scrapy-redis使用以及剖析
阿新 • • 發佈：2018-04-01
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scrapy-redis是一個基於redis的scrapy組件，通過它可以快速實現簡單分布式爬蟲程序，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
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定義去重規則（被調度器調用並應用） a. 內部會使用以下配置進行連接Redis
# REDIS_HOST = ‘localhost‘ # 主機名
# REDIS_PORT = 6379 # 端口
# REDIS_URL = ‘redis://user:pass@hostname:9001‘ # 連接URL（優先於以上配置）
# REDIS_PARAMS = {} # Redis連接參數 默認：REDIS_PARAMS = {‘socket_timeout‘: 30,‘socket_connect_timeout‘: 30,‘retry_on_timeout‘: True,‘encoding‘: REDIS_ENCODING,}） # REDIS_PARAMS[‘redis_cls‘] = ‘myproject.RedisClient‘ # 指定連接Redis的Python模塊 默認：redis.StrictRedis
# REDIS_ENCODING = "utf-8" # redis編碼類型 默認：‘utf-8‘
b. 去重規則通過redis的集合完成，集合的Key為：
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轉換成唯一標示，然後在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參數位置不同時，計算結果一致；
- 默認請求頭不在計算範圍，include_headers可以設置指定請求頭
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"
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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，並且使用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），其他：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 # 是否在開始之前清空 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，如果為空，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
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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
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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，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，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‘
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scrapy-redis使用以及剖析