scrapy-redis使用以及剖析
生活随笔
收集整理的這篇文章主要介紹了
scrapy-redis使用以及剖析
小編覺得挺不錯的,現在分享給大家,幫大家做個參考.
scrapy-redis是一個基于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
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | 定義去重規則(被調度器調用并應用) ????a. 內部會使用以下配置進行連接Redis ????????# REDIS_HOST = 'localhost'??????????????????????????? # 主機名 ????????# REDIS_PORT = 6379?????????????????????????????????? # 端口 ????????# REDIS_URL = 'redis://user:pass@hostname:9001'?????? # 連接URL(優先于以上配置) ????????# 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參數位置不同時,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
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | """ 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,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(最后沒數據,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
| 1 2 3 4 5 6 7 8 | 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
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | """ 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' |
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 = 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 # 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(最后沒數據,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' # 連接URL(優先于以上配置) # # 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' 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?
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
轉載于:https://www.cnblogs.com/zero-white/p/8684720.html
總結
以上是生活随笔為你收集整理的scrapy-redis使用以及剖析的全部內容,希望文章能夠幫你解決所遇到的問題。
- 上一篇: c++程序设计中文件输入输出流知识点
- 下一篇: Client.Timeout excee