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Receipt Parsing API

Extract JSON data from receipt images and PDFs using your schema.

Try It Live

Extract structured JSON from the preloaded sample, then switch to your own document when you are ready.

Document

sample-receipt.jpg

Uploaded document

Add fields, nested object fields, and lists of objects to build your schema.

List Item Fields

Ready to try it on your own document?

We will save your file and schema so you can pick up where you left off after sign-in.

Use via API

Drop the same schema into your stack. Pick a language tab to copy a request that uses the sample document and starter schema.

Receipt Parsing API in TypeScript

Type-safe TypeScript example using fetch and a JSON schema. Drop into Next.js, Express, or any Node runtime.

typescript
import { readFileSync } from 'node:fs';

const schema = {
  "type": "object",
  "properties": {
    "restaurant_name": {
      "type": "string"
    },
    "order_type": {
      "type": "string",
      "description": "Pickup or dine in"
    },
    "items": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "name": {
            "type": "string"
          },
          "quantity": {
            "type": "number"
          },
          "price_per_item": {
            "type": "number",
            "description": "Price per each item, for example \"$5.00 each\""
          },
          "additional_charge": {
            "type": "number",
            "description": "Added in ()"
          },
          "total_per_item": {
            "type": "number"
          }
        },
        "required": [
          "name",
          "quantity",
          "price_per_item",
          "additional_charge",
          "total_per_item"
        ]
      }
    },
    "subtotal": {
      "type": "number"
    },
    "sales_tax": {
      "type": "number"
    },
    "total": {
      "type": "number"
    },
    "cash": {
      "type": "number"
    },
    "change": {
      "type": "number"
    }
  },
  "required": [
    "restaurant_name",
    "order_type",
    "items",
    "subtotal",
    "sales_tax",
    "total",
    "cash",
    "change"
  ]
};

const file = new File([readFileSync('sample-receipt.jpg')], 'sample-receipt.jpg', {
  type: 'image/jpeg',
});

const formData = new FormData();
formData.set('file', file);
formData.set('schema', JSON.stringify(schema));

const response = await fetch('https://api.structpdf.com/v1/extract', {
  method: 'POST',
  headers: {
    Authorization: `Bearer ${process.env.STRUCTPDF_API_KEY}`,
  },
  body: formData,
});

const data = await response.json();
console.log(data);

Receipt Parsing API in JavaScript

Plain JavaScript / Node.js example using fetch. Works in Node 18+ and modern serverless runtimes.

javascript
const fs = require('node:fs');

const schema = {
  "type": "object",
  "properties": {
    "restaurant_name": {
      "type": "string"
    },
    "order_type": {
      "type": "string",
      "description": "Pickup or dine in"
    },
    "items": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "name": {
            "type": "string"
          },
          "quantity": {
            "type": "number"
          },
          "price_per_item": {
            "type": "number",
            "description": "Price per each item, for example \"$5.00 each\""
          },
          "additional_charge": {
            "type": "number",
            "description": "Added in ()"
          },
          "total_per_item": {
            "type": "number"
          }
        },
        "required": [
          "name",
          "quantity",
          "price_per_item",
          "additional_charge",
          "total_per_item"
        ]
      }
    },
    "subtotal": {
      "type": "number"
    },
    "sales_tax": {
      "type": "number"
    },
    "total": {
      "type": "number"
    },
    "cash": {
      "type": "number"
    },
    "change": {
      "type": "number"
    }
  },
  "required": [
    "restaurant_name",
    "order_type",
    "items",
    "subtotal",
    "sales_tax",
    "total",
    "cash",
    "change"
  ]
};

const file = new File([fs.readFileSync('sample-receipt.jpg')], 'sample-receipt.jpg', {
  type: 'image/jpeg',
});

const formData = new FormData();
formData.set('file', file);
formData.set('schema', JSON.stringify(schema));

const response = await fetch('https://api.structpdf.com/v1/extract', {
  method: 'POST',
  headers: {
    Authorization: `Bearer ${process.env.STRUCTPDF_API_KEY}`,
  },
  body: formData,
});

const data = await response.json();
console.log(data);

Receipt Parsing API in Python

Python example using requests. Works on Python 3.8+ and integrates cleanly with Django, FastAPI, and ETL pipelines.

