Forestry → Market → Sawmill → Precut → Builder
                ↓
            Manufacturer → Wholesaler → Other

// AWS Cognitoのカスタム属性で8種類のユーザー属性を管理
interface UserAttributes {
  'custom:user_type': 'lumber_mill' | 'market' | 'manufacturer' | 'precut' | 'builder' | 'wholesaler' | 'other';
  'custom:company_id': string;
  'custom:permissions': string; // "create_order,view_inventory,manage_users"
}

// 権限チェック関数
const hasPermission = (user: UserAttributes, permission: string): boolean => {
  const permissions = user['custom:permissions'].split(',');
  return permissions.includes(permission);
};

// TypeScriptによる型安全なユーザー属性管理
type UserType = 'lumber_mill' | 'market' | 'manufacturer';

interface User {
  id: string;
  userType: UserType;
  companyId: string;
  permissions: Set<Permission>;
}

// ユーザー属性ごとの条件付きレンダリング
const Dashboard: React.FC<{ user: User }> = ({ user }) => {
  return (
    <div>
      {user.permissions.has('create_order') && <CreateOrderButton />}
      {user.permissions.has('view_inventory') && <InventoryList />}
      {user.userType === 'market' && <MarketPriceChart />}
    </div>
  );
};

import { useQuery } from '@tanstack/react-query';

const useInventory = (companyId: string) => {
  return useQuery({
    queryKey: ['inventory', companyId],
    queryFn: () => fetchInventory(companyId),
    staleTime: 5 * 60 * 1000, // 5分間キャッシュ
    refetchOnWindowFocus: true,
  });
};

// コンポーネントでの使用
const InventoryList: React.FC = () => {
  const { data, isLoading, error } = useInventory(user.companyId);

  if (isLoading) return <Spinner />;
  if (error) return <ErrorMessage error={error} />;

  return <Table data={data} />;
};

# 帳票生成：openpyxl で Excel を作り、LibreOffice ヘッドレスで PDF 化
import subprocess
from openpyxl import load_workbook

def generate_invoice(order) -> tuple[str, str]:
    """請求書を Excel テンプレートから生成し、PDF へ変換する。"""
    wb = load_workbook("templates/invoice.xlsx")
    ws = wb.active
    ws["B2"] = order.invoice_number
    ws["B3"] = order.customer_name
    # ... 明細を流し込む
    xlsx_path = f"invoices/{order.id}.xlsx"
    wb.save(xlsx_path)

    # 業務帳票はレイアウト再現性が重要なので、表計算をそのまま PDF 化する
    subprocess.run(
        ["libreoffice", "--headless", "--convert-to", "pdf", "--outdir", "invoices/", xlsx_path],
        check=True,
    )
    return xlsx_path, xlsx_path.replace(".xlsx", ".pdf")


# Excel→DB 取り込み：openpyxl（read_only）＋ psycopg2 の execute_values で一括 INSERT
from openpyxl import load_workbook
from psycopg2.extras import execute_values

def import_excel_to_db(conn, file_path: str) -> None:
    """既存 Excel を DB へ一括インポートする（S3 トリガーの Lambda で実行）。"""
    wb = load_workbook(file_path, read_only=True, data_only=True)
    rows = []
    for r in wb.active.iter_rows(min_row=2, values_only=True):
        product_id, name, price, stock = r
        if product_id is None or price is None:
            continue  # 欠損行はスキップ
        rows.append((product_id, name, float(price), stock))

    with conn.cursor() as cur:
        execute_values(
            cur,
            "INSERT INTO products (product_id, name, price, stock) VALUES %s",
            rows,  # 行ループの個別 INSERT ではなく一括投入（高速・低負荷）
        )
    conn.commit()

# ECS Cluster
resource "aws_ecs_cluster" "main" {
  name = "lumber-saas-cluster"

  setting {
    name  = "containerInsights"
    value = "enabled"
  }
}

# ECS Task Definition
resource "aws_ecs_task_definition" "app" {
  family                   = "lumber-saas-app"
  requires_compatibilities = ["FARGATE"]
  network_mode             = "awsvpc"
  cpu                      = "1024"
  memory                   = "2048"

  container_definitions = jsonencode([{
    name  = "app"
    image = "${var.ecr_repository_url}:latest"
    portMappings = [{
      containerPort = 8080
      protocol      = "tcp"
    }]
    environment = [
      { name = "DATABASE_URL", value = var.database_url },
      { name = "COGNITO_USER_POOL_ID", value = aws_cognito_user_pool.main.id }
    ]
  }])
}

# Auto Scaling
resource "aws_appautoscaling_target" "ecs_target" {
  max_capacity       = 10
  min_capacity       = 2
  resource_id        = "service/${aws_ecs_cluster.main.name}/${aws_ecs_service.app.name}"
  scalable_dimension = "ecs:service:DesiredCount"
  service_namespace  = "ecs"
}

resource "aws_appautoscaling_policy" "ecs_policy" {
  name               = "scale-up"
  policy_type        = "TargetTrackingScaling"
  resource_id        = aws_appautoscaling_target.ecs_target.resource_id
  scalable_dimension = aws_appautoscaling_target.ecs_target.scalable_dimension
  service_namespace  = aws_appautoscaling_target.ecs_target.service_namespace

  target_tracking_scaling_policy_configuration {
    target_value = 70.0
    predefined_metric_specification {
      predefined_metric_type = "ECSServiceAverageCPUUtilization"
    }
  }
}

// ag-Grid を使用したExcelライクなテーブル
import { AgGridReact } from 'ag-grid-react';

const InventoryTable: React.FC = () => {
  const columnDefs = [
    { field: 'product_name', headerName: '商品名', editable: true },
    { field: 'stock', headerName: '在庫数', editable: true },
    { field: 'price', headerName: '単価', editable: true },
  ];

  const onCellValueChanged = (params: any) => {
    // セル編集時、自動保存
    updateInventory(params.data);
  };

  return (
    <AgGridReact
      columnDefs={columnDefs}
      rowData={inventoryData}
      onCellValueChanged={onCellValueChanged}
      enableRangeSelection={true} // Excel風の範囲選択
    />
  );
};

// ❌ 悪い例
throw new Error('ValidationError: field "price" must be positive');

// ✅ 良い例
throw new Error('価格は0円以上で入力してください。現在の入力値: -1000円');

Phase 1 (1–3 months): Information sharing only (Excel allowed alongside)
  ↓
Phase 2 (4–6 months): Partial migration of the ordering feature (Excel alongside)
  ↓
Phase 3 (7–12 months): Full migration (Excel retired)

# Phase 1: Excel アップロード機能
@app.route('/api/inventory/upload', methods=['POST'])
def upload_excel():
    """既存Excelをアップロードして、DBに同期"""
    file = request.files['file']
    df = pd.read_excel(file)

    # DB同期
    sync_inventory_from_dataframe(df)

    return jsonify({'message': 'Excelをアップロードしました。Web画面でも確認できます。'})

# Phase 2: Excelダウンロード機能（Excel併用）
@app.route('/api/inventory/download', methods=['GET'])
def download_excel():
    """Web上のデータをExcelでダウンロード"""
    inventory = Inventory.query.all()
    df = pd.DataFrame([inv.to_dict() for inv in inventory])

    output = io.BytesIO()
    df.to_excel(output, index=False)
    output.seek(0)

    return send_file(output, mimetype='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet',
                     as_attachment=True, download_name='inventory.xlsx')