init

公共代码/public.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Mar 23 23:36:40 2021
+
+@author: rico
+"""
+import requests
+
+
+
+def zgc_api(func,data):
+    
+    headers = {
+    'Connection': 'Keep-Alive'
+    }
+    
+    key = 'eRo1#ZFHY5N&GEzV'
+    
+    api = f"http://59.110.219.171:8000/{func}/"
+    print(api)
+    
+    data.update({'key':key})
+    session = requests.session()
+    result = session.post(api,json=data,headers=headers,timeout=6000).json()
+    
+    
+    return result
+
+
+#进度条
+class Index(object):
+    def __init__(self, number=50, decimal=2):
+        """
+        :param decimal: 你保留的保留小数位
+        :param number: # 号的 个数
+        """
+        self.decimal = decimal
+        self.number = number
+        self.a = 100/number   # 在百分比 为几时增加一个 # 号
+ 
+    def __call__(self, now, total):
+        # 1. 获取当前的百分比数
+        percentage = self.percentage_number(now, total)
+ 
+        # 2. 根据 现在百分比计算
+        well_num = int(percentage / self.a)
+        # print("well_num: ", well_num, percentage)
+ 
+        # 3. 打印字符进度条
+        progress_bar_num = self.progress_bar(well_num)
+ 
+        # 4. 完成的进度条
+        result = "\r%s %s" % (progress_bar_num, percentage)
+        return result
+ 
+    def percentage_number(self, now, total):
+        """
+        计算百分比
+        :param now:  现在的数
+        :param total:  总数
+        :return: 百分
+        """
+        return round(now / total * 100, self.decimal)
+ 
+    def progress_bar(self, num):
+        """
+        显示进度条位置
+        :param num:  拼接的  “#” 号的
+        :return: 返回的结果当前的进度条
+        """
+        # 1. "#" 号个数
+        well_num = "#" * num
+ 
+        # 2. 空格的个数
+        space_num = " " * (self.number - num)
+ 
+        return '[%s%s]' % (well_num, space_num)
+    
+
+
+
+

公共代码/upload_finish_code.sh

+
+scp $1 uploadfile@59.110.219.171:/home/zgcAPI/PointCategoryDealFile/
\ No newline at end of file

公共代码/上传补充后的数据字典.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Feb 24 17:21:29 2021
+
+@author: rico
+"""
+
+
+import pandas as pd
+import pymssql
+from public import Index
+
+#上传数据字典补充数据
+def ComplicatedDataDict(path):
+    
+    #创建新产品库链接
+    conn_zi_new = pymssql.connect(host='123.56.115.207', user='zgcprice3311',password='zgcprice20200628',database= 'ZI_NEW',autocommit=True)
+    cursor_zi_new = conn_zi_new.cursor()
+    
+    df = pd.read_excel(path)
+    process_index = 0
+    index = Index()
+    for index,row in df.iterrows():
+        
+        try:
+            print(index(process_index,len(df)-1), end='%')
+        except:
+            print(index(process_index,1), end='%')
+        process_index+=1
+    
+        cursor_zi_new.execute(f"update ShuJuZiDian_Cfg set stdvalue = '{row['stdvalue']}',simplevalue = '{row['simplevalue']}' where id = {row['id']}")
+       
+        
+    conn_zi_new.close()
+    
+    
+path = ''
+ComplicatedDataDict(path)
\ No newline at end of file

公共代码/导出库内参数数据.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Feb 23 00:36:24 2021
+
+@author: rico
+"""
+
+import pandas as pd
+import pymssql
+from public import Index
+
+
+def get_point_category_params_data(category):
+    
+    category_sheet_name = category.replace("/","_")
+    #创建产品库链接
+    conn_zi_new = pymssql.connect(host='123.56.115.207', user='zgcprice3311',password='zgcprice20200628',database= 'ZI_NEW',autocommit=True)
+    cursor = conn_zi_new.cursor()
+    
+    conn_zdindex = pymssql.connect(host='123.56.115.207', user='zgcprice3311',password='zgcprice20200628',database= 'zdindex',autocommit=True)
+    cursor_zdindex = conn_zdindex.cursor()
+    
+    cursor.execute(f"select id,name from p_category where id not in (select distinct pid from p_category) and name in ('{category}')")
+    
+    data = (cursor.fetchall())
+    export_category = pd.DataFrame(data,columns=[tuple[0] for tuple in cursor.description])
+    
+    writer = pd.ExcelWriter(f"{category_sheet_name}参数确认.xlsx")
