python高级之scrapy-redis

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目录:

  • scrapy-redis组件

  • scrapy-redis配置示例

一、scrapy-redis组件

1、scrapy-redis简介:

scrapy-redis是一个基于redis的scrapy组件,通过它可以快速实现简单分布式爬虫程序,该组件本质上提供了三大功能:

  • scheduler - 调度器
  • dupefilter - URL去重规则(被调度器使用)
  • pipeline   - 数据持久化

2、url去重

多爬虫分布式并发,如何保证调用的url不重复。需要把爬虫队列和调度器,去重规则,提取到redis中。

组件: scrapy-redis,将去重规则和调度器放置到redis中。

流程:连接redis,指定调度器时,调用去重规则.request_seen方法。

技术分享
 1 定义去重规则(被调度器调用并应用)
 2  
 3     a. 内部会使用以下配置进行连接Redis
 4  
 5         # REDIS_HOST = ‘localhost‘                            # 主机名
 6         # REDIS_PORT = 6379                                   # 端口
 7         # REDIS_URL = ‘redis://user:[email protected]:9001‘       # 连接URL(优先于以上配置)
 8         # REDIS_PARAMS  = {}                                  # Redis连接参数             默认:REDIS_PARAMS = {‘socket_timeout‘: 30,‘socket_connect_timeout‘: 30,‘retry_on_timeout‘: True,‘encoding‘: REDIS_ENCODING,})
 9         # REDIS_PARAMS[‘redis_cls‘] = ‘myproject.RedisClient‘ # 指定连接Redis的Python模块  默认:redis.StrictRedis
10         # REDIS_ENCODING = "utf-8"                            # redis编码类型             默认:‘utf-8‘
11      
12     b. 去重规则通过redis的集合完成,集合的Key为:
13      
14         key = defaults.DUPEFILTER_KEY % {timestamp: int(time.time())}
15         默认配置:
16             DUPEFILTER_KEY = dupefilter:%(timestamp)s
17               
18     c. 去重规则中将url转换成唯一标示,然后在redis中检查是否已经在集合中存在
19      
20         from scrapy.utils import request
21         from scrapy.http import Request
22          
23         req = Request(url=http://www.cnblogs.com/wupeiqi.html)
24         result = request.request_fingerprint(req)
25         print(result) # 8ea4fd67887449313ccc12e5b6b92510cc53675c
26          
27          
28         PS:
29             - URL参数位置不同时,计算结果一致;
30             - 默认请求头不在计算范围,include_headers可以设置指定请求头
31             示例:
32                 from scrapy.utils import request
33                 from scrapy.http import Request
34                  
35                 req = Request(url=http://www.baidu.com?name=8&id=1,callback=lambda x:print(x),cookies={k1:vvvvv})
36                 result = request.request_fingerprint(req,include_headers=[cookies,])
37                  
38                 print(result)
39                  
40                 req = Request(url=http://www.baidu.com?id=1&name=8,callback=lambda x:print(x),cookies={k1:666})
41                  
42                 result = request.request_fingerprint(req,include_headers=[cookies,])
43                  
44                 print(result)
45          
46 """
47 # Ensure all spiders share same duplicates filter through redis.
48 # DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"
View Code

ps.有关爬虫队列和调度器,去重规则详见

http://www.cnblogs.com/wangshuyang/p/7717263.html

3、调度器

技术分享
 1 """
 2 调度器,调度器使用PriorityQueue(有序集合)、FifoQueue(列表)、LifoQueue(列表)进行保存请求,并且使用RFPDupeFilter对URL去重
 3      
 4     a. 调度器
 5         SCHEDULER_QUEUE_CLASS = ‘scrapy_redis.queue.PriorityQueue‘          # 默认使用优先级队列(默认),其他:PriorityQueue(有序集合),FifoQueue(列表)、LifoQueue(列表)
 6         SCHEDULER_QUEUE_KEY = ‘%(spider)s:requests‘                         # 调度器中请求存放在redis中的key
 7         SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"                  # 对保存到redis中的数据进行序列化,默认使用pickle
 8         SCHEDULER_PERSIST = True                                            # 是否在关闭时候保留原来的调度器和去重记录,True=保留,False=清空
 9         SCHEDULER_FLUSH_ON_START = True                                     # 是否在开始之前清空 调度器和去重记录,True=清空,False=不清空
10         SCHEDULER_IDLE_BEFORE_CLOSE = 10                                    # 去调度器中获取数据时,如果为空,最多等待时间(最后没数据,未获取到)。
11         SCHEDULER_DUPEFILTER_KEY = ‘%(spider)s:dupefilter‘                  # 去重规则,在redis中保存时对应的key
12         SCHEDULER_DUPEFILTER_CLASS = ‘scrapy_redis.dupefilter.RFPDupeFilter‘# 去重规则对应处理的类
13  
14  
15 """
16 # Enables scheduling storing requests queue in redis.
17 SCHEDULER = "scrapy_redis.scheduler.Scheduler"
18  
19 # Default requests serializer is pickle, but it can be changed to any module
20 # with loads and dumps functions. Note that pickle is not compatible between
21 # python versions.
22 # Caveat: In python 3.x, the serializer must return strings keys and support
23 # bytes as values. Because of this reason the json or msgpack module will not
24 # work by default. In python 2.x there is no such issue and you can use
25 # ‘json‘ or ‘msgpack‘ as serializers.
26 # SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"
27  
28 # Don‘t cleanup redis queues, allows to pause/resume crawls.
29 # SCHEDULER_PERSIST = True
30  
31 # Schedule requests using a priority queue. (default)
32 # SCHEDULER_QUEUE_CLASS = ‘scrapy_redis.queue.PriorityQueue‘
33  
34 # Alternative queues.
35 # SCHEDULER_QUEUE_CLASS = ‘scrapy_redis.queue.FifoQueue‘
36 # SCHEDULER_QUEUE_CLASS = ‘scrapy_redis.queue.LifoQueue‘
37  
38 # Max idle time to prevent the spider from being closed when distributed crawling.
39 # This only works if queue class is SpiderQueue or SpiderStack,
40 # and may also block the same time when your spider start at the first time (because the queue is empty).
41 # SCHEDULER_IDLE_BEFORE_CLOSE = 10  
View Code

