scrapy-redis是一個基于redis的scrapy組件，通過它可以快速實作簡單分布式爬蟲程式，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 - 資料持久化
Scrapy-redis提供了下面四種組件（components）：(四種組件意味著這四個模塊都要做相應的修改)
- Scheduler
- Duplication Filter
- Item Pipeline
- Base Spider
scrapy-redis組件
scrapy-redis架構
URL去重
定義去重規則（被調度器呼叫并應用）
a. 內部會使用以下配置進行連接Redis
# REDIS_HOST = 'localhost' # 主機名
# REDIS_PORT = 6379 # 埠
# REDIS_URL = 'redis://user:pass@hostname:9001' # 連接URL（優先于以上配置）
# REDIS_PARAMS = {} # Redis連接引數 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編碼型別 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，然后在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引數位置不同時，計算結果一致；
- 默認請求頭不在計算范圍，include_headers可以設定指定請求頭
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"
調度器
"""
調度器，調度器使用PriorityQueue（有序集合）、FifoQueue（串列）、LifoQueue（串列）進行保存請求，并且使用RFPDupeFilter對URL去重
a. 調度器
SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.PriorityQueue' # 默認使用優先級佇列（默認），其他：PriorityQueue（有序集合），FifoQueue（串列）、LifoQueue（串列）
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中的資料進行序列化，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 # 去調度器中獲取資料時，如果為空，最多等待時間（最后沒資料，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
資料持久化
2. 定義持久化，爬蟲yield Item物件時執行RedisPipeline
a. 將item持久化到redis時，指定key和序列化函式
REDIS_ITEMS_KEY = '%(spider)s:items'
REDIS_ITEMS_SERIALIZER = 'json.dumps'
b. 使用串列保存item資料
起始URL相關
"""
起始URL相關
a. 獲取起始URL時，去集合中獲取還是去串列中獲取？True，集合；False，串列
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. 撰寫爬蟲時，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
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' # 默認使用優先級佇列（默認），其他：PriorityQueue（有序集合），FifoQueue（串列）、LifoQueue（串列）
8 # SCHEDULER_QUEUE_KEY = '%(spider)s:requests' # 調度器中請求存放在redis中的key
9 # SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat" # 對保存到redis中的資料進行序列化，默認使用pickle
10 # 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
11 # SCHEDULER_FLUSH_ON_START = False # 是否在開始之前清空 調度器和去重記錄，True=清空，False=不清空
12 # SCHEDULER_IDLE_BEFORE_CLOSE = 10 # 去調度器中獲取資料時，如果為空，最多等待時間（最后沒資料，未獲取到），
13 # SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter' # 去重規則，在redis中保存時對應的key
14 # SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'# 去重規則對應處理的類
15 #
16 #
17 #
18 # REDIS_HOST = '10.211.55.13' # 主機名
19 # REDIS_PORT = 6379 # 埠
20 # # REDIS_URL = 'redis://user:pass@hostname:9001' # 連接URL（優先于以上配置）
21 # # REDIS_PARAMS = {} # Redis連接引數 默認：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}）
22 # # REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定連接Redis的Python模塊 默認：redis.StrictRedis
23 # REDIS_ENCODING = "utf-8" # redis編碼型別 默認：'utf-8'
24
25 組態檔
組態檔
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
爬蟲檔案
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標籤：Python