+    
+    for category_code,category_name in zip(export_category['id'].tolist(),export_category['name'].tolist()):
+        
+        print(f"开始提取{category_name}参数数据")
+
+        #获取产品信息
+        cursor.execute(f"select a.*,h.name as father_brand_name,d.name as brand_name,g.name as attr_name,f.value from p_sku a \
+                       left join p_spu b \
+                       on a.spuid = b.id \
+                       left join p_category c \
+                       on b.categoryid = c.id \
+                       left join p_brand d \
+                       on b.brandid = d.id \
+                       left join p_skuvaluemap e \
+                       on a.id = e.skuid \
+                       left join p_skuvalue f \
+                       on e.valueid = f.id \
+                       left join p_skusubtitle g \
+                       on f.subtitleid = g.id \
+                       left join p_brand h \
+                       on d.pid = h.id \
+                       where b.categoryid = {category_code} and a.state in (1,2,4)")
+        data = (cursor.fetchall())
+        df_sku = pd.DataFrame(data,columns=[tuple[0] for tuple in cursor.description])
+        
+        cursor.execute(f"select a.*,d.name as brand_name,g.name as attr_name,f.value from p_sku a \
+                   left join p_spu b \
+                   on a.spuid = b.id \
+                   left join p_category c \
+                   on b.categoryid = c.id \
+                   left join p_brand d \
+                   on b.brandid = d.id \
+                   left join p_valuemap e \
+                   on b.id = e.spuid \
+                   left join p_value f \
+                   on e.valueid = f.id \
+                   left join p_subtitle g \
+                   on f.subtitleid = g.id \
+                   where b.categoryid = {category_code} and a.state in (1,2,4)")
+        data = (cursor.fetchall())
+        df_spu = pd.DataFrame(data,columns=[tuple[0] for tuple in cursor.description])
+        
+        res = pd.DataFrame()
+        id_list = []
+        state_list = []
+        product_name_list = []
+        father_brand_list = []
+        brand_list = []
+        category_list = []
+        #param_list
+        
+        cursor.execute(f"select * from vw_property where categoryid = {category_code}")
+        data = cursor.fetchall()
+        params_df = pd.DataFrame(data, columns=[tuple[0] for tuple in cursor.description])
+        params_df['needed_param'] = params_df['identy'].apply(lambda x: x[0])
+        params_df['standard_param'] = params_df['identy'].apply(lambda x: x[2])
+        
+        params_df = params_df[params_df['needed_param'] != '0']
+        params_df['subtitle'] = params_df['subtitle'].apply(lambda x: x.strip())
+        
+
+        param_list = params_df['subtitle'].tolist()
+        for param in param_list:
+            param_var = '_' + ''.join(param.split()).replace('（','').replace('）','').replace('/','').replace('(','').replace(')','').replace('+','').replace('-','').replace('*','').replace('.','')
+            exec('%s_list=[]'%param_var)
+    
+                
+        
+        process_index = 0
+        index = Index()
+        
+        for prodcut_id in list(df_sku['sku'].unique()):
+            
+            try:
+                print(index(process_index,len(list(df_sku['sku'].unique()))-1), end='%')
+            except:
+                print(index(process_index,1), end='%')
+            process_index+=1
+            
+            id_list.append(prodcut_id)
+            state_list.append(df_sku[df_sku['sku'] == prodcut_id]['state'].tolist()[0])
+            product_name_list.append(df_sku[df_sku['sku'] == prodcut_id]['skuname'].tolist()[0])
+            
+            father_brand_list.append(df_sku[df_sku['sku'] == prodcut_id]['father_brand_name'].tolist()[0])
+            brand_list.append(df_sku[df_sku['sku'] == prodcut_id]['brand_name'].tolist()[0])