4、数据持久化

技术分享
1 2. 定义持久化,爬虫yield Item对象时执行RedisPipeline
2      
3     a. 将item持久化到redis时,指定key和序列化函数
4      
5         REDIS_ITEMS_KEY = %(spider)s:items
6         REDIS_ITEMS_SERIALIZER = json.dumps
7      
8     b. 使用列表保存item数据
View Code

5、起始URL相关

技术分享
 1 """
 2 起始URL相关
 3  
 4     a. 获取起始URL时,去集合中获取还是去列表中获取?True,集合;False,列表
 5         REDIS_START_URLS_AS_SET = False    # 获取起始URL时,如果为True,则使用self.server.spop;如果为False,则使用self.server.lpop
 6     b. 编写爬虫时,起始URL从redis的Key中获取
 7         REDIS_START_URLS_KEY = ‘%(name)s:start_urls‘
 8          
 9 """
10 # If True, it uses redis‘ ``spop`` operation. This could be useful if you
11 # want to avoid duplicates in your start urls list. In this cases, urls must
12 # be added via ``sadd`` command or you will get a type error from redis.
13 # REDIS_START_URLS_AS_SET = False
14  
15 # Default start urls key for RedisSpider and RedisCrawlSpider.
16 # REDIS_START_URLS_KEY = ‘%(name)s:start_urls‘
View Code

二、scrapy-redis配置示例

1、示例文件

技术分享
 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‘          # 默认使用优先级队列(默认),其他:PriorityQueue(有序集合),FifoQueue(列表)、LifoQueue(列表)
 8 # SCHEDULER_QUEUE_KEY = ‘%(spider)s:requests‘                         # 调度器中请求存放在redis中的key
 9 # SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"                  # 对保存到redis中的数据进行序列化,默认使用pickle
10 # SCHEDULER_PERSIST = True                                            # 是否在关闭时候保留原来的调度器和去重记录,True=保留,False=清空
11 # SCHEDULER_FLUSH_ON_START = False                                    # 是否在开始之前清空 调度器和去重记录,True=清空,False=不清空
12 # SCHEDULER_IDLE_BEFORE_CLOSE = 10                                    # 去调度器中获取数据时,如果为空,最多等待时间(最后没数据,未获取到)。
13 # SCHEDULER_DUPEFILTER_KEY = ‘%(spider)s:dupefilter‘                  # 去重规则,在redis中保存时对应的key
14 # SCHEDULER_DUPEFILTER_CLASS = ‘scrapy_redis.dupefilter.RFPDupeFilter‘# 去重规则对应处理的类
15 #
16 #
17 #
18 # REDIS_HOST = ‘10.211.55.13‘                           # 主机名
19 # REDIS_PORT = 6379                                     # 端口
20 # # REDIS_URL = ‘redis://user:[email protected]:9001‘       # 连接URL(优先于以上配置)
21 # # REDIS_PARAMS  = {}                                  # Redis连接参数             默认:REDIS_PARAMS = {‘socket_timeout‘: 30,‘socket_connect_timeout‘: 30,‘retry_on_timeout‘: True,‘encoding‘: REDIS_ENCODING,})
22 # # REDIS_PARAMS[‘redis_cls‘] = ‘myproject.RedisClient‘ # 指定连接Redis的Python模块  默认:redis.StrictRedis
23 # REDIS_ENCODING = "utf-8"                              # redis编码类型             默认:‘utf-8‘
View Code

2、爬虫文件

技术分享
 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
View Code

 

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