When developing applications for the Japanese market, handling sensitive identification data like the Individual Number—commonly known as "My Number"—requires precision and care. The mock-jutsu library provides a dedicated function, jp_in, to generate realistic, synthetically created Japanese Individual Numbers. This function creates a 12-digit string that adheres strictly to the official structural requirements established by Japanese authorities. By using jp_in, developers can populate their databases with high-quality mock data that mimics real-world identifiers without compromising actual personal information or violating privacy regulations like the My Number Act.
The technical integrity of the jp_in function lies in its implementation of the MOD-11 check digit algorithm. Each generated number is not just a random sequence of digits; it includes a calculated check digit as the final character, ensuring that the entire string passes the standard validation logic used by government and financial systems. This level of detail makes mock-jutsu an essential tool for testing data entry forms, backend validation scripts, and API endpoints that expect a valid My Number format. Whether you are performing unit tests in a Python environment using jutsu.generate('jp_in') or executing high-volume performance tests in JMeter with the ${__mockjutsu(jp_in,)} syntax, the generated test data remains consistent, valid, and reliable.
Beyond simple validation, the jp_in function offers significant benefits for edge-case testing and UI development. Developers can use this mock data to verify how their systems handle 12-digit inputs, ensuring that database schemas are correctly sized and that frontend masks or formatting logic display the numbers accurately. From a CLI perspective, running the command mockjutsu generate jp_in allows for quick data generation during manual debugging sessions or shell scripting. By integrating jp_in into your CI/CD pipelines, you ensure that your internationalized applications are robust enough to handle Japanese identification standards from the initial build.
Ultimately, mock-jutsu streamlines the development lifecycle by removing the friction associated with sourcing compliant test data. The jp_in function specifically addresses the complexities of Japanese administrative identifiers, allowing teams to focus on building features rather than manual data entry. Whether you are building a fintech application, a human resources management system, or a localized government portal, the ability to generate valid, MOD-11 compliant mock data ensures that your software is production-ready and fully compatible with Japanese regulatory standards.
mockjutsu generate jp_inmockjutsu bulk jp_in --count 10mockjutsu export jp_in --count 10 --format jsonmockjutsu export jp_in --count 10 --format csvmockjutsu export jp_in --count 10 --format sql# --mask: regulation-compliant output (PCI DSS / GDPR / KVKK)mockjutsu generate jp_in --maskmockjutsu bulk jp_in --count 5 --maskfrom mockjutsu import jutsujutsu.generate('jp_in')jutsu.bulk('jp_in', count=10)jutsu.template(['jp_in'], count=5)# mask=True: regulation-compliant outputjutsu.generate('jp_in', mask=True)jutsu.bulk('jp_in', count=5, mask=True)${__mockjutsu_intl_ids(jp_in)}# JMeter Function: __mockjutsu_intl_ids# Parameter 1: jp_in# Parameter 2: (not required for this function)# Add 'mask' keyword to get a regulation-compliant masked value${__mockjutsu_intl_ids(jp_in,mask)}GET /generate/jp_in# → {"type":"jp_in","result":"...","status":"ok"}GET /bulk/jp_in?count=10POST /template {"types":["jp_in"],"count":1}# mask=true: regulation-compliant outputGET /generate/jp_in?mask=trueGET /bulk/jp_in?count=5&mask=true| Parameter | Values | Description |
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| --mask | true | false | Return a regulation-compliant masked value (PCI DSS, GDPR, KVKK…) |