+            
+            category_list.append(category_name)
+            
+            for param in param_list:
+                param_var = '_' + ''.join(param.split()).replace('（','').replace('）','').replace('/','').replace('(','').replace(')','').replace('+','').replace('-','').replace('*','').replace('.','')
+                try:
+                    exec("%s_list.append(df_sku[(df_sku['sku'] == prodcut_id) & (df_sku['attr_name'] == '%s')]['value'].tolist()[0])"%(param_var,param))
+                except:
+                    try:
+                        exec("%s_list.append(df_spu[(df_spu['sku'] == prodcut_id) & (df_spu['attr_name'] == '%s')]['value'].tolist()[0])"%(param_var,param))
+                    except:
+                        exec("%s_list.append('无参数，需补充')"%param_var)
+
+        
+        res['产品编码'] = id_list
+        res['产品状态'] = state_list
+        res['产品名称'] = product_name_list
+        res['产品父品牌'] = father_brand_list
+        res['产品品牌'] = brand_list
+        res['产品类别'] = category_list
+
+        for index,row in params_df.iterrows():
+            param = row['subtitle']
+            needed_flag = row['needed_param']
+            standard_flag = row['standard_param']
+            if param == '产品名称':
+                continue
+            
+            param_var = '_' + ''.join(param.split()).replace('（','').replace('）','').replace('/','').replace('(','').replace(')','').replace('+','').replace('-','').replace('*','').replace('.','')
+
+            #标记标准项
+            if needed_flag == '1' and standard_flag == '1':
+                param = '*' + param
+                
+
+            exec("res['%s']=%s_list"%(param,param_var))
+    
+        res.to_excel(writer,f"{category_sheet_name}参数数据")
+        
+        
+        cursor_zdindex.execute(f"select goods_id,goods_name,platform_id,goods_url,index_price_wave from zd_week_price where periods in (select top 1 max(periods) from zd_entry_goods_price) and sub_category_code = {category_code} ")
+        data = (cursor_zdindex.fetchall())
+        price_df = pd.DataFrame(data,columns=[tuple[0] for tuple in cursor_zdindex.description])
+        price_df.to_excel(writer,f"{category_sheet_name}价格链接数据")
+        print(f"{category_name}数据导出完毕！")
+        
+    writer.save()
+    conn_zi_new.close()
+
+
+category = '复印纸'
+get_point_category_params_data(category)
\ No newline at end of file

公共代码/更新库内产品数据.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Thu Feb 25 10:53:59 2021
+
+@author: rico
+"""
+
+import pymssql
+import pandas as pd
+from public import Index
+
+
+def transform_simplevalue(cursor_zi_new,shujuzidiandf,categoryname,subtitle,stdvalue):
+    
+    stdvalue = stdvalue.strip()
+    
+    simple_subtitle_list = ['CPU型号','显存容量','操作系统','双面器','双面输稿器','网络打印','标配外服务及配件','标配外耗材','镜头描述','碎纸效果']
+    if subtitle not in simple_subtitle_list:
+        return stdvalue
+    
+    simplevalue_list = list(set(shujuzidiandf[(shujuzidiandf['categoryname'] == categoryname) & (shujuzidiandf['subtitle'] == subtitle) & (shujuzidiandf['stdvalue'] == stdvalue)]['simplevalue'].tolist()))
+    
+    if len(simplevalue_list) == 0:
+        print(f"非法值，不存在数据字典中。{subtitle},{stdvalue}")
+        #add_shujuzidian(cursor_zi_new,categoryname,subtitle,stdvalue)
+        return False
+    
+    elif len(simplevalue_list) == 1:
+        if simplevalue_list[0] == '无简称':
+            #add_shujuzidian(categoryname,subtitle,stdvalue)
+            return " "
+        else:
+            return simplevalue_list[0]
+        
+    else:
+        print(f"异常数据，具有多个简称。{subtitle},{stdvalue}")
+        return False
+
+
+
+def dael_name_content(skuname,brand):
+    #处理产品名称中 括号里的内容
+
+    skuname = skuname.replace(brand,'')
+
+    name_head = skuname.split('（')[0]
+    name_tail = skuname.split('（')[1].split('）')[1]
+       
+    name_content = skuname.split('（')[1].split('）')[0].split('/')
