为什么要学？

Scrapy_redis在scrapy的基础上实现了更多，更强大的功能。

有哪些功能体现？

request去重、爬虫持久化、实现分布式爬虫、断点续爬（带爬取的request存在redis中）、增量式爬虫（爬取过的生成指纹）

工作流程

先来看看之前的爬虫流程

再来看看scrapy_redis的爬虫流程

 

安装：

pip install scrapy-redis

源码包安装：

git clone git://github.com/rolando/scrapy-redis

官方文档在：

scrapy_redis 的源码在github：

它提供了三个demo在example-projec/example中

 

三个案例有

 

先来看第一个案例：

dmoz.py

from scrapy.linkextractors import LinkExtractorfrom scrapy.spiders import CrawlSpider, Ruleclass DmozSpider(CrawlSpider):    """Follow categories and extract links."""    name = 'dmoz'    allowed_domains = ['dmoz.org']    start_urls = ['http://www.dmoz.org/']    rules = [        Rule(LinkExtractor(            restrict_css=('.top-cat', '.sub-cat', '.cat-item')        ), callback='parse_directory', follow=True),    ]    def parse_directory(self, response):        for div in response.css('.title-and-desc'):            yield {                'name': div.css('.site-title::text').extract_first(),                'description': div.css('.site-descr::text').extract_first().strip(),                'link': div.css('a::attr(href)').extract_first(),            }

这个案例很像我们自己写的crawlspider什么区别,所以接下来就要进行配置操作

先来看看官方的 Use the following settings in your project: 

1 # 指定schedule队列 2 # Enables scheduling storing requests queue in redis. 3 SCHEDULER = "scrapy_redis.scheduler.Scheduler" 4  5  6 # 指定哪个去重方法给request对象去重 7 # Ensure all spiders share same duplicates filter through redis. 8 DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter" 9 10 # Default requests serializer is pickle, but it can be changed to any module11 # with loads and dumps functions. Note that pickle is not compatible between12 # python versions.13 # Caveat: In python 3.x, the serializer must return strings keys and support14 # bytes as values. Because of this reason the json or msgpack module will not15 # work by default. In python 2.x there is no such issue and you can use16 # 'json' or 'msgpack' as serializers.17 #SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"18 19 # 队列中的内容是否持久保存，False：在关闭redis的时候清空redis20 # Don't cleanup redis queues, allows to pause/resume crawls.21 #SCHEDULER_PERSIST = True22 23 # Schedule requests using a priority queue. (default)24 #SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.PriorityQueue'25 26 # Alternative queues.27 #SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.FifoQueue'28 #SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.LifoQueue'29 30 # Max idle time to prevent the spider from being closed when distributed crawling.31 # This only works if queue class is SpiderQueue or SpiderStack,32 # and may also block the same time when your spider start at the first time (because the queue is empty).33 #SCHEDULER_IDLE_BEFORE_CLOSE = 1034 35 # scrapy_redis实现的items保存到redis的pipeline36 # Store scraped item in redis for post-processing.37 ITEM_PIPELINES = {38     'scrapy_redis.pipelines.RedisPipeline': 30039 }40 41 # The item pipeline serializes and stores the items in this redis key.42 #REDIS_ITEMS_KEY = '%(spider)s:items'43 44 # The items serializer is by default ScrapyJSONEncoder. You can use any45 # importable path to a callable object.46 #REDIS_ITEMS_SERIALIZER = 'json.dumps'47 48 # 指定redis的地址49 # Specify the host and port to use when connecting to Redis (optional).50 #REDIS_HOST = 'localhost'51 #REDIS_PORT = 637952 53 54 # 指定redis的地址55 # Specify the full Redis URL for connecting (optional).56 # If set, this takes precedence over the REDIS_HOST and REDIS_PORT settings.57 #REDIS_URL = 'redis://user:pass@hostname:9001'58 59 # Custom redis client parameters (i.e.: socket timeout, etc.)60 #REDIS_PARAMS  = {}61 # Use custom redis client class.62 #REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient'63 64 # If True, it uses redis' ``spop`` operation. This could be useful if you65 # want to avoid duplicates in your start urls list. In this cases, urls must66 # be added via ``sadd`` command or you will get a type error from redis.67 #REDIS_START_URLS_AS_SET = False68 69 # Default start urls key for RedisSpider and RedisCrawlSpider.70 #REDIS_START_URLS_KEY = '%(name)s:start_urls'71 72 # Use other encoding than utf-8 for redis.73 #REDIS_ENCODING = 'latin1'

