继上次Scrapy爬取猫眼电影之后，这几天学习了Scrapy-Redis分布式来提高爬取效率，也算是停留在舒适圈一段时间后往前走了一步！！
准备工作
MongoDB
Redis
Scrapy-Redis
Scrapy
这次爬取的是上海自如租房，相信在魔都生活的小伙伴们如果不是本地人，租房费用占了每月开销很大的一部分，我们来看下租房体验比较好的自如，除了价格贵外 - -！！
实战应用
创建一个工程
scrapy startproject ziru
第一步 编辑item.py
import scrapy
class ZiruItem(scrapy.Item):
# define the fields for your item here like:
# name = scrapy.Field()
ziroom_area = scrapy.Field()
ziroom_face = scrapy.Field()
ziroom_floor = scrapy.Field()
ziroom_label = scrapy.Field()
# ziroom_location = scrapy.Field()
ziroom_name = scrapy.Field()
ziroom_price = scrapy.Field()
ziroom_type = scrapy.Field()
ziroom_traffic = scrapy.Field()
rounding_info = scrapy.Field()
traffic_info = scrapy.Field()
ziroom_image = scrapy.Field()
pass
- 首先，引入Scrapy
- 接着，创建一个类，继承自scrapy.item,这个是用来储存要爬下来的数据的存放容器
第二步 获取网页数据
在spider文件下创建spider.py
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# -*- coding: utf-8 -*-
from scrapy.spiders import Rule
from scrapy.selector import Selector
from scrapy.linkextractors import LinkExtractor
from ziru.items import ZiruItem
from scrapy_redis.spiders import RedisCrawlSpider
class ZiroomSpider(RedisCrawlSpider):
name = 'ziroom'
# allowed_domains = ['http://sh.ziroom.com/z/nl/z2.html?qwd=']
# start_urls = ['http://sh.ziroom.com/z/nl/z2.html?qwd=']
redis_key = 'ziroomspider:start_urls'
rules = (
Rule(LinkExtractor(allow=(r'http://sh.ziroom.com/z/nl/z2.html\?qwd=\&p=\d+'))),
Rule(LinkExtractor(allow=(r'http:\//sh\.ziroom\.com\/z\/vr\/\d+\.html')), callback='parse_item')
)
def parse_item(self, response):
# print(response.body)
sel = Selector(response)
...省略索取元素的代码...
yield item
- 比起Scrapy，又多引入了 from scrapy_redis.spiders import RedisCrawlSpider
- start_urls变为redis_key = 'ziroomspider:start_urls' 作为所有链接存储到 redis
- 爬取rule还是一个链接为翻页，一个为详情页链接
第三步 编辑管道pipeline.py
import pymongo
from scrapy.conf import settings
from scrapy.exceptions import DropItem
from scrapy import log
class MongoDBPipeline(object):
def __init__(self):
client = pymongo.MongoClient(settings['MONGODB_SERVER'], settings['MONGODB_PORT'])
db = client[settings['MONGODB_DB']]
self.collection = db[settings['MONGODB_COLLECTION']]
def process_item(self, item, spider):
# item: (Item 对象) – 被爬取的item
# (Spider 对象) – 爬取该item的spider
# 去重，删除重复的数据
valid = True
for data in item:
if not data:
valid = False
raise DropItem('Missing %s of blogpost from %s' % (data, item['url']))
if valid:
homes = [{
'ziroom_area': item['ziroom_area'],
'ziroom_face': item['ziroom_face'],
'ziroom_floor': item['ziroom_floor'],
'ziroom_label': item['ziroom_label'],
# 'ziroom_location': item['ziroom_location'],
'ziroom_name' :item['ziroom_name'],
'ziroom_price' : item['ziroom_price'],
'ziroom_type' : item['ziroom_type'],
'ziroom_traffic': item['ziroom_traffic'],
'rounding_info': item['rounding_info'],
'traffic_info': item['traffic_info'],
'ziroom_image': item['ziroom_image'],
}]
# 插入数据库集合中
self.collection.insert(homes)
log.msg('Item wrote to MongoDB database %s/%s' % (settings['MONGODB_DB'], settings['MONGODB_COLLECTION']),
level=log.DEBUG, spider=spider)
return item
编辑MongoDBpipelines，将获取的数据存入MongoDB数据库中
第四步 编辑middlewares.py
在中间件中写入随机选取伪造请求头来防止spider被封掉
class RotateUserAgentMiddleware(UserAgentMiddleware):
def __int__(self, user_agent=''):
self.user_agent = user_agent
def process_request(self, request, spider):
# 这句话用于随机选择user-agent
ua = random.choice(self.user_agent_list)
if ua:
logging.info(ua)
request.headers.setdefault('User-Agent', ua)
# the default user_agent_list composes chrome,I E,firefox,Mozilla,opera,netscape
# for more user agent strings,you can find it in http://www.useragentstring.com/pages/useragentstring.php
user_agent_list = [
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/22.0.1207.1 Safari/537.1",
"Mozilla/5.0 (X11; CrOS i686 2268.111.0) AppleWebKit/536.11 (KHTML, like Gecko) Chrome/20.0.1132.57 Safari/536.11",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1092.0 Safari/536.6",