+    
+    if (len(list(set(name_content))) == 1 and name_content[0] == ' ') or (len(list(set(name_content))) == 2 and ' ' in name_content and '/' in name_content):
+        if name_tail == '': 
+            res = brand + name_head
+        else:
+            res = brand  + name_head + " " + name_tail
+    else:
+        temp_content = ''
+        for element in name_content:
+            if element == ' ':
+                continue
+            else:
+                temp_content += element + '/'
+        temp_content = "（" + temp_content.strip('/') + "）"
+        
+        if name_tail == '':
+            res = brand + name_head + temp_content
+        else:
+            if temp_content == '':
+                res = brand + name_head + " " + name_tail
+            else:
+                res = brand + name_head + temp_content + name_tail
+    
+    return res.strip()
+
+
+def upload_params_data(category,path):
+
+    df = pd.read_excel(path,converters = {'产品编码':str})
+    
+    
+    #创建新产品库链接
+    conn_zi_new = pymssql.connect(host='123.56.115.207', user='zgcprice3311',password='zgcprice20200628',database= 'ZI_NEW',autocommit=True)
+    cursor_zi_new = conn_zi_new.cursor()
+    
+    ##加载库中参数项数据（参数id，参数从属）
+    cursor_zi_new.execute(f"select * from vw_property where name = '{category}' and identy != '0000'")
+    db_params = pd.DataFrame(cursor_zi_new.fetchall(), columns=[tuple[0] for tuple in cursor_zi_new.description])
+    db_params['subtitle'] = db_params['subtitle'].apply(lambda x: x.strip())
+    subtitle_list = db_params['subtitle'].tolist()
+    
+    subtitle_id_dict = dict(zip(db_params['subtitle'].tolist(),db_params['subtitleid'].tolist()))
+    subtitle_type_dict = dict(zip(db_params['subtitle'].tolist(),db_params['skuorspu'].tolist()))
+    
+    #获取命名规则
+    cursor_zi_new.execute(f"select * from skuname_named_rule where categoryname = '{category}'")
+    named_rules_df = pd.DataFrame(cursor_zi_new.fetchall(), columns=[tuple[0] for tuple in cursor_zi_new.description])
+    
+    if named_rules_df.empty:
+        print(f"{category}类别无SKU命名规则，无法处理")
+        return False
+    named_rule = named_rules_df['rule'].str.cat()
+    
+    
+    #获取数据字典
+    cursor_zi_new.execute(f"select * from ShuJuZiDian_Cfg where categoryname = '{category}'")
+    data_dict = pd.DataFrame(cursor_zi_new.fetchall(), columns=[tuple[0] for tuple in cursor_zi_new.description])
+    data_dict['stdvalue'] = data_dict['stdvalue'].apply(lambda x : x.upper())
+    single_data_dict = data_dict
+    
+    
+    process_index = 0
+    index_ = Index()
+    #暂不支持复印纸命名
+    for index,row in df.iterrows():
+        try:
+            print(index_(process_index,len(df)-1), end='%')
+        except:
+            print(index_(process_index,1), end='%')
+        process_index+=1
+        
+        sku = row['产品编码']
+        brandname = row['产品品牌']
+        
+        params = dict(zip(subtitle_list,[row[subtitle] for subtitle in subtitle_list]))
+        
+        cursor_zi_new.execute(f"select id,spuid from p_sku where sku = '{sku}'")
+        skuid,spuid = cursor_zi_new.fetchone()
+        
+        skuname = ''
+        
+        for element in named_rule.split(" "):
+            
+            if element == '品牌名称':
+                value = brandname
+                
+            elif element == '类别名称':
+                value = category
+            
+            elif element[0] == "（" and "/" in element:
+                element = element.replace("（","").replace("）","")
+                detail_element_list = element.split("/")
+                for i in range(len(detail_element_list)):
+    
+                    #value = cat_sku_df[(cat_sku_df['sku'] == sku) & (cat_sku_df['name'] == detail_element_list[i])]['value'].tolist()[0]
+                    value = str(params[detail_element_list[i]])
+     
+                    value = transform_simplevalue(cursor_zi_new,single_data_dict,category,detail_element_list[i],value.upper())
