scrapy实战2分布式爬取lagou招聘（加入了免费的User-Agent随机动态获取库 fake-useragent 使用方法查看：https://github.com/hellysmile/fake-useragent）

items.py

 # -*- coding: utf-8 -*-

 # Define here the models for your scraped items
 #
 # See documentation in:
 # http://doc.scrapy.org/en/latest/topics/items.html

 import scrapy
 class LagouItem(scrapy.Item):
     # define the fields for your item here like:
     # name = scrapy.Field()
     #id
     obj_id=scrapy.Field()
     #职位名
     positon_name=scrapy.Field()
     #工作地点
     work_place=scrapy.Field()
     #发布日期
     publish_time=scrapy.Field()
     #工资
     salary=scrapy.Field()
     #工作经验
     work_experience=scrapy.Field()
     #学历
     education=scrapy.Field()
     #full_time
     full_time=scrapy.Field()
     #标签
     tags=scrapy.Field()
     #公司名字
     company_name=scrapy.Field()
     # #产业
     # industry=scrapy.Field()
     #职位诱惑
     job_temptation=scrapy.Field()
     #工作描述
     job_desc=scrapy.Field()
     #公司logo地址
     logo_image=scrapy.Field()
      #领域
     field=scrapy.Field()
     #发展阶段
     stage=scrapy.Field()
     #公司规模
     company_size=scrapy.Field()
     # 公司主页
     home = scrapy.Field()
     #职位发布者
     job_publisher=scrapy.Field()
     #投资机构
     financeOrg=scrapy.Field()
     #爬取时间
     crawl_time=scrapy.Field()

spiders>lagou.py

 # -*- coding: utf-8 -*-
 import scrapy
 from scrapy.linkextractors import LinkExtractor
 from scrapy.spiders import CrawlSpider, Rule
 from LaGou.items import LagouItem
 from LaGou.utils.MD5 import get_md5
 from datetime import datetime

 class LagouSpider(CrawlSpider):
     name = 'lagou'
     allowed_domains = ['lagou.com']
     start_urls = ['https://www.lagou.com/zhaopin/']
     content_links=LinkExtractor(allow=(r"https://www.lagou.com/jobs/\d+.html"))
     page_links=LinkExtractor(allow=(r"https://www.lagou.com/zhaopin/\d+"))
     rules = (
         Rule(content_links, callback="parse_item", follow=False),
         Rule(page_links,follow=True)
     )

     def parse_item(self, response):
         item=LagouItem()
         #获取到公司拉钩主页的url作为ID
         item["obj_id"]=get_md5(response.url)
         #公司名称
         item["company_name"]=response.xpath('//dl[@class="job_company"]//a/img/@alt').extract()[0]
         # 职位
         item["positon_name"]=response.xpath('//div[@class="job-name"]//span[@class="name"]/text()').extract()[0]
         #工资
         item["salary"]=response.xpath('//dd[@class="job_request"]//span[1]/text()').extract()[0]
         # 工作地点
         work_place=response.xpath('//dd[@class="job_request"]//span[2]/text()').extract()[0]
         item["work_place"]=work_place.replace("/","")
         # 工作经验
         work_experience=response.xpath('//dd[@class="job_request"]//span[3]/text()').extract()[0]
         item["work_experience"]=work_experience.replace("/","")
         # 学历
         education=response.xpath('//dd[@class="job_request"]//span[4]/text()').extract()[0]
         item["education"]=education.replace("/","")
         # full_time
         item['full_time']=response.xpath('//dd[@class="job_request"]//span[5]/text()').extract()[0]
         #tags
         tags=response.xpath('//dd[@class="job_request"]//li[@class="labels"]/text()').extract()
         item["tags"]=",".join(tags)
         #publish_time
         item["publish_time"]=response.xpath('//dd[@class="job_request"]//p[@class="publish_time"]/text()').extract()[0]
         # 职位诱惑
         job_temptation=response.xpath('//dd[@class="job-advantage"]/p/text()').extract()
         item["job_temptation"]=",".join(job_temptation)
         # 工作描述
         job_desc=response.xpath('//dd[@class="job_bt"]/div//p/text()').extract()
         item["job_desc"]=",".join(job_desc).replace("\xa0","").strip()
         #job_publisher
         item["job_publisher"]=response.xpath('//div[@class="publisher_name"]//span[@class="name"]/text()').extract()[0]
         # 公司logo地址
         logo_image=response.xpath('//dl[@class="job_company"]//a/img/@src').extract()[0]
         item["logo_image"]=logo_image.replace("//","")
         # 领域
         field=response.xpath('//ul[@class="c_feature"]//li[1]/text()').extract()
         item["field"]="".join(field).strip()
         # 发展阶段
         stage=response.xpath('//ul[@class="c_feature"]//li[2]/text()').extract()
         item["stage"]="".join(stage).strip()
         # 投资机构
         financeOrg=response.xpath('//ul[@class="c_feature"]//li[3]/p/text()').extract()
         if financeOrg:
             item["financeOrg"]="".join(financeOrg)
         else:
             item["financeOrg"]=""
         #公司规模
         if financeOrg:
              company_size= response.xpath('//ul[@class="c_feature"]//li[4]/text()').extract()
              item["company_size"]="".join(company_size).strip()
         else:
             company_size = response.xpath('//ul[@class="c_feature"]//li[3]/text()').extract()
             item["company_size"] = "".join(company_size).strip()
         # 公司主页
         item["home"]=response.xpath('//ul[@class="c_feature"]//li/a/@href').extract()[0]
         # 爬取时间
         item["crawl_time"]=datetime.now()

