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Ecommerce Report Walkthrough ​

After this page, you can design a real data source for an ecommerce app and understand exactly what this package can do now versus what is planned for export.

Scenario ​

  • 1000 users
  • each user has 10 orders
  • each order amount is 300 taka

Expected totals:

  • total orders = 1000 * 10 = 10,000
  • total revenue = 10,000 * 300 = 3,000,000 taka

What works today ​

Current package phase supports:

  • registering data sources
  • defining safe columns/fields
  • exposing metadata through API

Current package phase does not yet include:

  • preview/run query execution endpoints
  • CSV export
  • XLS/XLSX export

Step 1: Design your source fields ​

Use only trusted fields needed for reporting.

php
new EloquentDataSource(
    key: 'orders',
    label: 'Orders',
    model: Order::class,
    fields: [
        Field::integer('user_id')
            ->label('User')
            ->column('orders.user_id')
            ->groupable()
            ->filterable([FilterOperator::Eq, FilterOperator::In]),
        Field::decimal('total_amount')
            ->label('Order Amount')
            ->column('orders.total_amount')
            ->sortable()
            ->groupable()
            ->filterable([FilterOperator::Eq, FilterOperator::Gt, FilterOperator::Between])
            ->aggregates([AggregateFunction::Sum, AggregateFunction::Avg]),
        Field::dateTime('created_at')
            ->label('Order Date')
            ->column('orders.created_at')
            ->sortable()
            ->filterable([FilterOperator::Gte, FilterOperator::Lte]),
    ],
);

Step 2: Register the data source ​

php
$reportBuilder->registerDataSource(new OrdersDataSource());

Step 3: Verify metadata ​

bash
curl http://your-app.test/report-builder/sources/orders

You should see field metadata for user_id, total_amount, and created_at.

How export will work (planned flow) ​

mermaid
flowchart LR
    UI["FrontendUser"] -->|"SelectSavedReport + format(csv/xlsx)"| ExportAPI["ReportExportController(planned)"]
    ExportAPI --> Service["ExportService(planned)"]
    Service --> Engine["QueryEngine(planned)"]
    Engine --> Dataset["DatasetRows"]
    Dataset --> CsvExporter["CsvExporter(planned)"]
    Dataset --> ExcelExporter["ExcelExporter(planned)"]
    CsvExporter --> Storage["StorageDisk"]
    ExcelExporter --> Storage
    Storage --> UI

Practical note for your example ​

For your ecommerce dataset, the desired report is:

  • group by user_id
  • aggregate sum(total_amount) as total spend per user

When preview/run/export phase lands, this same source definition will power that output safely.