+                    
+                    if i == 0:
+                        skuname += "（" + value + "/"
+                        
+                    elif i == len(detail_element_list)-1:
+                        skuname +=  value + "） "
+                        
+                    else:
+                        skuname +=  value + "/"
+                continue
+            
+            elif element[0] == "（" and "/" not in element:
+                element =  element.replace("（","").replace("）","")
+                
+                value = str(params[element])
+                
+                value = transform_simplevalue(cursor_zi_new,single_data_dict,category,element,value.upper())
+                
+                skuname += "（" + value + "） "
+                continue
+            
+            else:
+                value = str(params[element])
+                
+                value = transform_simplevalue(cursor_zi_new,single_data_dict,category,element,value.upper())
+                
+        
+            skuname += value + " "
+
+        skuname = skuname.strip()
+    
+        #处理名称中的空格
+        if category in ['复印纸','扫描仪']:
+            skuname = skuname    
+        
+        elif category in ['笔记本','台式机','一体电脑','碎纸机']:
+            
+            skuname = dael_name_content(skuname,brandname)
+    
+        elif category in ['复印机','多功能一体机','单反相机']:
+    
+            skuname_part1 = skuname.split(category)[0]
+            skuname_part2 = skuname.split(category)[1]
+            
+            skuname_1 = dael_name_content(skuname_part1,brandname)
+            skuname_2 = dael_name_content(skuname_part2,brandname).replace(brandname,"")
+            
+            skuname = skuname_1 + " " + category + skuname_2
+            
+        elif category in ['投影机','激光打印机','空调']:
+            if category == '空调':
+                skuname_part1 = skuname.split("空调 （")[0].strip()
+            else:
+                skuname_part1 = skuname.split(category)[0].strip()
+            skuname_part2 = skuname.replace("中央空调","").replace("空调扇","").split(category)[1]
+            
+            skuname_2 = dael_name_content(skuname_part2,brandname).replace(brandname,"")
+            
+            skuname = skuname_part1 + " " + category + skuname_2
+     
+        elif category in ['单电/微单相机']:
+            
+            skuname_part1 = skuname.split(category)[0]
+            skuname_part2 = skuname.split(category)[1]
+            
+            skuname_1 = dael_name_content(skuname_part1,brandname)
+            skuname_2 = dael_name_content(skuname_part2,brandname).replace(brandname,"")
+            
+            skuname = skuname_1 + " " + category + skuname_2
+        
+        else:
+            
+            skuname_part1 = skuname.split(category)[0].strip()
+            skuname_part2 = skuname.split(category)[1]
+            
+            skuname_2 = dael_name_content(skuname_part2,brandname).replace(brandname,"")
+            
+            skuname = skuname_part1 + " " +category + skuname_2
+            
+        cursor_zi_new.execute(f"update p_sku set skuname = '{skuname}' where sku = '{sku}'")
+        #print(skuname)
+        
+
+        
+        for subtitle in subtitle_list:
+            
+            value = row[subtitle].strip()
+            subtitleid = subtitle_id_dict[subtitle]
+            
+            subtitle_type = subtitle_type_dict[subtitle]
+            
+            if subtitle_type == 'sku':
+            
+                cursor_zi_new.execute(f"select id from p_skuvalue where subtitleid = {subtitleid} and value = '{value}' order by id")
+                data = cursor_zi_new.fetchall()
+                
+                try:
+                    valueid = pd.DataFrame(data, columns=[tuple[0] for tuple in cursor_zi_new.description])['id'].tolist()[0]
+                except:
