1、创建Scrapy项目
- scrapy startproject PosProductRedis
2.进入项目目录,使用命令genspider创建Spider
- scrapy genspider posproductredis XXXX.com
3、定义要抓取的数据(处理items.py文件)
- # -*- coding: utf-8 -*-
- import scrapy
-
- class PosproductredisItem(scrapy.Item):
- # 获取序号
- number_list = scrapy.Field()
- # 获取ID
- id_list = scrapy.Field()
- # 获取商家名称
- qiye_list = scrapy.Field()
- # 获取分类
- product_list = scrapy.Field()
- # 获取产品名称
- product_name_list = scrapy.Field()
- # 获取销售情况
- sale_list = scrapy.Field()
- # 销售标题(有空格)
- sales_title = scrapy.Field()
- # 获取销售区域
- sales_area = scrapy.Field()
- # 获取规格
- product_size = scrapy.Field()
- # 获取起订量
- product_quantity = scrapy.Field()
- # 获取零售价
- retail_price = scrapy.Field()
- # 获取零售促销价
- promotion_price = scrapy.Field()
- # 获取skuid,可以不写
- # skuid = scrapy.Field()
-
4、编写提取item数据的Spider(在spiders文件夹下:posproductredis.py)
- # -*- coding: utf-8 -*-
- # 利用scrapy_redis将pos后台数据包含价格、规格、起订量、销售区域等信息全部保存到excel中
- import scrapy
- from PosProductRedis.items import PosproductredisItem
- from scrapy_redis.spiders import RedisSpider
- import re
-
- class PosproductredisSpider(RedisSpider):
- name = 'posproductredis'
- allowed_domains = ['XXXX.com']
- redis_key = "PosproductredisSpider:start_urls"
- # lpush PosproductredisSpider:start_urls https://pos.XXX.com/item/itemonlist.html?d-49489-p=1
-
- login_page = "https://pos.XXXX.com/login.html"
-
- def start_requests(self):
- yield scrapy.Request(url=self.login_page,callback=self.login)
-
- def login(self, response):
- self.username = input("请输入账号:")
- self.password = input("请输入密码:")
- yield scrapy.FormRequest.from_response(
- response,
- formdata={"j_username":self.username, "j_password":self.password},
- callback = self.parse_page
- )
- # 获取登录成功的状态,访问需要登录后才能访问的页面
- def parse_page(self, response):
- if "loginerror" in response.body.decode('utf-8'):
- print("登录失败,错误的手机号或密码!")
- if "</span>首页" in response.body.decode('utf-8'):
- print("欢迎您'%s',成功登录POS管理系统!" % (self.username))
- print("请在slaver端(爬虫程序执行端)输入:lpush %s 爬取列表页网址"%(self.redis_key))
- # 登录成功后获取在线产品的列表页,并回调parse()函数处理数据
- # yield scrapy.Request(response.url, callback=self.parse)
- def parse(self, response):
- # print("数据处理中......")
- items =[]
- # 获取下一页的链接地址,列表,需要和“https://pos.XXXX.com/item/itemonlist.html”进行拼接
- next_url_list = response.xpath('//body//div//div/span/span[@class="paginate_button"]/a/@href').extract()
- for each in response.xpath('//div[@class="dataTables_wrapper"]'):
- # 序号
- number_list = each.xpath('.//td[1]/text()').extract()
- # 获取ID
- id_list = each.xpath('.//tbody//tr//td//input[@onclick="homeShow(this)"]/@value').extract()
- # 获取商家名称
- qiye_list = each.xpath('.//td[2]/text()').extract()
- # 获取分类
- product_list = each.xpath('.//td[4]/text()').extract()
- # 获取产品名称
- product_name_list = each.xpath('.//td[3]/a/text()').extract()
- for i in range(len(id_list)):
- item = PosproductredisItem()
- item['number_list'] = number_list[i].strip()
- item['id_list'] = id_list[i]
- item['qiye_list'] = qiye_list[i].strip()
- item['product_list'] = product_list[i].strip()
- item['product_name_list'] = product_name_list[i].strip()
- # yield item
- items.append(item)
- for item in items:
- id_url = "https://pos.XXXX.com/item/showitem.html?item.id="+ item['id_list']
- yield scrapy.Request(url=id_url,meta={'meta_1':item},callback=self.parse_id)
- pattern = re.compile(r"/?d-49489-p=(\d+)")
- for url in next_url_list:
- i =pattern.search(url).group(1)
- print("第%s页数据处理中...."%i)
- fullurl = 'https://pos.XXXX.com/item/itemonlist.html'+ str(url)
- yield scrapy.Request(url=fullurl,callback=self.parse)
