pip install scrapy-redis
easy_install scrapy-redis
下载
http://redis.io/download
版本推荐
stable 3.0.2
运行redis
redis-server redis.conf
清空缓存
redis-cli flushdb
settings.py配置redis(在scrapy-redis 自带的例子中已经配置好)
SCHEDULER = "scrapy_redis.scheduler.Scheduler"
SCHEDULER_PERSIST = True
SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.SpiderPriorityQueue'
REDIS_URL = None # 一般情况可以省去
REDIS_HOST = '127.0.0.1' # 也可以根据情况改成 localhost
REDIS_PORT = 6379
spider 继承RedisSpider
class tempSpider(RedisSpider)
name = "temp"
redis_key = ''temp:start_url"
在redis的src目录下,执行 ./redis-server启动服务器
执行 ./redis-cli 启动客户端
启动scropy-redis的代码;
如启动name= "lhy",start_urls="lhy:start_urls" 的spider。
如果在redis中没有 主键为lhy:start_urls 的list,则爬虫已只监听等待。
此时,在redis客户端执行:lpush lhy:start_urls http://blog.csdn.net/u013378306/article/details/53888173
可以看到爬虫开始抓取。在 redis客户端下输入 keys *,查看所有主键
原来的 lhy:start_urls 已经被自动删除,并新建了 一个lhy:dupefilter (set),一个 lhy:items (list), 一个 lhy:requests(zset)
lhy:dupefilter用来存储 已经requests 过的url的hash值,分布式去重时使用到, lhy:items是分布式生成的items,lhy:requests是新生成的 url封装后的requests。
理论上,lhy:dupefilter 等于已经request的数量,一直增加
lhy:items 是经过 spider prase生成的
lhy:requests 是有序集合ZSET,scrapy-redis 重新吧他封装成了一个队列,requests是spider 解析生成新url后重新封装,如果不载有新的url产生,则随着spider的prase,一直减少。总之取request时出队列,新的url会重新封装成request后增加进来,入队列。
scrapy-redis 重写了scrapy的多个类,具体请看http://blog.csdn.net/u013378306/article/details/53992707
并且在setting.py中 配置了这些类,所以当运行scrapy-redis例子时,自动使用了scrapy-redis 重写的类。
下载scrapy-redis源代码 https://github.com/rolando/scrapy-Redis
文档结构如下:
其中,src 中是scrapy-redis的源代码。
example-redis 是写好的例子,其中有三个例子
(1)domz.py (2) mycrawler_redis.py (3) myspider.py
文档中队者三个例子的解释如下
* **dmoz**
This spider simply scrapes dmoz.org.
* **myspider_redis**
This spider uses redis as a shared requests queue and uses
``myspider:start_urls`` as start URLs seed. For each URL, the spider outputs
one item.
* **mycrawler_redis**
This spider uses redis as a shared requests queue and uses
``mycrawler:start_urls`` as start URLs seed. For each URL, the spider follows
are links.
domz.py :此例子仅仅是抓取一个网站下的数据,没有用分布式
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule
class 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(),
}
mycrawler_redis.py
此例子 使用 RedisCrawlSpider类,支持分布式去重爬取,并且 可以定义抓取连接的rules
from scrapy.spiders import Rule
from scrapy.linkextractors import LinkExtractor
from scrapy_redis.spiders import RedisCrawlSpider
class 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,
}
from scrapy_redis.spiders import RedisSpider
class 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,
}