+                    cursor_zi_new.execute(f"insert into p_skuvalue (subtitleid,value) values ({subtitleid}, '{value}')")
+                        
+                    cursor_zi_new.execute(f"select id from p_skuvalue where subtitleid = {subtitleid} and value = '{value}'")
+                    valueid = pd.DataFrame(cursor_zi_new.fetchall(), columns=[tuple[0] for tuple in cursor_zi_new.description])['id'].tolist()[0]
+                    
+                    
+                cursor_zi_new.execute(f"select a.valueid from p_skuvaluemap a \
+                                                  left join p_skuvalue b \
+                                                  on a.valueid = b.id \
+                                                  left join p_skusubtitle c \
+                                                  on b.subtitleid = c.id \
+                                                  where a.skuid = {skuid} and c.name = '{subtitle}'")
+                data = cursor_zi_new.fetchall()
+                valueid_df = pd.DataFrame(data, columns=[tuple[0] for tuple in cursor_zi_new.description])
+                
+                if valueid_df.empty:
+                    
+                    cursor_zi_new.execute(f"select id from p_skuvaluemap where skuid = {skuid} and valueid = {valueid}")
+                    data = cursor_zi_new.fetchall()
+                    check_df = pd.DataFrame(data, columns=[tuple[0] for tuple in cursor_zi_new.description])
+                    if check_df.empty:
+                        cursor_zi_new.execute(f"insert into p_skuvaluemap (skuid,valueid) values ({skuid}, {valueid})")
+                else:
+                    
+                    valueid_list = valueid_df['valueid'].unique().tolist()
+                    for valueid_ in valueid_list:
+                        cursor_zi_new.execute(f"delete from p_skuvaluemap where skuid = {skuid} and valueid = {valueid_}")
+                    
+                    cursor_zi_new.execute(f"select id from p_skuvaluemap where skuid = {skuid} and valueid = {valueid}")
+                    data = cursor_zi_new.fetchall()
+                    check_df = pd.DataFrame(data, columns=[tuple[0] for tuple in cursor_zi_new.description])
+                    if check_df.empty:
+                        cursor_zi_new.execute(f"insert into p_skuvaluemap (skuid,valueid) values ({skuid}, {valueid})")
+                        
+            elif subtitle_type == 'spu':
+                
+                cursor_zi_new.execute(f"select id from p_value where subtitleid = {subtitleid} and value = '{value}' order by id")
+                data = cursor_zi_new.fetchall()
+                
+                try:
+                    valueid = pd.DataFrame(data, columns=[tuple[0] for tuple in cursor_zi_new.description])['id'].tolist()[0]
+                except:
+                    cursor_zi_new.execute(f"insert into p_value (subtitleid,value) values ({subtitleid}, '{value}')")
+                        
+                    cursor_zi_new.execute(f"select id from p_value where subtitleid = {subtitleid} and value = '{value}'")
+                    valueid = pd.DataFrame(cursor_zi_new.fetchall(), columns=[tuple[0] for tuple in cursor_zi_new.description])['id'].tolist()[0]
+                    
+                    
+                cursor_zi_new.execute(f"select a.valueid from p_valuemap a \
+                                                  left join p_value b \
+                                                  on a.valueid = b.id \
+                                                  left join p_subtitle c \
+                                                  on b.subtitleid = c.id \
+                                                  where a.spuid = {spuid} and c.name = '{subtitle}'")
+                data = cursor_zi_new.fetchall()
+                valueid_df = pd.DataFrame(data, columns=[tuple[0] for tuple in cursor_zi_new.description])
