Refund and Return Receipt OCR

Understand the printed transaction first

Preserve explicit negative amounts and distinguish refund evidence from an original purchase. Review result issues rather than coercing an unusual signed amount into a positive sale. Start by checking whether the document is a completed payment, an estimate, an order confirmation or an account summary. A successful read of the header is not enough: the amount beside the final payable label and the boundaries of individual item rows are the evidence that makes a useful expense record.

Extract receipt fields without inventing a breakdown

Use the receipt OCR API for merchant_name, date, time, currency, total_amount, tax_amount and items. Each item exposes name, quantity and price; price is the whole-row amount, not necessarily a unit price. The public schema has no dedicated tender, tip, loyalty, QR payload or receipt-number object. Keep the source document when those details matter. For implementation details, see the Python receipt integration.

From receipt image to an expense record

Read a receipt from a Python backend

Submit one receipt image using the standard endpoint. Keep the API key server-side and examine quality indicators before mapping the result to an expense. The sample does not claim a live test on this merchant.

import base64
import os
import requests

with open("receipt.jpg", "rb") as source:
    encoded = base64.b64encode(source.read()).decode("ascii")

response = requests.post(
    "https://api.structocr.com/v1/receipt",
    headers={"x-api-key": os.environ["STRUCTOCR_API_KEY"]},
    json={"img": encoded},
    timeout=60,
)
response.raise_for_status()
result = response.json()
if not result.get("success"):
    raise RuntimeError("Extraction was not successful; inspect the response securely")
data = result.get("data") or {}
needs_review = (
    not data.get("is_valid")
    or data.get("status") != "complete"
    or bool(data.get("issues"))
    or data.get("confidence") == "low"
)
# Persist through your own storage layer; avoid logging receipt contents.
print({"needs_review": needs_review, "item_count": len(data.get("items") or [])})

{
  "success": true,
  "data": {
    "response_version": 2,
    "is_valid": true,
    "merchant_name": "Example Merchant",
    "date": "2026-09-01",
    "time": "12:30",
    "currency": "USD",
    "total_amount": 12,
    "tax_amount": 1,
    "items": [
      {
        "name": "EXAMPLE PURCHASE",
        "quantity": 2,
        "price": "8.00"
      },
      {
        "name": "EXAMPLE CHARGE",
        "quantity": 1,
        "price": "3.00"
      }
    ],
    "confidence": "high",
    "validation_error": null,
    "status": "complete",
    "issues": []
  }
}