"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1090.0 Safari/536.6",
"Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/19.77.34.5 Safari/537.1",
"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.9 Safari/536.5",
"Mozilla/5.0 (Windows NT 6.0) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.36 Safari/536.5",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
"Mozilla/5.0 (Windows NT 5.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",
"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
"Mozilla/5.0 (Windows NT 6.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.0 Safari/536.3",
"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24",
"Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24",
"Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US) AppleWebKit/531.21.8 (KHTML, like Gecko) Version/4.0.4 Safari/531.21.10",
"Mozilla/5.0 (Windows; U; Windows NT 5.2; en-US) AppleWebKit/533.17.8 (KHTML, like Gecko) Version/5.0.1 Safari/533.17.8",
"Mozilla/5.0 (Windows; U; Windows NT 6.1; en-US) AppleWebKit/533.19.4 (KHTML, like Gecko) Version/5.0.2 Safari/533.18.5",
"Mozilla/5.0 (Windows; U; Windows NT 6.1; en-GB; rv:1.9.1.17) Gecko/20110123 (like Firefox/3.x) SeaMonkey/2.0.12",
"Mozilla/5.0 (Windows NT 5.2; rv:10.0.1) Gecko/20100101 Firefox/10.0.1 SeaMonkey/2.7.1",
"Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_5_8; en-US) AppleWebKit/532.8 (KHTML, like Gecko) Chrome/4.0.302.2 Safari/532.8",
"Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_4; en-US) AppleWebKit/534.3 (KHTML, like Gecko) Chrome/6.0.464.0 Safari/534.3",
"Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_5; en-US) AppleWebKit/534.13 (KHTML, like Gecko) Chrome/9.0.597.15 Safari/534.13",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_2) AppleWebKit/535.1 (KHTML, like Gecko) Chrome/14.0.835.186 Safari/535.1",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_8) AppleWebKit/535.2 (KHTML, like Gecko) Chrome/15.0.874.54 Safari/535.2",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_8) AppleWebKit/535.7 (KHTML, like Gecko) Chrome/16.0.912.36 Safari/535.7",
"Mozilla/5.0 (Macintosh; U; Mac OS X Mach-O; en-US; rv:2.0a) Gecko/20040614 Firefox/3.0.0 ",
"Mozilla/5.0 (Macintosh; U; PPC Mac OS X 10.5; en-US; rv:1.9.0.3) Gecko/2008092414 Firefox/3.0.3",
"Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10.5; en-US; rv:1.9.1) Gecko/20090624 Firefox/3.5",
"Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10.6; en-US; rv:1.9.2.14) Gecko/20110218 AlexaToolbar/alxf-2.0 Firefox/3.6.14",
"Mozilla/5.0 (Macintosh; U; PPC Mac OS X 10.5; en-US; rv:1.9.2.15) Gecko/20110303 Firefox/3.6.15",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10.6; rv:2.0.1) Gecko/20100101 Firefox/4.0.1"
]
第五步 设置setting.py
这一步要修改配置了
DOWNLOADER_MIDDLEWARES = {
# 'ziru.middlewares.MyCustomDownloaderMiddleware': 543,
'ziru.middlewares.RotateUserAgentMiddleware':200,
'scrapy.downloadermiddlewares.retry.RetryMiddleware': 80,
# 'itjuzi_dis.middlewares.ProxyMiddleware': 90,
'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware': 100,
}
ITEM_PIPELINES = {
'ziru.pipelines.MongoDBPipeline': 300,
'scrapy_redis.pipelines.RedisPipeline': 400,
}
#使用Scrapy-Redis的调度器
SCHEDULER = "scrapy_redis.scheduler.Scheduler"
#利用Redis的集合实现去重
DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"
#允许继续爬取
SCHEDULER_PERSIST = True
#设置优先级
SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.SpiderPriorityQueue'
REDIS_PARAMS = {'host': 'localhost', 'port': '6379'}
好了，所有的配置全部部署完了，现在来启动spider来爬取数据吧！！
scrapy crawl ziroom
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spider启动，它在等待我们的指令来爬取
打开redis-cli
lpush ziroomspider:start_urls http://sh.ziroom.com/z/nl/z2.html?qwd=
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我开了六个spider来爬取，电脑CPU有几个处理器就能开几个，我是8核，最多能开8个，接下来准备学习docker来部署spider
完整代码
[欢迎访问Treehl的博客(https://family-treesy.github.io/)
最后放一个爬虫集合，是我最近学习Python写的，喜欢的亲！给个Star呗！！！
SpiderList