 

所以我们需要做的就是在配置文件中添加这几行

# 去重DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"# 调度器SCHEDULER = "scrapy_redis.scheduler.Scheduler"# 调度器持久化SCHEDULER_PERSIST = True# 指定redis地址REDIS_URL = "redis://192.168.226.150:6379"ITEM_PIPELINES = {    'example.pipelines.ExamplePipeline': 300,    'scrapy_redis.pipelines.RedisPipeline': 400, # 保存数据到redis}

在这里也贴上github上的settings：

# Scrapy settings for example project## For simplicity, this file contains only the most important settings by# default. All the other settings are documented here:##     http://doc.scrapy.org/topics/settings.html#SPIDER_MODULES = ['example.spiders']NEWSPIDER_MODULE = 'example.spiders'USER_AGENT = 'scrapy-redis (+https://github.com/rolando/scrapy-redis)'DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"SCHEDULER = "scrapy_redis.scheduler.Scheduler"SCHEDULER_PERSIST = True#SCHEDULER_QUEUE_CLASS = "scrapy_redis.queue.SpiderPriorityQueue"#SCHEDULER_QUEUE_CLASS = "scrapy_redis.queue.SpiderQueue"#SCHEDULER_QUEUE_CLASS = "scrapy_redis.queue.SpiderStack"ITEM_PIPELINES = {    'example.pipelines.ExamplePipeline': 300,    'scrapy_redis.pipelines.RedisPipeline': 400,}LOG_LEVEL = 'DEBUG'# Introduce an artifical delay to make use of parallelism. to speed up the# crawl.DOWNLOAD_DELAY = 1

接下来我们就运行，跟往常的运行命令一样，切换到example 下，执行命令

\example>scrapy crawl dmoz

然后就去redis中查看

可以看到多了三个键

 dmoz:items ：存放获取到的item信息，在pipeline中开启RedisPipeline才会存入

  dmoz:dupefilter ：指纹集合，存放的是已经进入 scheduler 队列的 request 对象的指纹，指纹默认由请求方法，url和请求体组成

  dmoz:requests ：Scheduler队列，存放着待请求的 request 对象，获取的过程是pop操作，即获取一个会去除一个

三个键的类型：

以及数据

items

dupefilter

requests

如果我们不想把数据存放到redis，而是放到其他的地方，应该怎么做？

先来测试一下redispiipeline 关闭的情况

#ITEM_PIPELINES = {
        # 'example.pipelines.ExamplePipeline': 300,    #'scrapy_redis.pipelines.RedisPipeline': 400, # 保存数据到redis#}

再看看redis数据库中这三个键如何变化，变化结果：

dmoz:requests 有变化(变多或者变少或者不变)dmoz:dupefilter 变多dmoz:items 不变

所以 redispipeline中仅仅实现了item数据存储到redis的过程，我们可以新建一个pipeline（或者修改默认的ExamplePipeline），让数据存储到其他地方。

接下来看一下 RedisPipeline 的源码段

from scrapy_redis.pipelines import RedisPipeline    # 调用这个方法，实现数据的保存    def process_item(self, item, spider):    # 调用一个异步线程去处理这个item        return deferToThread(self._process_item, item, spider)    def _process_item(self, item, spider):        key = self.item_key(item, spider)        data = self.serialize(item)       # 向dmoz:items中添加item        self.server.rpush(key, data)        return item

