scrapyredis使用以及剖析[Python基础]

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提供了下面四种组件（components）：(四种组件意味着这四个模块都要做相应的修改)

• Scheduler
• Duplication Filter
• Item Pipeline
• Base Spider

scrapy-redis组件

scrapy-redis架构

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"

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

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

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

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"
24 
25 配置文件

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