         yield item

pipelines.py

 # -*- coding: utf-8 -*-

 # Define your item pipelines here
 #
 # Don't forget to add your pipeline to the ITEM_PIPELINES setting
 # See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html

 import pymysql
 class LagouPipeline(object):

     def process_item(self, item, spider):
         con = pymysql.connect(host="127.0.0.1", user="root", passwd="", db="lagou",charset="utf8")
         cur = con.cursor()
         sql = ("insert into lagouwang(obj_id,company_name,positon_name,salary,work_place,work_experience,education,full_time,tags,publish_time,job_temptation,job_desc,job_publisher,logo_image,field,stage,financeOrg,company_size,home,crawl_time)"
                "VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)")
         lis=(item["obj_id"],item["company_name"],item["positon_name"],item["salary"],item["work_place"],item["work_experience"],item["education"],item['full_time'],item["tags"],item["publish_time"],item["job_temptation"],item["job_desc"],item["job_publisher"],item["logo_image"],item["field"],item["stage"],item["financeOrg"],item["company_size"],item["home"],item["crawl_time"])
         cur.execute(sql, lis)
         con.commit()
         cur.close()
         con.close()

         return item

middlewares.py

 from scrapy import signals
 import random
 #from LaGou.settings import USER_AGENTS
 from fake_useragent import UserAgent

 class RandomUserAgent(object):
     # def __init__(self,crawl):
     #     super(RandomUserAgent,self).__init__()
     #     self.ua=UserAgent()
     def process_request(self, request, spider):
         #useragent = random.choice(USER_AGENTS)
         ua=UserAgent()
         request.headers.setdefault("User-Agent",ua.random)

settings.py

 # -*- coding: utf-8 -*-

 # Scrapy settings for LaGou project
 #
 # For simplicity, this file contains only settings considered important or
 # commonly used. You can find more settings consulting the documentation:
 #
 #     http://doc.scrapy.org/en/latest/topics/settings.html
 #     http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
 #     http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html

 BOT_NAME = 'LaGou'

 SPIDER_MODULES = ['LaGou.spiders']
 NEWSPIDER_MODULE = 'LaGou.spiders'

 # Crawl responsibly by identifying yourself (and your website) on the user-agent
 #USER_AGENT = 'LaGou (+http://www.yourdomain.com)'

 # Obey robots.txt rules
 ROBOTSTXT_OBEY = False

 # Configure maximum concurrent requests performed by Scrapy (default: 16)
 #CONCURRENT_REQUESTS = 32

 # Configure a delay for requests for the same website (default: 0)
 # See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay
 # See also autothrottle settings and docs
 DOWNLOAD_DELAY = 5
 # The download delay setting will honor only one of:
 #CONCURRENT_REQUESTS_PER_DOMAIN = 16
 #CONCURRENT_REQUESTS_PER_IP = 16