+                
+                if valueid_df.empty:
+                    
+                    cursor_zi_new.execute(f"select id from p_valuemap where spuid = {spuid} and valueid = {valueid}")
+                    data = cursor_zi_new.fetchall()
+                    check_df = pd.DataFrame(data, columns=[tuple[0] for tuple in cursor_zi_new.description])
+                    if check_df.empty:
+                        cursor_zi_new.execute(f"insert into p_valuemap (spuid,valueid) values ({spuid}, {valueid})")
+                else:
+                    
+                    valueid_list = valueid_df['valueid'].unique().tolist()
+                    for valueid_ in valueid_list:
+                        cursor_zi_new.execute(f"delete from p_valuemap where spuid = {spuid} and valueid = {valueid_}")
+                    
+                    cursor_zi_new.execute(f"select id from p_valuemap where spuid = {spuid} and valueid = {valueid}")
+                    data = cursor_zi_new.fetchall()
+                    check_df = pd.DataFrame(data, columns=[tuple[0] for tuple in cursor_zi_new.description])
+                    if check_df.empty:
+                        cursor_zi_new.execute(f"insert into p_valuemap (spuid,valueid) values ({spuid}, {valueid})")
+    
+    conn_zi_new.close()
+    print(f"{category_name}参数数据更新完成，命名完成")
+    
+ 
+category_name = ''
+path = ''
+   
+upload_params_data(category_name,path)
\ No newline at end of file

公共代码/校验参数数据.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Feb 24 15:07:58 2021
+
+@author: rico
+"""
+import pandas as pd
+import pymssql
+from public import zgc_api
+
+
+def check_data(category_name,path):
+
+    df = pd.read_excel(path,converters = {'产品编码':str})
+    df = df.rename(columns = {'Unnamed: 0':'id'})
+    
+    
+    if '无参数，需补充' in df.values:
+        print("仍有参数未补充，请补充完整后再继续处理。")
+        return False
+        
+    #创建新产品库链接
+    conn_zi_new = pymssql.connect(host='123.56.115.207', user='zgcprice3311',password='zgcprice20200628',database= 'ZI_NEW',autocommit=True)
+    cursor_zi_new = conn_zi_new.cursor()
+    
+    #进行非标转标
+    
+    ##加载库中参数项数据（参数id，参数从属）
+    cursor_zi_new.execute(f"select * from vw_property where name = '{category_name}'")
+    db_params = pd.DataFrame(cursor_zi_new.fetchall(), columns=[tuple[0] for tuple in cursor_zi_new.description])
+    db_params['standard_param'] = db_params['identy'].apply(lambda x: x[2])
+    db_params = db_params[db_params['standard_param'] != '0']
+    db_params['subtitle'] = db_params['subtitle'].apply(lambda x: x.strip())
+    
+    #subtitle_id_list = dict(zip(db_params['subtitle'].tolist(),db_params['subtitleid'].tolist()))
+    #subtitle_type_list = dict(zip(db_params['subtitle'].tolist(),db_params['skuorspu'].tolist()))
+    params_list = df.columns.tolist()[-len(db_params['subtitle']):]
+    recover_params_list = [params[1:] for params in params_list]
+    rename_dict = dict(zip(params_list,recover_params_list))
+    
+    df = df.rename(columns = rename_dict)
+
+    
+    ##数据准备
+    id_list = list()
+    params_list = list()
+    for index,row in df.iterrows():
+        id_ = row['id']
+        id_list.append(id_)
+    
+        temp_key_list = list()
+        temp_value_list = list()
+        for db_param in db_params['subtitle'].tolist():
+            if db_param in ['产品型号', 'CPU属性']:
+                continue
+            temp_key_list.append(db_param)
+            temp_value_list.append(row[db_param])
+        params_list.append(dict(zip(temp_key_list, temp_value_list)))
+    print(f"{category_name}数据准备完成")
+    
+    
+    ##获取标准参数值
+    data = {
+        "params_info": {
+            "category": category_name,
+            "id_list": id_list,
+            "params_dict_list": params_list
+        }
+    }
+    res = zgc_api("GetZGCParamValuesInfo", data)
+    res_value_dict = res['paramsValue_dict']
