137 lines
4.7 KiB
Plaintext
137 lines
4.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"from utils.gtools import MySQLconnect\n",
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"categories = '94 - Office Desks'\n",
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"with MySQLconnect('ods') as db:\n",
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" engine = db.engine()\n",
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" sql = f\"\"\"\n",
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"WITH a AS (\n",
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"\tSELECT\n",
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"\t\tt1.SPU,\n",
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"\t\tt2.SKU,\n",
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"\t\tt1.产品分类,\n",
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"\t\tt1.添加时间,\n",
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"\t\torder_date,\n",
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"\t\tt2.成本价,\n",
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"\t\topl.product_price_dollar,\n",
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"\t\topl.product_num,\n",
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"\t\tTIMESTAMPDIFF( MONTH, t1.添加时间, order_date ) AS month_diff \n",
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"\tFROM\n",
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"\t\tods.stg_bayshop_litfad_spu t1\n",
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"\t\tLEFT JOIN ods.stg_bayshop_litfad_sku t2 ON t2.产品PID = t1.产品PID\n",
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"\t\tLEFT JOIN dws.order_product_list opl ON t2.SKU = opl.SKU \n",
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"\tWHERE\n",
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"\t\tt1.添加时间 BETWEEN '2023-01-01' \n",
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"\t\tAND '2025-06-16 23:59:59' \n",
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"\t\tAND 产品分类 = '{categories}'\n",
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"\t\tAND t2.SKU IS NOT NULL \n",
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"\t),\n",
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"\tb AS (\n",
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"\tSELECT\n",
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"\t\tSPU,\n",
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"\t\tSKU,添加时间,产品分类,成本价,\n",
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"\t\tb.erp_package_vol,\n",
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"\t\torder_date,\n",
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"\tIF\n",
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"\t\t( month_diff >= 6, NULL, month_diff ) AS month_diff,\n",
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"\t\tROW_NUMBER() over ( PARTITION BY SKU ORDER BY order_date DESC ) AS ranking \n",
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"\tFROM\n",
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"\t\ta\n",
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"\t\tLEFT JOIN dwd.dim_erp_sku_package_vol_info b ON a.SKU = b.erp_sku \n",
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"\t) SELECT\n",
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"\tSPU,\n",
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"\tSKU,添加时间,产品分类,成本价,\n",
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"\tb.erp_package_vol \n",
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"FROM\n",
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"\tb \n",
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"WHERE\n",
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"\tranking = 1 \n",
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"\tAND month_diff IS NULL\n",
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"\"\"\"\n",
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" df = pd.read_sql(sql, engine)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"得到每个SKU的最长边，围长，总重量，6000抛重，采购体积比（采购/6000抛重）"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import json\n",
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"import re\n",
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"from utils import Package,Package_group\n",
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"from sell.sell_price import call_sell_and_order_price\n",
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"def extract_number(value):\n",
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" # 提取字符串中的第一个数字\n",
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" match = re.search(r\"[-+]?\\d*\\.\\d+|\\d+\", str(value))\n",
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" return float(match.group()) if match else 0.0\n",
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"for index, row in df.iterrows():\n",
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" package_dict = json.loads(row['erp_package_vol'])\n",
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" max_length = 0 # 最长边\n",
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" max_girth = 0 # 最大围长\n",
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" all_weight = 0 # 总重量\n",
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" all_vol_weight = 0 # 总抛重\n",
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" for key, package in package_dict.items():\n",
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" package['长'] = extract_number(package['长'])\n",
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" package['宽'] = extract_number(package['宽'])\n",
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" package['高'] = extract_number(package['高'])\n",
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" package['重量'] = extract_number(package['重量'])\n",
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" size =sorted([package['长'],package['宽'],package['高']])\n",
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" fst_size = size[0]\n",
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" snd_size = size[1]\n",
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" thd_size = size[2]\n",
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" max_length=max(max_length,fst_size)\n",
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" max_girth=max(max_girth,fst_size+(snd_size+thd_size)*2)\n",
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" all_weight+=package['重量']/1000\n",
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" all_vol_weight+=package['长']*package['宽']*package['高']/6000\n",
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" sell_price,order_price,order_type = call_sell_and_order_price(row['成本价'], row['erp_package_vol'],\"海运\")\n",
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" df.loc[index,'网站售价'] = sell_price[0]\n",
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" df.loc[index,'物流分摊费'] = sell_price[1]\n",
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" df.loc[index,'订单物流费'] = order_price\n",
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" df.loc[index,'尾端类型'] = order_type\n",
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" df.loc[index,'最长边'] = max_length\n",
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" df.loc[index,'最大围长'] = max_girth\n",
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" df.loc[index,'总重量'] = all_weight\n",
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" df.loc[index,'总抛重'] = all_vol_weight\n",
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"\n",
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"# 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，"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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