候保留原來的調度器和去重記錄，True=保留，False=清空          SCHEDULER_FLUSH_ON_START = True                                     # 是否在開始以前清空 調度器和去重記錄，True=清空，False=不清空          SCHEDULER_IDLE_BEFORE_CLOSE = 10                                    # 去調度器中獲取數據時，若是爲空，最多等待時間（最後沒數據，未獲取到）。          SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter'                  # 去重規則，在redis中保存時對應的key          SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'# 去重規則對應處理的類     """ # 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. 數據持久化

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2.  定義持久化，爬蟲 yield  Item對象時執行RedisPipeline            a. 將item持久化到redis時，指定key和序列化函數                REDIS_ITEMS_KEY  =  '%(spider)s:items'          REDIS_ITEMS_SERIALIZER  =  'json.dumps'            b. 使用列表保存item數據

4. 起始URL相關

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""" 起始URL相關        a. 獲取起始URL時，去集合中獲取仍是去列表中獲取？True，集合；False，列表          REDIS_START_URLS_AS_SET = False    # 獲取起始URL時，若是爲True，則使用self.server.spop；若是爲False，則使用self.server.lpop      b. 編寫爬蟲時，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'          # 默認使用優先級隊列（默認），其餘：PriorityQueue（有序集合），FifoQueue（列表）、LifoQueue（列表）
# SCHEDULER_QUEUE_KEY = '%(spider)s:requests'                         # 調度器中請求存放在redis中的key
# SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"                  # 對保存到redis中的數據進行序列化，默認使用pickle
# SCHEDULER_PERSIST = True                                            # 是否在關閉時候保留原來的調度器和去重記錄，True=保留，False=清空
# SCHEDULER_FLUSH_ON_START = False                                    # 是否在開始以前清空 調度器和去重記錄，True=清空，False=不清空
# SCHEDULER_IDLE_BEFORE_CLOSE = 10                                    # 去調度器中獲取數據時，若是爲空，最多等待時間（最後沒數據，未獲取到）。
# SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter'                  # 去重規則，在redis中保存時對應的key
# SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'# 去重規則對應處理的類
#
#
#
# REDIS_HOST = '10.211.55.13'                           # 主機名
# REDIS_PORT = 6379                                     # 端口
# # REDIS_URL = 'redis://user:pass@hostname:9001'       # 鏈接URL（優先於以上配置）
# # REDIS_PARAMS  = {}                                  # Redis鏈接參數             默認：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}）
# # REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定鏈接Redis的Python模塊  默認：redis.StrictRedis
# REDIS_ENCODING = "utf-8"                              # redis編碼類型             默認：'utf-8'

配置文件

import scrapy


class 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

爬蟲文件

補充：

看這個https://www.cnblogs.com/pythoner6833/p/9148937.html 

 

參考or轉發

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