data-analytics template

odf init my-project --template data-analytics

default (Item/Items/SQLite) plus one @Analytics @Task: SummarizeItems, which aggregates the repository into a JSON report. Analytics is consumption-oriented — it reads repository data and produces a report artifact, rather than ingesting one the way data-engineering/research do.

Layout

my-project/
├── config.toml
├── app/
│   ├── __init__.py
│   ├── analytics.py      # SummarizeItems (@Analytics @Task)
│   ├── entities.py       # Item
│   ├── repositories.py   # Items(SQLite)
│   └── storages.py       # SQLite
└── reports/               # starts empty — SummarizeItems writes here

What's added

# app/analytics.py
@Analytics
@Task
class SummarizeItems:
    def execute(self) -> dict:
        all_items = self.items.all()
        summary = {
            "item_count": len(all_items),
            "total_quantity": sum(item.quantity for item in all_items),
        }
        ...  # written to reports/summary.json
        return summary

The report path comes from [task.summarize-items] report-path in config (default "reports/summary.json"). @Analytics marks it for the Layer the UI groups analytics-style tasks under; @Task is what makes it executable from the UI's Execute action or the MCP execute_task tool.

Run it

odf runUI running at http://127.0.0.1:4747

Trigger SummarizeItems from the UI (or execute_task over MCP) and check reports/summary.json.