python
import json
import os
import requests

schema = {
  "type": "object",
  "properties": {
    "restaurant_name": {
      "type": "string"
    },
    "order_type": {
      "type": "string",
      "description": "Pickup or dine in"
    },
    "items": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "name": {
            "type": "string"
          },
          "quantity": {
            "type": "number"
          },
          "price_per_item": {
            "type": "number",
            "description": "Price per each item, for example \"$5.00 each\""
          },
          "additional_charge": {
            "type": "number",
            "description": "Added in ()"
          },
          "total_per_item": {
            "type": "number"
          }
        },
        "required": [
          "name",
          "quantity",
          "price_per_item",
          "additional_charge",
          "total_per_item"
        ]
      }
    },
    "subtotal": {
      "type": "number"
    },
    "sales_tax": {
      "type": "number"
    },
    "total": {
      "type": "number"
    },
    "cash": {
      "type": "number"
    },
    "change": {
      "type": "number"
    }
  },
  "required": [
    "restaurant_name",
    "order_type",
    "items",
    "subtotal",
    "sales_tax",
    "total",
    "cash",
    "change"
  ]
}

with open("sample-receipt.jpg", "rb") as fh:
    response = requests.post(
        "https://api.structpdf.com/v1/extract",
        headers={"Authorization": f"Bearer {os.environ['STRUCTPDF_API_KEY']}"},
        files={"file": ("sample-receipt.jpg", fh, "image/jpeg")},
        data={"schema": json.dumps(schema)},
    )

response.raise_for_status()
print(response.json())

Receipt Parsing API in Java

Java example using HttpClient. Works on Java 11+ and integrates with Spring Boot or any JVM service.

java
import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.UUID;

public class ExtractExample {
  public static void main(String[] args) throws Exception {
    String schema = "{\"type\":\"object\",\"properties\":{\"restaurant_name\":{\"type\":\"string\"},\"order_type\":{\"type\":\"string\",\"description\":\"Pickup or dine in\"},\"items\":{\"type\":\"array\",\"items\":{\"type\":\"object\",\"properties\":{\"name\":{\"type\":\"string\"},\"quantity\":{\"type\":\"number\"},\"price_per_item\":{\"type\":\"number\",\"description\":\"Price per each item, for example \\"$5.00 each\\"\"},\"additional_charge\":{\"type\":\"number\",\"description\":\"Added in ()\"},\"total_per_item\":{\"type\":\"number\"}},\"required\":[\"name\",\"quantity\",\"price_per_item\",\"additional_charge\",\"total_per_item\"]}},\"subtotal\":{\"type\":\"number\"},\"sales_tax\":{\"type\":\"number\"},\"total\":{\"type\":\"number\"},\"cash\":{\"type\":\"number\"},\"change\":{\"type\":\"number\"}},\"required\":[\"restaurant_name\",\"order_type\",\"items\",\"subtotal\",\"sales_tax\",\"total\",\"cash\",\"change\"]}";
    Path file = Path.of("sample-receipt.jpg");
    String boundary = UUID.randomUUID().toString();
    String CRLF = "\r\n";

    var body = new java.io.ByteArrayOutputStream();
    body.writeBytes(("--" + boundary + CRLF
        + "Content-Disposition: form-data; name=\"schema\"" + CRLF + CRLF
        + schema + CRLF).getBytes());
    body.writeBytes(("--" + boundary + CRLF
        + "Content-Disposition: form-data; name=\"file\"; filename=\"sample-receipt.jpg\"" + CRLF
        + "Content-Type: image/jpeg" + CRLF + CRLF).getBytes());
    body.writeBytes(Files.readAllBytes(file));
    body.writeBytes((CRLF + "--" + boundary + "--" + CRLF).getBytes());

    HttpRequest request = HttpRequest.newBuilder()
        .uri(URI.create("https://api.structpdf.com/v1/extract"))
        .header("Authorization", "Bearer " + System.getenv("STRUCTPDF_API_KEY"))
        .header("Content-Type", "multipart/form-data; boundary=" + boundary)
        .POST(HttpRequest.BodyPublishers.ofByteArray(body.toByteArray()))
        .build();