+    
+    #非标准值添加数据字典
+    flag = False
+    dict_id_list = list()
+    for index,row in df.iterrows():
+        id_ = str(row['id'])
+        for db_param in db_params['subtitle'].tolist():
+            if db_param in ['产品型号', 'CPU属性']:#CPU属性为衍生属性，需要特殊处理
+                continue
+            pri_value = row[db_param]
+            value, value_flag = tuple(res_value_dict[id_][db_param].items())[0]
+            
+            if value_flag == False:
+                
+                cursor_zi_new.execute(f"select * from ShuJuZiDian_Cfg where categoryname = '{category_name}' and subtitle = '{db_param}' and primitive = '{pri_value}'")
+                check_df = pd.DataFrame(cursor_zi_new.fetchall(),
+                                        columns=[tuple[0] for tuple in cursor_zi_new.description])
+    
+                if check_df.empty:
+                    flag = True
+                    cursor_zi_new.execute(f"insert into ShuJuZiDian_Cfg (categoryname,subtitle,primitive) values ('{category_name}','{db_param}','{pri_value}')")
+                    
+                    cursor_zi_new.execute(f"select id from ShuJuZiDian_Cfg where categoryname = '{category_name}' and subtitle = '{db_param}' and primitive = '{pri_value}'")
+                    dict_id = cursor_zi_new.fetchone()[0]
+                    dict_id_list.append(dict_id)
+                    
+    if flag:
+        
+        if len(dict_id_list) == 1:
+            _id = dict_id_list[0]
+            cursor_zi_new.execute(f"select * from ShuJuZiDian_Cfg where stdvalue is Null and id = {_id}")
+        else:
+            cursor_zi_new.execute("select * from ShuJuZiDian_Cfg where stdvalue is Null and id in (%s)" % ','.join(['%s'] * len(dict_id_list)),tuple(dict_id_list))
+        fill_shujuzidian_df = pd.DataFrame(cursor_zi_new.fetchall(), columns=[tuple[0] for tuple in cursor_zi_new.description])
+        fill_shujuzidian_df.to_excel(f"{category_name}数据字典补充.xlsx")
+    else:
+        
+        for db_param in db_params['subtitle'].tolist():
+            if db_param == '产品型号':
+                continue
+            param_var = '_' + ''.join(db_param.split()).replace('（','').replace('）','').replace('/','').replace('(','').replace(')','').replace('+','').replace('-','').replace('*','').replace('.','')
+            exec('%s_list=[]'%param_var)
+        
+        for index,row in df.iterrows():
+            id_ = str(row['id'])
+            for db_param in db_params['subtitle'].tolist():
+                param_var = '_' + ''.join(db_param.split()).replace('（','').replace('）','').replace('/','').replace('(','').replace(')','').replace('+','').replace('-','').replace('*','').replace('.','')
+                if db_param == '产品型号':
+                    continue
+                elif db_param == 'CPU属性':
+                    value,value_flag = tuple(res_value_dict[id_]['CPU型号'].items())[0]
+                    if '飞腾' in value or '龙芯' in value or '兆芯' in value:
+                        pass
+                    else:
+                        value = value.split('-')[0]
+                else:
+                    value,value_flag = tuple(res_value_dict[id_][db_param].items())[0]
+                    
+                exec("%s_list.append('%s')"%(param_var,value))
+                
+        for db_param in db_params['subtitle'].tolist():
+            if db_param == '产品型号':
+                continue
+            param_var = '_' + ''.join(db_param.split()).replace('（','').replace('）','').replace('/','').replace('(','').replace(')','').replace('+','').replace('-','').replace('*','').replace('.','')
+    
+            exec("df['%s']=%s_list"%(db_param,param_var))
+        
+        path = path.split('.xlsx')[0] + '(校验通过).xlsx'
+        df.to_excel(path,index=False)
+        print(f"{category_name}数据通过校验，可更新库内参数")
+
+
+category_name = ''
+path = ''
+
+check_data(category_name,path)
+
+
+
+
+
+
+
+
+
+
+
+
+
+