Argentina DNI OCR Python SDK

Parsing Argentina DNI Challenges

Extracting data from Argentina's DNI (Documento Nacional de Identidad) presents unique challenges due to varying layout designs between different card versions. Standard OCR engines struggle to reliably extract critical, localized fields like the CUIL/CUIT or the Nro. de Trámite, which are often printed in small or varying fonts. Most importantly, manually parsing the Machine-Readable Zone (MRZ) on the back of the card to mathematically verify the document's authenticity is complex and adds significant engineering overhead.

Why StructOCR for Argentina

StructOCR is explicitly trained on a vast dataset of Argentine DNI cards, enabling unparalleled accuracy in id card parsing. Our Python SDK abstracts away the complexities of OCR, seamlessly extracting Spanish names, addresses, and local tax identifiers for enhanced kyc automation.

Common Use Cases in Latin America

• Digital Onboarding: Verify users for Fintech apps and digital wallets in Argentina by pre-filling DNI data in < 2 seconds.
• Government & Compliance: Automate the extraction of the Nro. de Trámite to instantly validate identity status with RENAPER databases.
• Pan-LatAm Expansion: Seamlessly process users across Mercosur and LATAM. Our unified Python SDK automatically detects and extracts data from neighboring documents, such as the Brazil CPF/RG or Chile RUN, without requiring any custom rules or new API endpoints.

Python SDK Integration

Install the SDK via pip: `pip install structocr`. The SDK automatically maps Argentina-specific fields (like CUIL and Nro. de Trámite) and parses the TD1 MRZ block.

Prerequisite: Python 3.6+ and `structocr` library installed.

from structocr import StructOCR

# 🔑 Need a key for Argentina? Get 200 free credits instantly:
# 👉 https://structocr.com/register
# Initialize with your API Key
client = StructOCR("YOUR_API_KEY_HERE")

def scan_argentina_id():
    # Note: Supports JPG, PNG, WebP (Max 4.5MB)
    image_path = "argentina_dni_front_back.jpg"

    try:
        print(f"Scanning {image_path}...")
        result = client.scan_national_id(image_path)

        if result.get('success'):
            data = result['data']
            print("✅ Argentina DNI Extraction Successful!")
            
            # Basic Identity
            print(f"Region:      {data.get('country_code')} (Ejemplar: {data.get('card_series')})")
            print(f"Name:        {data.get('given_names')} {data.get('surname')}")
            print(f"DNI Number:  {data.get('document_number')}")
            
            # Critical Local Fields
            print(f"CUIL/CUIT:   {data.get('personal_number')}")
            additional = data.get('additional_fields', {})
            print(f"Trámite No.: {additional.get('tramite_number', 'N/A')}")
            
            # Demographics
            print(f"DOB:         {data.get('date_of_birth')} ({data.get('sex')})")
            print(f"Address:     {data.get('address', 'Extracted from back')}")
            
            # Extract TD1 MRZ Data
            if additional.get('mrz_line_1'):
                print("\n🔍 MRZ Data Extracted & Validated:")
                print(f"Line 1: {additional.get('mrz_line_1')}")
            # ... (lines 2 & 3)
        else:
            print(f"❌ Extraction Failed: {result.get('error')}")

    except Exception as e:
        print(f"An error occurred: {e}")

if __name__ == "__main__":
    scan_argentina_id()

JSON Response Example

The SDK returns a Python dictionary containing the parsed visual data (VIZ), local Argentina fields, and the raw Machine-Readable Zone (MRZ) block.

{
  "success": true,
  "data": {
    "type": "national_id",
    "country_code": "ARG",
    "nationality": "ARGENTINA",
    "document_number": "30123456",
    "card_series": "A",
    "personal_number": "20-30123456-7",
    "surname": "GÓMEZ",
    "given_names": "LUCAS MARTÍN",
    "sex": "M",
    "date_of_birth": "1985-08-20",
    "place_of_birth": "CÓRDOBA",
    "address": "AV. COLÓN 456, CÓRDOBA",
    "date_of_issue": "2021-03-15",
    "date_of_expiry": "2036-03-15",
    "issuing_authority": "RENAPER",
    "additional_fields": {
      "tramite_number": "00123456789",
      "mrz_line_1": "IDARG30123456<2<<<<<<<<<<<<<<<",
      "mrz_line_2": "8508203M3603158ARG<<<<<<<<<<<6",
      "mrz_line_3": "GOMEZ<<LUCAS<MARTIN<<<<<<<<<<<"
    }
  }
}