虽然scrapy能做的事情很多,但是要做到大规模的分布式应用则捉襟见肘。有能人改变了scrapy的队列调度,将起始的网址从start_urls里分离出来,改为从redis读取,多个客户端可以同时读取同一个redis,从而实现了分布式的爬虫。就算在同一台电脑上,也可以多进程的运行爬虫,在大规模抓取的过程中非常有效。
准备:
1、windows一台(从:scrapy)
2、linux一台(主:scrapy\redis\mongo)
ip:192.168.184.129
3、python3.6
linux下scrapy的配置步骤:
1、安装python3.6
yum install openssl-devel -y 解决pip3不能使用的问题(pip is configured with locations that require TLS/SSL, however the ssl module in Python is not available)
下载python软件包,Python-3.6.1.tar.xz,解压后
./configure --prefix=/python3
make
make install
加上环境变量:
PATH=/python3/bin:$PATH:$HOME/bin
export PATH
安装完成后,pip3默认也已经安装完成了(安装前需要先yum gcc)
2、安装Twisted
下载Twisted-17.9.0.tar.bz2,解压后 cd Twisted-17.9.0, python3 setup.py install
3、安装scrapy
pip3 install scrapy
pip3 install scrapy-redis
4、安装redis
见博文redis安装与简单使用
错误:You need tcl 8.5 or newer in order to run the Redis test
1、wget http://downloads.sourceforge.net/tcl/tcl8.6.1-src.tar.gz
2、tar -xvf tcl8.6.1-src.tar.gz
3、cd tcl8.6.1/unix ; make; make install
cp /root/redis-3.2.11/redis.conf /etc/
启动:/root/redis-3.2.11/src/redis-server /etc/redis.conf &
5、pip3 install redis
6、安装mongodb
启动:# mongod --bind_ip 192.168.184.129 &
7、pip3 install pymongo
windows上scrapy的部署步骤:
'''
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'''
1、安装wheel
pip install wheel
2、安装lxml
https://pypi.python.org/pypi/lxml/4.1.0
3、安装pyopenssl
https://pypi.python.org/pypi/pyOpenSSL/17.5.0
4、安装Twisted
https://www.lfd.uci.edu/~gohlke/pythonlibs/
5、安装pywin32
https://sourceforge.net/projects/pywin32/files/
6、安装scrapy
pip install scrapy
部署代码:
我以美剧天堂的电影爬取为简单例子,说一下分布式的实现,代码linux和windows上各放一份,配置一样,两者可同时运行爬取。
只列出需要修改的地方:
settings
设置爬取数据的存储数据库(mongodb),指纹和queue存储的数据库(redis)
'''
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'''
ROBOTSTXT_OBEY = False # 禁止robot
CONCURRENT_REQUESTS = 1 # scrapy调试queue的最大并发,默认16
ITEM_PIPELINES = {
'meiju.pipelines.MongoPipeline': 300,
}
MONGO_URI = '192.168.184.129' # mongodb连接信息
MONGO_DATABASE = 'mj'
SCHEDULER = "scrapy_redis.scheduler.Scheduler" # 使用scrapy_redis的调度
DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter" # 在redis库中去重(url)
# REDIS_URL = 'redis://root:kongzhagen@localhost:6379' # 如果redis有密码,使用这个配置
REDIS_HOST = '192.168.184.129' #redisdb连接信息
REDIS_PORT = 6379
SCHEDULER_PERSIST = True # 不清空指纹
piplines
存储到MongoDB的代码
'''
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'''
import pymongo
class MeijuPipeline(object):
def process_item(self, item, spider):
return item
class MongoPipeline(object):
collection_name = 'movies'
def __init__(self, mongo_uri, mongo_db):
self.mongo_uri = mongo_uri
self.mongo_db = mongo_db
@classmethod
def from_crawler(cls, crawler):
return cls(
mongo_uri=crawler.settings.get('MONGO_URI'),
mongo_db=crawler.settings.get('MONGO_DATABASE', 'items')
)
def open_spider(self, spider):
self.client = pymongo.MongoClient(self.mongo_uri)
self.db = self.client[self.mongo_db]
def close_spider(self, spider):
self.client.close()
def process_item(self, item, spider):
self.db[self.collection_name].insert_one(dict(item))
return item
items
数据结构
import scrapy
class MeijuItem(scrapy.Item):
movieName = scrapy.Field()
status = scrapy.Field()
english = scrapy.Field()
alias = scrapy.Field()
tv = scrapy.Field()
year = scrapy.Field()
type = scrapy.Field()
爬虫脚本mj.py
'''
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'''
# -*- coding: utf-8 -*-
import scrapy
from scrapy import Request
class MjSpider(scrapy.Spider):
name = 'mj'
allowed_domains = ['meijutt.com']
# start_urls = ['http://www.meijutt.com/file/list1.html']
def start_requests(self):
yield Request(url='http://www.meijutt.com/file/list1.html', callback=self.parse)
def parse(self, response):
from meiju.items import MeijuItem
movies = response.xpath('//div[@class="cn_box2"]')
for movie in movies:
item = MeijuItem()
item['movieName'] = movie.xpath('./ul[@class="list_20"]/li[1]/a/text()').extract_first()
item['status'] = movie.xpath('./ul[@class="list_20"]/li[2]/span/font/text()').extract_first()
item['english'] = movie.xpath('./ul[@class="list_20"]/li[3]/font[2]/text()').extract_first()
item['alias'] = movie.xpath('./ul[@class="list_20"]/li[4]/font[2]/text()').extract_first()
item['tv'] = movie.xpath('./ul[@class="list_20"]/li[5]/font[2]/text()').extract_first()
item['year'] = movie.xpath('./ul[@class="list_20"]/li[6]/font[2]/text()').extract_first()
item['type'] = movie.xpath('./ul[@class="list_20"]/li[7]/font[2]/text()').extract_first()
yield item
for i in response.xpath('//div[@class="cn_box2"]/ul[@class="list_20"]/li[1]/a/@href').extract():
yield Request(url='http://www.meijutt.com' + i)
# next = 'http://www.meijutt.com' + response.xpath("//a[contains(.,'下一页')]/@href")[1].extract()
# print(next)
# yield Request(url=next, callback=self.parse)
img
看一下redis中的情况:
img看看mongodb中的数据:
img
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