    HttpResponse<String> response = HttpClient.newHttpClient()
        .send(request, HttpResponse.BodyHandlers.ofString());
    System.out.println(response.body());
  }
}

Receipt Parsing API in Go

Go example using net/http. Idiomatic Go HTTP client suitable for microservices and serverless functions.

go
package main

import (
	"bytes"
	"fmt"
	"io"
	"mime/multipart"
	"net/http"
	"net/textproto"
	"os"
)

func main() {
	schema := `{"type":"object","properties":{"restaurant_name":{"type":"string"},"order_type":{"type":"string","description":"Pickup or dine in"},"items":{"type":"array","items":{"type":"object","properties":{"name":{"type":"string"},"quantity":{"type":"number"},"price_per_item":{"type":"number","description":"Price per each item, for example \"$5.00 each\""},"additional_charge":{"type":"number","description":"Added in ()"},"total_per_item":{"type":"number"}},"required":["name","quantity","price_per_item","additional_charge","total_per_item"]}},"subtotal":{"type":"number"},"sales_tax":{"type":"number"},"total":{"type":"number"},"cash":{"type":"number"},"change":{"type":"number"}},"required":["restaurant_name","order_type","items","subtotal","sales_tax","total","cash","change"]}`

	file, err := os.Open("sample-receipt.jpg")
	if err != nil {
		panic(err)
	}
	defer file.Close()

	var body bytes.Buffer
	writer := multipart.NewWriter(&body)
	_ = writer.WriteField("schema", schema)

	header := make(textproto.MIMEHeader)
	header.Set("Content-Disposition", "form-data; name=\"file\"; filename=\"sample-receipt.jpg\"")
	header.Set("Content-Type", "image/jpeg")
	part, err := writer.CreatePart(header)
	if err != nil {
		panic(err)
	}
	if _, err := io.Copy(part, file); err != nil {
		panic(err)
	}
	writer.Close()

	req, err := http.NewRequest("POST", "https://api.structpdf.com/v1/extract", &body)
	if err != nil {
		panic(err)
	}
	req.Header.Set("Authorization", "Bearer "+os.Getenv("STRUCTPDF_API_KEY"))
	req.Header.Set("Content-Type", writer.FormDataContentType())

	resp, err := http.DefaultClient.Do(req)
	if err != nil {
		panic(err)
	}
	defer resp.Body.Close()

	out, _ := io.ReadAll(resp.Body)
	fmt.Println(string(out))
}

Frequently Asked Questions

What does the Receipt Parsing API return?

Send a receipt image or PDF plus a JSON schema and get back structured JSON shaped exactly like your schema, alongside per-field findings, snippets, and page references that explain where each value came from.

Which file formats are supported?

PDFs and common image formats all flow through the same extraction endpoint, so mobile photos, emailed receipts, and exported PDFs can be ingested in one call.

How is usage priced?

Extractions are billed per page in credits. There is no separate parse charge before extraction — the credit you see is the credit you pay.

Can I customize the fields I extract?

Yes. Edit the schema in the playground or build it visually in the Schema Builder. Save it once and reuse it in production via schema_id, including nested objects and line-item arrays such as purchased items.

Do I have to sign up to try it?

No. Run the demo on a sample receipt without an account. When you upload your own receipt, we ask you to sign in with Google or a magic link to run your first extraction. Your file and schema are saved automatically so you pick up where you left off.

API ReferencePricingCreate Free Account

Pricing

Start on the free plan, then continue with Pay-As-You-Go or a subscription as your volume grows.

Free
Get started with 250 credits every month
Free
Get Started Free
  • 250 credits/month
  • No credit card required
  • Schema builder (save requires upgrade)
Starter
For getting started and light usage
$19.00/month
Get Started with Starter
  • Up to 1,000 extractions
  • $0.019 per credit
  • 1,000 credits
  • Save and reuse extraction schemas
Popular
Developer
For individual developers and small projects
$39.00/month
Get Started with Developer
  • Up to 2,500 extractions
  • $0.0156 per credit
  • 2,500 credits
  • Save and reuse extraction schemas
Pro
For professional teams and heavier usage
$99.00/month
Get Started with Pro
  • Up to 8,000 extractions
  • $0.0124 per credit
  • 8,000 credits
  • Save and reuse extraction schemas