The ar_dni function is a specialized tool within the mock-jutsu library designed to generate realistic Argentinian Documento Nacional de Identidad (DNI) numbers. As a core component of the IntlIDs category, this function simplifies the process of creating localized test data for applications targeting the South American market. By producing strings of seven or eight digits, ar_dni ensures that developers have access to syntactically correct identifiers that mirror the identification system managed by the National Registry of Persons (RENAPER) in Argentina. This level of precision is vital for maintaining the integrity of testing environments that require regional accuracy.
Integrating ar_dni into your development workflow is seamless, whether you are working in a Python environment, using a command-line interface, or performing performance testing with JMeter. For instance, a simple call to jutsu.generate('ar_dni') within a Python script provides immediate access to high-quality mock data. This flexibility allows engineering teams to populate databases, simulate user registrations, and validate form input logic without the ethical or legal risks associated with using real citizen data. The function adheres to the standard numerical format used across the country, ensuring that the generated values pass basic length and character validation checks common in both front-end and back-end systems.
Beyond simple generation, the ar_dni function serves critical roles in various testing scenarios. QA engineers can leverage this tool to verify that database schemas correctly handle varying lengths of identification numbers, as older DNI versions may contain seven digits while newer ones contain eight. Furthermore, using mock-jutsu for generating test data facilitates robust edge-case testing, such as ensuring that UI masks, data transformation pipelines, and search filters function correctly across different regional formats. This attention to detail is essential for building inclusive software that respects international identity standards and provides a smooth user experience.
Ultimately, the primary benefit of using ar_dni within the mock-jutsu ecosystem is the significant reduction in manual data entry and the elimination of "dummy" data that lacks structural integrity. By automating the creation of Argentinian DNI numbers, developers can focus on core logic and feature development rather than manual data curation. Whether you are building a fintech platform, a government portal, or a retail application, having access to reliable, standardized mock data ensures that your software is production-ready and capable of handling real-world Argentinian user profiles with precision and security.
mockjutsu generate ar_dnimockjutsu bulk ar_dni --count 10mockjutsu export ar_dni --count 10 --format jsonmockjutsu export ar_dni --count 10 --format csvmockjutsu export ar_dni --count 10 --format sql# --mask: regulation-compliant output (PCI DSS / GDPR / KVKK)mockjutsu generate ar_dni --maskmockjutsu bulk ar_dni --count 5 --maskfrom mockjutsu import jutsujutsu.generate('ar_dni')jutsu.bulk('ar_dni', count=10)jutsu.template(['ar_dni'], count=5)# mask=True: regulation-compliant outputjutsu.generate('ar_dni', mask=True)jutsu.bulk('ar_dni', count=5, mask=True)${__mockjutsu_intl_ids(ar_dni)}# JMeter Function: __mockjutsu_intl_ids# Parameter 1: ar_dni# Parameter 2: (not required for this function)# Add 'mask' keyword to get a regulation-compliant masked value${__mockjutsu_intl_ids(ar_dni,mask)}GET /generate/ar_dni# → {"type":"ar_dni","result":"...","status":"ok"}GET /bulk/ar_dni?count=10POST /template {"types":["ar_dni"],"count":1}# mask=true: regulation-compliant outputGET /generate/ar_dni?mask=trueGET /bulk/ar_dni?count=5&mask=true| Parameter | Values | Description |
|---|---|---|
| --mask | true | false | Return a regulation-compliant masked value (PCI DSS, GDPR, KVKK…) |