init

func_timer.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Nov  4 13:19:46 2019
+
+@author: rico
+"""
+
+import time
+
+def timer(func):
+    def wrapper(*args,**kwds):
+        t0 = time.time()
+        res = func(*args,**kwds)
+        t1 = time.time()
+        print(func.__name__+'耗时%0.3f秒'%(t1-t0))
+        return res
+    return wrapper

function.py

+# -*- coding: utf-8 -*-
+import pymssql
+import pandas as pd
+import re
+from lxml import etree
+'''
+class product():
+    def __init__(self, product_name, product_SKU, product_class_num = 'na'):
+        self.product_name = str(product_name)
+        self.product_SKU = str(product_SKU)
+        self.product_class = str(product_class_num)
+
+    def get_parameter(self, **kwargs):
+'''
+
+class sql_find():
+    
+    def __init__ (self, database='ZI_DataBase', localhost=True):
+        if localhost:
+            self.conn = pymssql.connect(host='localhost', user='zgc',password='1234',database=database,autocommit=True)
+        else:
+            self.conn = pymssql.connect(host='123.56.115.207', user='zgcprice3311',password='admin@2018@)!*',database=database,autocommit=True)
+        self.cursor = self.conn.cursor()
+    '''
+    def execute(self, sql_sentence):
+        self.cursor.execute(sql_sentence)
+        return self.cursor
+    '''
+def BN(brand):
+    brand = str(brand)
+    try:
+        country = brand.split('[')[1].split(']')[-2]
+        brand = brand.replace(country,'')
+    except IndexError:
+        pass
+    res = re.findall(r'[\u4E00-\u9FA5]', brand)
+    new_res = ''.join(res)
+	#print(len(new_res))
+    if len(new_res) == 0:
+        res1 = re.findall(r'[a-zA-Z0-9]', brand)
+        new_res = ''.join(res1)
+        new_res = new_res.upper()
+    return new_res
+
+    
+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)
+
+class tool():
+    def __init__(self):
+        self.peijian_table = pd.read_excel('是否需要配件.xlsx')
+        self.brand_table = pd.read_excel('品牌对应表.xlsx')
+    
+    def judge_brand(self, brand, brandcode_original):
+        if brandcode_original == '没有对应指数品牌':
+            BRANDID = '没有对应指数品牌'
+            for ID,Chinese_brand,English_brand in zip(self.brand_table['ID'], self.brand_table['中文品牌'], self.brand_table['英文品牌']):
+                if brand == Chinese_brand:
+                    BRANDID = str(ID).zfill(5)
+                    return BRANDID
+                elif BN(brand) == English_brand:
+                    BRANDID = str(ID).zfill(5)
+                    return BRANDID
+        else:
+            BRANDID = str(brandcode_original).zfill(5)[-5:]
+        return BRANDID
+    
+    def judge_peijian(self, data_table):
+        ispeijian_lyst = []
+        isunique_lyst = []
+        for class_code in data_table['指数子类编码']:
+            mark = '0'
+            mark2 = '0'
+            class_code = str(class_code).zfill(4)
+            if class_code != '没有匹配的指数子类编码':
+                for categorycode, ispeijian, isunique in zip(self.peijian_table['categorycode'], self.peijian_table['ispeijian'], self.peijian_table['isunique']):
+                    if class_code == str(categorycode).zfill(4):
+                        if str(ispeijian) != '0':
+                            mark = '1'
+                        if str(isunique) != '0':
+                            mark2 = '1'
+                        break
+                ispeijian_lyst.append(mark)
+                isunique_lyst.append(mark2)
+            else:
+                ispeijian_lyst.append(mark)
+                isunique_lyst.append(mark2)
+        #print(len(ispeijian_lyst), len(data_table['指数子类编码']))
+        data_table['有无配件'] = ispeijian_lyst
+        data_table['型号_only'] = isunique_lyst
+        return data_table
+
+def judge_unit(string):
+    unit_list = {'MM','CM', 'DM', 'ML', 'W', 'KW'}
+    if not string[0].isdigit():
+        return True
+    m = 0
+    for char in string:
+        if char.isdigit() or char == '.':
+            m += 1
+            continue
+        elif char.isalpha():
+            if string[m:].upper() in unit_list:
+                return False
+            else:
+                return True
+    return True
+
+def type_extract_JD(name, params, brand):
+    #params = eval(params)
+    try:
+        brand_remove = re.findall(r"[A-Za-z0-9]+", brand)[0].upper()
+    except IndexError:
+        brand_remove = '没有英文品牌！'
+    param_xinghao = 'NA'
+    if '型号' in params:
+        param_xinghao = params['型号']
+    elif r'\t型号\t' in params:
+        param_xinghao = params[r'\t型号\t']
+    name_xinghao_lyst = list(filter(lambda x: len(x) >= 2, re.findall(r"[A-Za-z0-9-+/.*]+", name)))
+    for i in range(len(name_xinghao_lyst)):
+        name_xinghao_lyst[i] = name_xinghao_lyst[i].upper()
+    try:
+        name_xinghao_lyst.remove(brand_remove)
+    except ValueError:
+        pass
+    if len(name_xinghao_lyst) == 0:
+        #type_lyst.append(param_xinghao.upper())
+        return param_xinghao.upper()
+    else:
+        if param_xinghao in name_xinghao_lyst:
+            #type_lyst.append(param_xinghao.upper())
+            return param_xinghao.upper()
+        else:
+            xinghao_data = max(name_xinghao_lyst, key=len)
+            for xinghao in name_xinghao_lyst:
+                if len(xinghao) > 2 and '*' not in xinghao and judge_unit(xinghao):
+                    xinghao_data = xinghao
+                    break
+            if not judge_unit(xinghao_data):
+                xinghao_data == 'NA'
+            #type_lyst.append(xinghao_data.upper())
+            return xinghao_data
+
+
+def type_extract(name, params):
+    #params = eval(params)
+    param_xinghao = 'NA'
+    if '型号' in params:
+        param_xinghao = params['型号']
+    elif r'\t型号\t' in params:
+        param_xinghao = params[r'\t型号\t']
+    name_xinghao_lyst = list(filter(lambda x: len(x) >= 2, re.findall(r"[A-Za-z0-9-+/.*]+", name)))
+    if len(name_xinghao_lyst) == 0:
+        #type_lyst.append(param_xinghao.upper())
+        return param_xinghao.upper()
+    else:
+        if param_xinghao in name_xinghao_lyst:
+            #type_lyst.append(param_xinghao.upper())
+            return param_xinghao.upper()
+        else:
+            xinghao_data = max(name_xinghao_lyst, key=len)
+            for xinghao in name_xinghao_lyst:
+                if len(xinghao) > 2 and '*' not in xinghao and judge_unit(xinghao):
+                    xinghao_data = xinghao
+                    break
+            if not judge_unit(xinghao_data):
+                xinghao_data == 'NA'
+            #type_lyst.append(xinghao_data.upper())
+            return xinghao_data.upper()
+
+def param_load(product_id, xml_string):
+    """
+    传入sku，和xml原始代码
+    :param product_id:sku
+    :param xml_string:xml数据
+    :return:csv
+    """
+    xml_str = etree.HTML(xml_string)
+    #title = xml_str.xpath("//th[@class='tdTitle']")
+    secend = xml_str.xpath("//td[@class='tdTitle']")
+    zhi = xml_str.xpath("//tr//td[position()>1]")
+    data_dict = {}
+    for j, k in zip(secend, zhi):
+        #item = i.xpath("./text()")[0]
+        sec = j.xpath("./text()")[0]
+        value = k.xpath("./text()")[0]
+        data_dict[sec] = value
+    return data_dict
+
+if __name__ == '__main__':
+    sqlserver = sql_find('ZI_BAK', True)
+    sqlserver.cursor.execute("select * from ZI_Price_Quote where  productcode = '0506003750007'")
+    print(sqlserver.cursor.fetchall())
+
+    

