文章目錄

• 一. 案例介紹
• 二.創(chuàng)建項目
• 三. settings.py配置
• 四. 詳細(xì)代碼
• 五. 部署
• • 1. windows環(huán)境下生成requirements.txt文件
  • 2. xshell連接ubuntu服務(wù)器并安裝依賴環(huán)境
  • 3. 修改部分代碼
  • 4. 上傳代碼至服務(wù)器并運(yùn)行

一. 案例介紹

爬取房天下（https://www1.fang.com/）的網(wǎng)頁信息。

源代碼已更新至：Github

二.創(chuàng)建項目

打開windows終端，切換至項目將要存放的目錄下：

scrapy startproject fang

cd fang\

scrapy genspider sfw “fang.com”

項目目錄結(jié)構(gòu)如下所示：

三. settings.py配置

# Obey robots.txt rules ROBOTSTXT_OBEY = False DOWNLOAD_DELAY = 3 DEFAULT_REQUEST_HEADERS = {'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8','Accept-Language': 'en', } DOWNLOADER_MIDDLEWARES = {'fang.middlewares.UserAgentDownloadMiddleware': 543, } ITEM_PIPELINES = {'fang.pipelines.FangPipeline': 300, }

四. 詳細(xì)代碼

settings.py:

# -*- coding: utf-8 -*-# Scrapy settings for fang project # # For simplicity, this file contains only settings considered important or # commonly used. You can find more settings consulting the documentation: # # https://docs.scrapy.org/en/latest/topics/settings.html # https://docs.scrapy.org/en/latest/topics/downloader-middleware.html # https://docs.scrapy.org/en/latest/topics/spider-middleware.htmlBOT_NAME = 'fang'SPIDER_MODULES = ['fang.spiders'] NEWSPIDER_MODULE = 'fang.spiders'# Crawl responsibly by identifying yourself (and your website) on the user-agent #USER_AGENT = 'fang (+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 https://docs.scrapy.org/en/latest/topics/settings.html#download-delay # See also autothrottle settings and docs DOWNLOAD_DELAY = 3 # 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# 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', }# Enable or disable spider middlewares # See https://docs.scrapy.org/en/latest/topics/spider-middleware.html #SPIDER_MIDDLEWARES = { # 'fang.middlewares.FangSpiderMiddleware': 543, #}# Enable or disable downloader middlewares # See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html DOWNLOADER_MIDDLEWARES = {'fang.middlewares.UserAgentDownloadMiddleware': 543, }# Enable or disable extensions # See https://docs.scrapy.org/en/latest/topics/extensions.html #EXTENSIONS = { # 'scrapy.extensions.telnet.TelnetConsole': None, #}# Configure item pipelines # See https://docs.scrapy.org/en/latest/topics/item-pipeline.html ITEM_PIPELINES = {'fang.pipelines.FangPipeline': 300, }# Enable and configure the AutoThrottle extension (disabled by default) # See https://docs.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 https://docs.scrapy.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'

items.py:

# -*- coding: utf-8 -*-# Define here the models for your scraped items # # See documentation in: # https://docs.scrapy.org/en/latest/topics/items.htmlimport scrapyclass NewHouseItem(scrapy.Item):# 省份province = scrapy.Field()# 城市city = scrapy.Field()# 小區(qū)名字name = scrapy.Field()# 價格price = scrapy.Field()# 幾居 列表rooms = scrapy.Field()# 面積area = scrapy.Field()# 地址address = scrapy.Field()# 行政區(qū)district = scrapy.Field()# 是否在售sale = scrapy.Field()# 房天下詳情頁面的urlorigin_url = scrapy.Field()class ESFHouseItem(scrapy.Item):# 省份province = scrapy.Field()# 城市city = scrapy.Field()# 小區(qū)名字name = scrapy.Field()# 幾室?guī)讖drooms = scrapy.Field()# 層floor = scrapy.Field()# 朝向toward = scrapy.Field()# 年代year = scrapy.Field()# 地址address = scrapy.Field()# 建筑面積area = scrapy.Field()# 總價price = scrapy.Field()# 單價unit = scrapy.Field()# 原始urlorigin_url = scrapy.Field()

pipelines.py:

