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Wenxixi 2025-06-18 12:08:06 +08:00
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commit 180b4fda1d
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产品上限优化.ipynb
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@ -2,12 +2,60 @@
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"df = pd.read_clipboard()"
"from utils.gtools import MySQLconnect\n",
"categories = '94 - Office Desks'\n",
"with MySQLconnect('ods') as db:\n",
" engine = db.engine()\n",
" sql = f\"\"\"\n",
"WITH a AS (\n",
"\tSELECT\n",
"\t\tt1.SPU,\n",
"\t\tt2.SKU,\n",
"\t\tt1.产品分类,\n",
"\t\tt1.添加时间,\n",
"\t\torder_date,\n",
"\t\tt2.成本价,\n",
"\t\topl.product_price_dollar,\n",
"\t\topl.product_num,\n",
"\t\tTIMESTAMPDIFF( MONTH, t1.添加时间, order_date ) AS month_diff \n",
"\tFROM\n",
"\t\tods.stg_bayshop_litfad_spu t1\n",
"\t\tLEFT JOIN ods.stg_bayshop_litfad_sku t2 ON t2.产品PID = t1.产品PID\n",
"\t\tLEFT JOIN dws.order_product_list opl ON t2.SKU = opl.SKU \n",
"\tWHERE\n",
"\t\tt1.添加时间 BETWEEN '2023-01-01' \n",
"\t\tAND '2025-06-16 23:59:59' \n",
"\t\tAND 产品分类 = '{categories}'\n",
"\t\tAND t2.SKU IS NOT NULL \n",
"\t),\n",
"\tb AS (\n",
"\tSELECT\n",
"\t\tSPU,\n",
"\t\tSKU,添加时间,产品分类,成本价,\n",
"\t\tb.erp_package_vol,\n",
"\t\torder_date,\n",
"\tIF\n",
"\t\t( month_diff >= 6, NULL, month_diff ) AS month_diff,\n",
"\t\tROW_NUMBER() over ( PARTITION BY SKU ORDER BY order_date DESC ) AS ranking \n",
"\tFROM\n",
"\t\ta\n",
"\t\tLEFT JOIN dwd.dim_erp_sku_package_vol_info b ON a.SKU = b.erp_sku \n",
"\t) SELECT\n",
"\tSPU,\n",
"\tSKU,添加时间,产品分类,成本价,\n",
"\tb.erp_package_vol \n",
"FROM\n",
"\tb \n",
"WHERE\n",
"\tranking = 1 \n",
"\tAND month_diff IS NULL\n",
"\"\"\"\n",
" df = pd.read_sql(sql, engine)"
]
},
{
@ -26,22 +74,41 @@
"import json\n",
"import re\n",
"from utils import Package,Package_group\n",
"from sell.sell_price import call_sell_and_order_price\n",
"def extract_number(value):\n",
" # 提取字符串中的第一个数字\n",
" match = re.search(r\"[-+]?\\d*\\.\\d+|\\d+\", str(value))\n",
" return float(match.group()) if match else 0.0\n",
"for index, row in df.iterrows():\n",
" package_dict = json.loads(row['erp_package_vol'])\n",
" max_length = 0 # 最长边\n",
" max_girth = 0 # 最大围长\n",
" all_weight = 0 # 总重量\n",
" all_vol_weight = 0 # 总抛重\n",
" for key, package in package_dict.items():\n",
" package_dict = json.loads(row['erp_package_vol'])\n",
" max_length = 0 # 最长边\n",
" max_girth = 0 # 最大围长\n",
" all_weight = 0 # 总重量\n",
" all_vol_weight = 0 # 总抛重\n",
" for key, package in package_dict.items():\n",
" package['长'] = extract_number(package['长'])\n",
" package['宽'] = extract_number(package['宽'])\n",
" package['高'] = extract_number(package['高'])\n",
" package['重量'] = extract_number(package['重量'])\n",
" "
" size =sorted([package['长'],package['宽'],package['高']])\n",
" fst_size = size[0]\n",
" snd_size = size[1]\n",
" thd_size = size[2]\n",
" max_length=max(max_length,fst_size)\n",
" max_girth=max(max_girth,fst_size+(snd_size+thd_size)*2)\n",
" all_weight+=package['重量']/1000\n",
" all_vol_weight+=package['长']*package['宽']*package['高']/6000\n",
" sell_price,order_price,order_type = call_sell_and_order_price(row['成本价'], row['erp_package_vol'],\"海运\")\n",
" df.loc[index,'网站售价'] = sell_price[0]\n",
" df.loc[index,'物流分摊费'] = sell_price[1]\n",
" df.loc[index,'订单物流费'] = order_price\n",
" df.loc[index,'尾端类型'] = order_type\n",
" df.loc[index,'最长边'] = max_length\n",
" df.loc[index,'最大围长'] = max_girth\n",
" df.loc[index,'总重量'] = all_weight\n",
" df.loc[index,'总抛重'] = all_vol_weight\n",
"\n",
"# 按照那个分组，按照总抛重，每5总抛重为一组，最长边取大，最短边取小，最大实重取大，最小实重取小，网站售价求和，物流分摊费求和，订单物流费求和，尾端类型不要，"
]
}
],