In the realm of modern software development and quality assurance, generating realistic test data is a critical step for ensuring application reliability and compliance. The mock-jutsu library provides a specialized function called il_idnr, specifically designed for developers and testers who need to simulate Israeli identity numbers, known locally as Mispar Zehut. This function is a core component of the IntlIDs category, offering a seamless way to generate valid 9-digit identifiers that adhere to the official Israeli numbering standards. By utilizing il_idnr, engineering teams can populate their staging environments with high-quality mock data without the legal or ethical privacy risks associated with using real personal information.
The technical foundation of the il_idnr function lies in its strict adherence to the Luhn algorithm, also known as the modulus 10 check. Each generated ID consists of nine digits, where the final digit serves as a checksum to validate the preceding eight. This level of precision is essential for testing systems that implement rigorous data entry validation. Whether you are building a government portal, a financial services application, or a localized healthcare platform, mock-jutsu ensures that your test data will pass through front-end and back-end validation layers exactly like a genuine Israeli ID would. This prevents false negatives during automated testing and ensures that the logic governing ID verification is thoroughly vetted.
Integration is a core strength of the mock-jutsu ecosystem, allowing the il_idnr function to be invoked through multiple interfaces depending on the specific developer workflow. For quick prototyping or shell scripting, the command-line interface allows for rapid generation of IDs. Python developers can integrate the library directly into their unit tests or data-seeding scripts using the standard jutsu.generate syntax. Furthermore, for performance and load testing, the library includes JMeter support, allowing for the dynamic injection of unique Israeli IDs into high-concurrency scenarios. This multi-platform flexibility makes it an indispensable tool for modern DevOps pipelines and continuous integration environments.
Beyond simple validation, the il_idnr function supports a wide range of complex testing scenarios. It is particularly useful for database seeding, where thousands of unique, valid records are required to stress-test search indexing and query performance. It also simplifies the process of testing edge cases in form submission logic and API endpoints that require regional ID verification. By streamlining the creation of compliant mock data, mock-jutsu empowers developers to focus on building robust features rather than manual data entry, ultimately accelerating the software development lifecycle and improving overall product quality.
mockjutsu generate il_idnrmockjutsu bulk il_idnr --count 10mockjutsu export il_idnr --count 10 --format jsonmockjutsu export il_idnr --count 10 --format csvmockjutsu export il_idnr --count 10 --format sql# --mask: regulation-compliant output (PCI DSS / GDPR / KVKK)mockjutsu generate il_idnr --maskmockjutsu bulk il_idnr --count 5 --maskfrom mockjutsu import jutsujutsu.generate('il_idnr')jutsu.bulk('il_idnr', count=10)jutsu.template(['il_idnr'], count=5)# mask=True: regulation-compliant outputjutsu.generate('il_idnr', mask=True)jutsu.bulk('il_idnr', count=5, mask=True)${__mockjutsu_intl_ids(il_idnr)}# JMeter Function: __mockjutsu_intl_ids# Parameter 1: il_idnr# Parameter 2: (not required for this function)# Add 'mask' keyword to get a regulation-compliant masked value${__mockjutsu_intl_ids(il_idnr,mask)}GET /generate/il_idnr# → {"type":"il_idnr","result":"...","status":"ok"}GET /bulk/il_idnr?count=10POST /template {"types":["il_idnr"],"count":1}# mask=true: regulation-compliant outputGET /generate/il_idnr?mask=trueGET /bulk/il_idnr?count=5&mask=true| Parameter | Values | Description |
|---|---|---|
| --mask | true | false | Return a regulation-compliant masked value (PCI DSS, GDPR, KVKK…) |