- # 处理id链接,获取价格、规格、起订量等信息
- def parse_id(self,response):
- # 提取每次response的meta数据
- meta_1 = response.meta['meta_1']
- # print("meta_1",meta_1)
- item = PosproductredisItem()
- # 获取销售标题
- sales_title = response.xpath('//div[@id="tabs-1"]/p[8]/span[@class="field"]/text()').extract()
- # 获取销售情况(有空格)
- sale_list = response.xpath('//div[@id="tabs-1"]/p[6]/span/text()').extract()
- # 获取销售区域
- sales_area = response.xpath('//div[@id="tabs-6"]/table/tbody[@id="review_list"]/tr/td[2]/text()').extract()
- # 获取规格
- product_size = response.xpath('//div[@id="tabs"]/div[@id="tabs-5"]/table/tbody/tr/td[1]/text()').extract()
- # 获取起订量
- product_quantity = response.xpath('//div[@id="tabs"]/div[@id="tabs-5"]/table/tbody/tr/td[8]/text()').extract()
- # 获取规格对应的skuid号码》》》javascript:show('688')
- skuid_list = response.xpath('//div[@id="tabs"]/div[@id="tabs-5"]/table/tbody/tr/td[9]/a/@href').extract()
- # 对skuid_list结果进行正则匹配出数字
- pattent = re.compile("\d+")
- # items = []
- # 有规格必然有起订量,这两个是一一对应,并且是必填项不可能为空,只要是在线的产品都会有规格和起订量
- for i in range(len(product_size)):
- # items = []
- item['product_size'] = product_size[i]
- item['product_quantity'] = product_quantity[i]
- # 如果是多个销售区域,那么用分号隔开
- if len(sales_area)>1:
- item['sales_area'] = ";".join(sales_area)
- elif len(sales_area) == 1:
- area_list ="北京市,天津市,河北省,山西省,内蒙古,辽宁省,吉林省,黑龙江省,上海市,江苏省,浙江省,安徽省,福建省,江西省,山东省,河南省,湖北省,湖南省,广东省,广西,海南省,重庆市,四川省,贵州省,云南省,西藏,陕西省,甘肃省,青海省,宁夏,新疆"
- area_list2 = "北京市,天津市,河北省,山西省,内蒙古,辽宁省,吉林省,黑龙江省,上海市,江苏省,浙江省,安徽省,福建省,江西省,山东省,河南省,湖北省,湖南省,广东省,广西,海南省,重庆市,四川省,贵州省,云南省,西藏,陕西省,甘肃省,青海省,宁夏,新疆省"
- full_area_list = "北京市,天津市,河北省,山西省,内蒙古,辽宁省,吉林省,黑龙江省,上海市,江苏省,浙江省,安徽省,福建省,江西省,山东省,河南省,湖北省,湖南省,广东省,广西,海南省,重庆市,四川省,贵州省,云南省,西藏,陕西省,甘肃省,青海省,宁夏,新疆,台湾省,香港,澳门"
- if sales_area[0] == area_list or sales_area[0] == area_list2:
- item['sales_area'] = "全国(不含港澳台)"
- elif sales_area[0] == full_area_list:
- item['sales_area'] = "全国"
- else:
- item['sales_area'] = sales_area[0]
- else:
- item['sales_area'] = "无区域"
-
- item['sales_title'] = sales_title[0].strip()
- item['sale_list'] = sale_list[0].strip()
- item['number_list'] = meta_1['number_list']
- item['id_list'] = meta_1['id_list']
- item['qiye_list'] = meta_1['qiye_list']
- item['product_list'] = meta_1['product_list']
- item['product_name_list'] = meta_1['product_name_list']
- # items.append(item)
- # 提取javascript:show('688')里面skuid号码
- skuid_number = pattent.search(skuid_list[i]).group()
- # 可以把skuid保存下来,这里无用就不保存了
- # item['skuid'] = skuid_number
- skuid_url = "https://pos.XXXX.com/item/showitemprice.html?sku.id="+ skuid_number
- yield scrapy.Request(url=skuid_url,meta={'meta_2':item},callback=self.parse_skuid)
-
- def parse_skuid(self,response):
- # 提取每次response的meta数据
- meta_2 = response.meta['meta_2']
- item = PosproductredisItem()
- # 零售价,将重复的价格筛选掉,用set去掉重复项,并转换为列表
- retail_price_list = response.xpath('//div[@id="tabs-1"]/table[@id="item"]/tbody/tr/td[2]/text()').extract()
- retail_price = list(set(retail_price_list))
- for i in range(len(retail_price)):
- if retail_price[i] == "0.0":
- retail_price[i] = '零售价待定'
- elif retail_price[i] == "0.00":
- retail_price[i] = '零售价数据0.00有误'
- # 如果是多个价格,用分号隔开
- if len(retail_price)>1:
- item['retail_price'] = ";".join(retail_price)
- elif len(retail_price) ==1:
- item['retail_price'] = retail_price[0]
-
- # 获取零售促销价,将重复的促销价筛选掉,用set去掉重复项,并转换为列表
- promotion_price_list = response.xpath('//div[@id="tabs-1"]/table[@id="item"]/tbody/tr/td[3]/text()').extract()
- promotion_price = list(set(promotion_price_list))
- for i in range(len(promotion_price)):
- if promotion_price[i] == "0.0":