# -*- coding: utf-8 -*-# Define your item pipelines here # # Don't forget to add your pipeline to the ITEM_PIPELINES setting # See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html from scrapy.exporters import JsonLinesItemExporterclass FangPipeline(object):def __init__(self):self.newhouse_fp = open('newhouse.json','wb')self.esfhouse_fp = open('esfhouse.json','wb')self.newhouse_exporter = JsonLinesItemExporter(self.newhouse_fp,ensure_ascii=False)self.esfhouse_exporter = JsonLinesItemExporter(self.esfhouse_fp, ensure_ascii=False)def process_item(self, item, spider):self.newhouse_exporter.export_item(item)self.esfhouse_exporter.export_item(item)return itemdef close_spider(self,spider):self.newhouse_fp.close()self.esfhouse_fp.close()

sfw.py:

# -*- coding: utf-8 -*- import reimport scrapy from fang.items import NewHouseItem, ESFHouseItemclass SfwSpider(scrapy.Spider):name = 'sfw'allowed_domains = ['fang.com']start_urls = ['https://www.fang.com/SoufunFamily.htm']def parse(self, response):trs = response.xpath("//div[@class='outCont']//tr")province = Nonefor tr in trs:tds = tr.xpath(".//td[not(@class)]")province_td = tds[0]province_text = province_td.xpath(".//text()").get()province_text = re.sub(r"\s","",province_text)if province_text:province = province_textif province == "其它":continuecity_id = tds[1]city_links = city_id.xpath(".//a")for city_link in city_links:city = city_link.xpath(".//text()").get()city_url = city_link.xpath(".//@href").get()# print("省份：",province)# print("城市：", city)# print("城市鏈接：", city_url)#構(gòu)建新房的url鏈接url_module = city_url.split("//")scheme = url_module[0]domain_all = url_module[1].split("fang")domain_0 = domain_all[0]domain_1 = domain_all[1]if "bj." in domain_0:newhouse_url = "https://newhouse.fang.com/house/s/"esf_url = "https://esf.fang.com/"else:newhouse_url =scheme + "//" + domain_0 + "newhouse.fang" + domain_1 + "house/s/"# 構(gòu)建二手房的URL鏈接esf_url = scheme + "//" + domain_0 + "esf.fang" + domain_1# print("城市：%s%s"%(province, city))# print("新房鏈接：%s"%newhouse_url)# print("二手房鏈接：%s"%esf_url)# yield scrapy.Request(url=newhouse_url,callback=self.parse_newhouse,meta={"info":(province, city)})yield scrapy.Request(url=esf_url,callback=self.parse_esf,meta={"info":(province, city)},dont_filter=True)# break# breakdef parse_newhouse(self,response):province,city = response.meta.get('info')lis = response.xpath("//div[contains(@class,'nl_con')]/ul/li")for li in lis:# 獲取 項目名字name = li.xpath(".//div[@class='nlcd_name']/a/text()").get()name = li.xpath(".//div[@class='nlcd_name']/a/text()").get()if name == None:passelse:name = name.strip()# print(name)# 獲取房子類型：幾居house_type_list = li.xpath(".//div[contains(@class,'house_type')]/a/text()").getall()if len(house_type_list) == 0:passelse:house_type_list = list(map(lambda x:re.sub(r"\s","",x),house_type_list))rooms = list(filter(lambda x:x.endswith("居"),house_type_list))# print(rooms)# 獲取房屋面積area = "".join(li.xpath(".//div[contains(@class,'house_type')]/text()").getall())area = re.sub(r"\s|/|－", "", area)if len(area) == 0:passelse:area =area# print(area)# 獲取地址address = li.xpath(".//div[@class='address']/a/@title").get()if address == None:passelse:address = address# print(address)# 獲取區(qū)劃分：海淀 朝陽district_text = "".join(li.xpath(".//div[@class='address']/a//text()").getall())if len(district_text) == 0:passelse:district = re.search(r".