I have a folder with multiple JSON files. Each file represents one month of orders.

Each JSON has this structure:

{ "month": "2024-07", "orders": [ { "order_id": "ORD-001", "user": { "name": "Lio Messi", "country": "AR" }, "items": [ { "product_id": "PROD-7", "name": "Soccer Ball", "qty": 2, "unit_price": 49.99 } ], "status": "completed", "created_at": "2022-12-18T12:30:00Z" } ] }

Write a Python script that:

1. Reads all .json files from a given folder path
2. Filters orders from Q3 2024 (July, August, September)
3. Computes the total spent per user_id (sum of qty by unit_price for completed orders)
4. Prints users whose total exceeds $500, sorted descending
5. Exports the result to a CSV file named q3_top_users.csv

Use pathlib and the standard csv module. No dependencies.

You describe the shape of the data, not the data itself.

The AI writes a reliable, auditable, reusable program.

You run it on your real files.