- promotion_price[i] = '无促销价'
- elif promotion_price[i] == "0.00":
- promotion_price[i] = '促销价数据0.00有误'
- # 如果是多个促销价格,用分号隔开
- if len(promotion_price)>1:
- item['promotion_price'] = ";".join(promotion_price)
- elif len(promotion_price) ==1:
- item['promotion_price'] = promotion_price[0]
-
- item['number_list'] = meta_2['number_list']
- # item['skuid'] = meta_2['skuid']
- item['id_list'] = meta_2['id_list']
- item['qiye_list'] = meta_2['qiye_list']
- item['product_list'] = meta_2['product_list']
- item['product_name_list'] = meta_2['product_name_list']
- item['sales_title'] = meta_2['sales_title']
- item['sale_list'] = meta_2['sale_list']
- item['product_size'] = meta_2['product_size']
- item['product_quantity'] = meta_2['product_quantity']
- item['sales_area'] = meta_2['sales_area']
- yield item
-
5.处理pipelines管道文件保存数据,可将结果保存到文件中(pipelines.py)
- # -*- coding: utf-8 -*-
- import json
- from openpyxl import Workbook
- import time
-
- # 转码操作
- class MyEncoder(json.JSONEncoder):
- def default(self, o):
- if isinstance(o, bytes):
- return str(o, encoding='utf-8')
- return json.JSONEncoder.default(self, o)
-
- class PosproductredisPipeline(object):
- def __init__(self):
- self.wb = Workbook()
- self.ws = self.wb.active
- # 创建表头
- self.ws.append(['序号', 'ID', '商家名称', '产品分类',
- '产品名称', '销售标题','销售情况', '零售价',
- '促销价', '规格', '起订量', '销售区域'
- ])
-
- def process_item(self, item, spider):
- text = [item['number_list'], item['id_list'], item['qiye_list'], item['product_list'],
- item['product_name_list'], item['sales_title'], item['sale_list'], item['retail_price'],
- item['promotion_price'], item['product_size'], item['product_quantity'], item['sales_area']]
- self.ws.append(text)
- return item
-
- def close_spider(self, spider):
- # 给保存的文件名字加上个当天的日期年月日
- file_end_name = time.strftime("%Y-%m-%d", time.localtime())
- self.wb.save("pos_product_redis"+file_end_name+'.xlsx')
- print("数据处理完成,谢谢使用!")
6.配置settings文件(settings.py)
- # 使用scrapy-redis里的去重组件,不再使用scrapy默认的去重
- DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"
- # 使用了scrapy-redis里的调度器组件,不再使用scrapy默认的调度器
- SCHEDULER = "scrapy_redis.scheduler.Scheduler"
- # 允许暂停,redis请求记录不丢失
- SCHEDULER_PERSIST = True
-
- # 不写默认存储到本地数据库
- # REDIS_HOST = "192.168.0.109"
- # REDIS_PORT = 6379
-
- # 默认的scrapy-redis请求队列形式
- SCHEDULER_QUEUE_CLASS = "scrapy_redis.queue.SpiderPriorityQueue"
- # 队列形式,先进先出,选这个会报错:Unhandled error in Deferred
- # SCHEDULER_QUEUE_CLASS = "scrapy_redis.queue.SpiderQueue"
- # 栈形式,先进后出
- #SCHEDULER_QUEUE_CLASS = "scrapy_redis.queue.SpiderStack"
-
- # Configure item pipelines去掉下面注释,打开管道文件,添加RedisPipeline
- ITEM_PIPELINES = {
- 'PosProductRedis.pipelines.PosproductredisPipeline': 300,
- 'scrapy_redis.pipelines.RedisPipeline': 400,
- }
-
-
- # Obey robots.txt rules,具体含义参照:https://www.cdsy.xyz/computer/programme/Python/241210/cd64912.html
- ROBOTSTXT_OBEY = False
-
- # Override the default request headers:添加User-Agent信息
- DEFAULT_REQUEST_HEADERS = {
- 'User-Agent': 'Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0);',
- # 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
- # 'Accept-Language': 'en',
- }
-
- # 还可以将日志存到本地文件中(可选添加设置)
- LOG_FILE = "posproductredis.log"
- LOG_LEVEL = "DEBUG"
- # 包含print全部放在日志中
- LOG_STDOUT = True
7.参照以下链接打开redis数据库:
- https://www.cdsy.xyz/computer/soft/database/redis/230308/cd41219.html
8.以上设置完毕,进行爬取:进入到spiders文件夹下执行项目命令,启动Spider:
- scrapy runspider posproductredis.py
9.在Master端(核心服务器)的redis-cli输入push指令,参考格式:
- 输入:lpush PosproductredisSpider:start_urls https://pos.XXXX.com/item/itemonlist.html?d-49489-p=1