*\[(.+)\].*",district_text).group(1)# print(district)# 獲取是否在售sale = li.xpath(".//div[contains(@class,'fangyuan')]/span/text()").get()if sale == None:passelse:sale = sale# print(sale)# 獲取價格price = li.xpath(".//div[@class='nhouse_price']//text()").getall()if len(price) == 0:passelse:price = "".join(price)price = re.sub(r"\s|廣告","",price)# print(price)# 獲取網(wǎng)址鏈接origin_url = li.xpath(".//div[@class='nlcd_name']/a/@href").get()if origin_url ==None:passelse:origin_url = origin_url# print(origin_url)item = NewHouseItem(name=name,rooms=rooms,area=area,address=address,district=district,sale=sale,price=price,origin_url=origin_url,province=province,city=city,)yield itemnext_url = response.xpath(".//div[@class='page']//a[@class='next']/@href").get()if next_url:yield scrapy.Request(url=response.urljoin(next_url), callback=self.parse_newhouse,meta={"info":(province,city)})def parse_esf(self, response):# 獲取省份和城市province, city = response.meta.get('info')dls = response.xpath("//div[@class='shop_list shop_list_4']/dl")for dl in dls:item = ESFHouseItem(province=province,city=city)# 獲取小區(qū)名字name = dl.xpath(".//p[@class='add_shop']/a/text()").get()if name == None:passelse:item['name'] = name.strip()# print(name)# 獲取綜合信息infos = dl.xpath(".//p[@class='tel_shop']/text()").getall()if len(infos) == 0:passelse:infos = list(map(lambda x:re.sub(r"\s","",x),infos))# print(infos)for info in infos:if "廳" in info :item['rooms']= infoelif '層' in info:item['floor']= infoelif '向' in info:item['toward']=infoelif '年' in info:item['year']=infoelif '㎡' in info:item['area'] = info# print(item)# 獲取地址address = dl.xpath(".//p[@class='add_shop']/span/text()").get()if address == None:passelse:# print(address)item['address'] = address# 獲取總價price = dl.xpath("./dd[@class='price_right']/span[1]/b/text()").getall()if len(price) == 0:passelse:price="".join(price)# print(price)item['price'] = price# 獲取單價unit = dl.xpath("./dd[@class='price_right']/span[2]/text()").get()if unit == None:passelse:# print(unit)item['unit'] = unit# 獲取初始urldetail_url = dl.xpath(".//h4[@class='clearfix']/a/@href").get()if detail_url == None:passelse:origin_url = response.urljoin(detail_url)# print(origin_url)item['origin_url'] = origin_url# print(item)yield itemnext_url = response.xpath(".//div[@class='page_al']/p/a/@href").get()# print(next_url)yield scrapy.Request(url=response.urljoin(next_url),callback=self.parse_esf,meta={"info":(province,city)})

middlewares.py:

# -*- coding: utf-8 -*-# Define here the models for your spider middleware # # See documentation in: # https://docs.scrapy.org/en/latest/topics/spider-middleware.htmlimport randomclass UserAgentDownloadMiddleware(object):# user-agent隨機(jī)請求頭中間件USER_AGENTS = ['Mozilla/5.0 (Windows; U; Windows NT 6.1; rv:2.2) Gecko/20110201''Mozilla/5.0 (Windows; U; Windows NT 5.1; pl; rv:1.9.2.3) Gecko/20100401 Lightningquail/3.6.3''Mozilla/5.0 (X11; ; Linux i686; rv:1.9.2.20) Gecko/20110805''Mozilla/5.0 (Windows; U; Windows NT 6.0; en-US; rv:1.9.1b3) Gecko/20090305''Mozilla/5.0 (X11; U; Linux i686; en-US; rv:1.9.0.14) Gecko/2009091010''Mozilla/5.0 (X11; U; Linux i686; en-US; rv:1.9.0.10) Gecko/2009042523']def process_request(self, request, spider):user_agent = random.choice(self.USER_AGENTS)request.headers['User-Agent'] = user_agent

start.sh:

from scrapy import cmdlinecmdline.execute("scrapy crawl sfw".split())