 # Disable cookies (enabled by default)
 COOKIES_ENABLED = False
 # USER_AGENTS = [
 #     "Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Win64; x64; Trident/5.0; .NET CLR 3.5.30729; .NET CLR 3.0.30729; .NET CLR 2.0.50727; Media Center PC 6.0)",
 #     "Mozilla/5.0 (compatible; MSIE 8.0; Windows NT 6.0; Trident/4.0; WOW64; Trident/4.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; .NET CLR 1.0.3705; .NET CLR 1.1.4322)",
 #     "Mozilla/4.0 (compatible; MSIE 7.0b; Windows NT 5.2; .NET CLR 1.1.4322; .NET CLR 2.0.50727; InfoPath.2; .NET CLR 3.0.04506.30)",
 #     "Mozilla/5.0 (Windows; U; Windows NT 5.1; zh-CN) AppleWebKit/523.15 (KHTML, like Gecko, Safari/419.3) Arora/0.3 (Change: 287 c9dfb30)",
 #     "Mozilla/5.0 (X11; U; Linux; en-US) AppleWebKit/527+ (KHTML, like Gecko, Safari/419.3) Arora/0.6",
 #     "Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.8.1.2pre) Gecko/20070215 K-Ninja/2.1.1",
 #     "Mozilla/5.0 (Windows; U; Windows NT 5.1; zh-CN; rv:1.9) Gecko/20080705 Firefox/3.0 Kapiko/3.0",
 #     "Mozilla/5.0 (X11; Linux i686; U;) Gecko/20070322 Kazehakase/0.4.5"
 #    ]
 # Disable Telnet Console (enabled by default)
 #TELNETCONSOLE_ENABLED = False

 # Override the default request headers:
 #DEFAULT_REQUEST_HEADERS = {
 #   'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
 #   'Accept-Language': 'en',
 #}
 DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"
 SCHEDULER = "scrapy_redis.scheduler.Scheduler"
 SCHEDULER_PERSIST = True
 # Enable or disable spider middlewares
 # See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
 #SPIDER_MIDDLEWARES = {
 #    'LaGou.middlewares.LagouSpiderMiddleware': 543,

 #}

 # Enable or disable downloader middlewares
 # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
 DOWNLOADER_MIDDLEWARES = {
       'LaGou.middlewares.RandomUserAgent': 1,
 #    'LaGou.middlewares.MyCustomDownloaderMiddleware': 543,
 }

 # Enable or disable extensions
 # See http://scrapy.readthedocs.org/en/latest/topics/extensions.html
 #EXTENSIONS = {
 #    'scrapy.extensions.telnet.TelnetConsole': None,
 #}

 # Configure item pipelines
 # See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
 ITEM_PIPELINES = {
       'scrapy_redis.pipelines.RedisPipeline':300,

     #'LaGou.pipelines.LagouPipeline': 300,
 }

 # Enable and configure the AutoThrottle extension (disabled by default)
 # See http://doc.scrapy.org/en/latest/topics/autothrottle.html
 #AUTOTHROTTLE_ENABLED = True
 # The initial download delay
 #AUTOTHROTTLE_START_DELAY = 5
 # The maximum download delay to be set in case of high latencies
 #AUTOTHROTTLE_MAX_DELAY = 60
 # The average number of requests Scrapy should be sending in parallel to
 # each remote server
 #AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
 # Enable showing throttling stats for every response received:
 #AUTOTHROTTLE_DEBUG = False

 # Enable and configure HTTP caching (disabled by default)
 # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
 #HTTPCACHE_ENABLED = True
 #HTTPCACHE_EXPIRATION_SECS = 0
 #HTTPCACHE_DIR = 'httpcache'
 #HTTPCACHE_IGNORE_HTTP_CODES = []
 #HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'

redis数据：

mysql数据：

申明：以上只限于参考学习交流！！！更多：https://github.com/huwei86/spiderlagou