去重的方法，通过生成指纹识别：指纹默认由请求方法，url和请求体组成

- 使用sha1加密request得到指纹- 把指纹存在redis的集合中- 下一次新来一个request，同样的方式生成指纹，判断指纹是否存在reids的集合中

- fp = hashlib.sha1()

- fp.update(request.method)

- fp.update(request.body or b"")

- fp.update(url)

- fp.hexdigest()

判断数据是否存在redis的集合中，不存在插入

added = self.server.sadd(self.key, fp)return added != 0

去重的的类 RFPDupeFilter ：

 

主要是这三个方法:

request_seen:判断requests对象是否已经存在,如果没有就添加到“dmoz:dupefilter”

request_fingerprint:调用函数request_fingerprint

request_fingerprint：主要是对请求进行加密生成指纹 下面来看看调度器：

总结： domz案例相当于之前的spider多了两个内容： 1、持久化 2、request去重的功能 通过源码以及setting中的配置来看，我们可以重写 去重 和 调度器的方法 ，还有存储数据的 pipeline 。在配置中改成我们重写的类就行。

 

 

Scrapy_redis 之 RedisSpider

这是scrapy_redis 的第二个案例

先来看试一下初始源码 

from scrapy_redis.spiders import RedisSpiderclass MySpider(RedisSpider):    """Spider that reads urls from redis queue (myspider:start_urls)."""    name = 'myspider_redis'    redis_key = 'myspider:start_urls'    def __init__(self, *args, **kwargs):        # Dynamically define the allowed domains list.        domain = kwargs.pop('domain', '')        self.allowed_domains = filter(None, domain.split(','))        super(MySpider, self).__init__(*args, **kwargs)    def parse(self, response):        return {            'name': response.css('title::text').extract_first(),            'url': response.url,        }

解析源码

 

配置文件设置：

# 去重DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"# 调度器SCHEDULER = "scrapy_redis.scheduler.Scheduler"# 调度器持久化SCHEDULER_PERSIST = True# 指定redis地址REDIS_URL = "redis://192.168.226.150:6379"ITEM_PIPELINES = {    'example.pipelines.ExamplePipeline': 300,    'scrapy_redis.pipelines.RedisPipeline': 400, # 保存数据到redis}

start_url 只能由一台机器爬取，其他机器刚开始处于等待状态，这是随机的

但是这里的start_url 改为redis_key='自定义键名' 例如('dangdang')

那么执行的启动命令就是在redis中执行这条语句：lpush 健名 起始url

lpush dangdang http://www.dangdang.com

 

 

 

Scrapy_redis 之 RedisCrawlSpider

这是scrapy_redis 的第三个案例

先来看初始源码

from scrapy.spiders import Rulefrom scrapy.linkextractors import LinkExtractorfrom scrapy_redis.spiders import RedisCrawlSpiderclass MyCrawler(RedisCrawlSpider):    """Spider that reads urls from redis queue (myspider:start_urls)."""    name = 'mycrawler_redis'    redis_key = 'mycrawler:start_urls'    rules = (        # follow all links        Rule(LinkExtractor(), callback='parse_page', follow=True),    )    def __init__(self, *args, **kwargs):        # Dynamically define the allowed domains list.        domain = kwargs.pop('domain', '')        self.allowed_domains = filter(None, domain.split(','))        super(MyCrawler, self).__init__(*args, **kwargs)    def parse_page(self, response):        return {            'name': response.css('title::text').extract_first(),            'url': response.url,        }

解析源码

 

配置文件

# 去重DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"# 调度器SCHEDULER = "scrapy_redis.scheduler.Scheduler"# 调度器持久化SCHEDULER_PERSIST = True# 指定redis地址REDIS_URL = "redis://192.168.226.150:6379"ITEM_PIPELINES = {    'example.pipelines.ExamplePipeline': 300,    'scrapy_redis.pipelines.RedisPipeline': 400, # 保存数据到redis}

这个案例跟crawlspider的使用差不多，也是没有start_url 改为了 redis_key 

启动方式跟案例二一样。爬虫准备就绪，redis数据库中

lpush 健名 起始url