此時在windows開發(fā)環(huán)境下運(yùn)行start.sh，即可正常爬取數(shù)據(jù)。

五. 部署

1. windows環(huán)境下生成requirements.txt文件

打開cmder，首先切換至虛擬化境：

cd C:\Users\fxd.virtualenvs\sipder_env
.\Scripts\activate

然后切換至項目所在目錄，輸入指令，生成requirements.txt文件
pip freeze > requirements.txt

2. xshell連接ubuntu服務(wù)器并安裝依賴環(huán)境

如果未安裝openssh，需要首先安裝，具體指令如下：

sudo apt-get install openssh-server

連接ubuntu服務(wù)器，切換至虛擬環(huán)境所在的目錄，執(zhí)行：

source ./bin/activate

進(jìn)入虛擬環(huán)境，執(zhí)行：

rz

上傳requirements.txt，執(zhí)行：

pip install -r requirements.txt

安裝項目依賴環(huán)境。

然后安裝scrapy-redis：

pip install scrapy-redis

3. 修改部分代碼

要將一個Scrapy項目變成一個Scrapy-redis項目，只需要修改以下三點(diǎn)：
（1）將爬蟲繼承的類，從scrapy.Spider 變成scrapy_redis.spiders.RedisSpider；或者從scrapy.CrowlSpider變成scrapy_redis.spiders.RedisCrowlSpider。
（2）將爬蟲中的start_urls刪掉，增加一個redis_key="***"。這個key是為了以后在redis中控制爬蟲啟動的，爬蟲的第一個url，就是在redis中通過這個推送出去的。
（3）在配置文件中增加如下配置：

# Scrapy-Redis相關(guān)配置 # 確保request存儲到redis中 SCHEDULER = "scrapy_redis.scheduler.Scheduler"# 確保所有的爬蟲共享相同的去重指紋 DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"# 設(shè)置redis為item_pipeline ITEM_PIPELINES = {'scrapy_redis.pipelines.RedisPipeline':300 }# 在redis中保持scrapy_redis用到的隊列，不會清理redis中的隊列，從而可以實現(xiàn)暫停和回復(fù)的功能 SCHEDULER_PERSIST = True# 設(shè)置連接redis信息 REDIS_HOST = '172.20.10.2' REDIS_PORT = 6379

4. 上傳代碼至服務(wù)器并運(yùn)行

將項目文件壓縮，在xshell中通過命令rz上傳，并解壓

運(yùn)行爬蟲：
（1）在爬蟲服務(wù)器上，進(jìn)入爬蟲文件sfw.py所在的路徑，然后輸入命令：scrapy runspider [爬蟲名字]

scrapy runspider sfw.py

（2）在redis（windows）服務(wù)器上，開啟redis服務(wù)：

redis-server redis.windows.conf
若報錯，按步驟執(zhí)行以下命令：
redis-cli.exe
shutdown
exit
redis-server.exe redis.windows.conf

（3）然后打開另外一個windows終端：

redis-cli

推入一個開始的url鏈接：

lpush fang:start_urls https://www.fang.com/SoufunFamily.htm

爬蟲開始

進(jìn)入RedisDesktopManager查看保存的數(shù)據(jù)：

另外一臺爬蟲服務(wù)器進(jìn)行同樣的操作。
項目結(jié)束！

總結(jié)

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