scrapy-redis使用以及剖析

Posted 2020-10-05 ForeverPine

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

一、scrapy-redis组件 

1. URL去重

 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:pass@hostname: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"

2. 调度器

 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　　

3. 数据持久化

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

4. 起始URL相关

 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\'

二、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:pass@hostname: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\'

配置文件

 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

爬虫文件