scrapy-redis使用以及剖析

Posted 2020-10-05 敏而好学，不耻下问。

 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

scrapy-redis组件

1. URL去重

定义去重规则（被调度器调用并应用）

    a. 内部会使用以下配置进行连接Redis

        # REDIS_HOST = \'localhost\'                            # 主机名
        # REDIS_PORT = 6379                                   # 端口
        # REDIS_URL = \'redis://user:pass@hostname:9001\'       # 连接URL（优先于以上配置）
        # 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,}）
        # REDIS_PARAMS[\'redis_cls\'] = \'myproject.RedisClient\' # 指定连接Redis的Python模块  默认：redis.StrictRedis
        # REDIS_ENCODING = "utf-8"                            # redis编码类型             默认：\'utf-8\'
    
    b. 去重规则通过redis的集合完成，集合的Key为：
    
        key = defaults.DUPEFILTER_KEY % {\'timestamp\': int(time.time())}
        默认配置：
            DUPEFILTER_KEY = \'dupefilter:%(timestamp)s\'
             
    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
    
        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参数位置不同时，计算结果一致；
            - 默认请求头不在计算范围，include_headers可以设置指定请求头
            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. 调度器

"""
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
    
    a. 调度器
        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）
        SCHEDULER_QUEUE_KEY = \'%(spider)s:requests\'                         # 调度器中请求存放在redis中的key
        SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"                  # 对保存到redis中的数据进行序列化，默认使用pickle
        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
        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
        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）。
        SCHEDULER_DUPEFILTER_KEY = \'%(spider)s:dupefilter\'                  # 去重规则，在redis中保存时对应的key
        SCHEDULER_DUPEFILTER_CLASS = \'scrapy_redis.dupefilter.RFPDupeFilter\'# 去重规则对应处理的类


"""
# 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. 数据持久化

2. 定义持久化，爬虫yield Item对象时执行RedisPipeline
    
    a. 将item持久化到redis时，指定key和序列化函数
    
        REDIS_ITEMS_KEY = \'%(spider)s:items\'
        REDIS_ITEMS_SERIALIZER = \'json.dumps\'
    
    b. 使用列表保存item数据

4. 起始URL相关

"""
起始URL相关

    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
        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
    b. 编写爬虫时，起始URL从redis的Key中获取
        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\'          # 默认使用优先级队列（默认），其他：PriorityQueue（有序集合），FifoQueue（列表）、LifoQueue（列表）
# SCHEDULER_QUEUE_KEY = \'%(spider)s:requests\'                         # 调度器中请求存放在redis中的key
# SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"                  # 对保存到redis中的数据进行序列化，默认使用pickle
# 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
# 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
# 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）。
# SCHEDULER_DUPEFILTER_KEY = \'%(spider)s:dupefilter\'                  # 去重规则，在redis中保存时对应的key
# SCHEDULER_DUPEFILTER_CLASS = \'scrapy_redis.dupefilter.RFPDupeFilter\'# 去重规则对应处理的类
#
#
#
# REDIS_HOST = \'10.211.55.13\'                           # 主机名
# REDIS_PORT = 6379                                     # 端口
# # REDIS_URL = \'redis://user:pass@hostname:9001\'       # 连接URL（优先于以上配置）
# # 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,}）
# # REDIS_PARAMS[\'redis_cls\'] = \'myproject.RedisClient\' # 指定连接Redis的Python模块  默认：redis.StrictRedis
# REDIS_ENCODING = "utf-8"                              # redis编码类型             默认：\'utf-8\'

配置文件

import scrapy


class 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

爬虫文件