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Wenxixi 2025-06-18 12:08:06 +08:00
parent 5a1d91b5da
commit 180b4fda1d
1 changed files with 76 additions and 9 deletions

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@ -2,12 +2,60 @@
"cells": [ "cells": [
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 9,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"import pandas as pd\n", "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 json\n",
"import re\n", "import re\n",
"from utils import Package,Package_group\n", "from utils import Package,Package_group\n",
"from sell.sell_price import call_sell_and_order_price\n",
"def extract_number(value):\n", "def extract_number(value):\n",
" # 提取字符串中的第一个数字\n", " # 提取字符串中的第一个数字\n",
" match = re.search(r\"[-+]?\\d*\\.\\d+|\\d+\", str(value))\n", " match = re.search(r\"[-+]?\\d*\\.\\d+|\\d+\", str(value))\n",
" return float(match.group()) if match else 0.0\n", " return float(match.group()) if match else 0.0\n",
"for index, row in df.iterrows():\n", "for index, row in df.iterrows():\n",
" package_dict = json.loads(row['erp_package_vol'])\n", " package_dict = json.loads(row['erp_package_vol'])\n",
" max_length = 0 # 最长边\n", " max_length = 0 # 最长边\n",
" max_girth = 0 # 最大围长\n", " max_girth = 0 # 最大围长\n",
" all_weight = 0 # 总重量\n", " all_weight = 0 # 总重量\n",
" all_vol_weight = 0 # 总抛重\n", " all_vol_weight = 0 # 总抛重\n",
" for key, package in package_dict.items():\n", " for key, package in package_dict.items():\n",
" package['长'] = extract_number(package['长'])\n", " package['长'] = extract_number(package['长'])\n",
" package['宽'] = extract_number(package['宽'])\n", " package['宽'] = extract_number(package['宽'])\n",
" package['高'] = extract_number(package['高'])\n", " package['高'] = extract_number(package['高'])\n",
" package['重量'] = extract_number(package['重量'])\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"
] ]
} }
], ],