priceModel_ds.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Dec 24 09:27:37 2019
+
+@author: rico
+"""
+#方案一：提前计算
+#方案二：实时计算
+
+#输入：产品名称输入、差异还原标识（未匹配到具体SKU，但匹配到SPU）
+
+import pymysql
+import pymssql
+from func_timer import timer
+import pandas as pd
+import dask.dataframe as dd
+from sqlalchemy import create_engine
+
+
+'''
+def Descartes(*args,repeat=1):
+    pools = [tuple(pool) for pool in args] * repeat
+    result = [[]]
+    for pool in pools:
+        result = [x + [y] for x in result for y in pool]
+    for prod in result:
+        yield tuple(prod)
+
+
+list(Descartes(['i3-7500','i5-7825'],['4G','8G']))
+'''
+
+
+@timer
+def get_price_data():
+    
+    conn = pymssql.connect('123.56.115.207','zgcindex','jiayou2017+2018','price_calculate')
+    cursor = conn.cursor()
+    cursor.execute("select * from vw_electricity_source_price")
+    price_df = pd.DataFrame([v for v in cursor.fetchall()],columns=[tuple[0] for tuple in cursor.description])
+        
+    cursor.close()
+    conn.close()
+    return price_df
+
+@timer
+def calculate_with_df(price_df):
+    
+    dfp = price_df
+    dfp['entry_retail_price'] = pd.to_numeric(dfp['entry_retail_price'])*4
+
+    dfp = dfp.groupby('ProductCode').entry_retail_price.mean()
+    
+    return dfp
+
+@timer
+def calculate_with_dd(price_df):
+    
+    dfp = price_df
+    dfp['entry_retail_price'] = pd.to_numeric(dfp['entry_retail_price'])
+
+    df = dd.from_pandas(dfp,npartitions = 1)
+    df.entry_retail_price = df.entry_retail_price*4
+    df = df.groupby('ProductCode').entry_retail_price.mean()
+    b = df.compute()
+    
+    return b
+
+df = get_price_data()
+a = calculate_with_df(df)
+b = calculate_with_dd(df)
+