In the evolving landscape of telecommunications and mobile application development, generating high-fidelity test data is a prerequisite for robust software quality assurance. The mock-jutsu library addresses this critical need through its specialized telecom module, specifically featuring the imei2 function. This utility generates a realistic International Mobile Equipment Identity (IMEI) number formatted with hyphens to match the standard display often found in hardware documentation and user interfaces. By producing strings such as 49-015420-323751-8, the imei2 function ensures that developers can simulate device-specific interactions with both visual accuracy and structural integrity.
Each mock data string produced by the imei2 function adheres to the rigorous international standards governing mobile device identification. The generated output follows the Type Allocation Code (TAC) and serial number structure, concluding with a valid check digit calculated via the Luhn algorithm. This level of precision is critical when using test data to validate database constraints or backend logic that requires checksum verification. Because mock-jutsu prioritizes algorithmic accuracy, the generated values are indistinguishable from real-world identifiers, allowing engineering teams to bypass the privacy risks and ethical concerns associated with using actual customer device information during the development lifecycle.
For engineers focused on performance testing and integration, the imei2 function provides significant versatility across multiple environments. Whether you are automating a Python script using jutsu.generate('imei2'), executing quick terminal commands via the CLI, or conducting large-scale load testing in Apache JMeter using the custom function syntax, the library ensures consistent and reliable results. This cross-platform flexibility makes it an essential tool for testing scenarios involving subscriber management systems, telecommunications billing platforms, and mobile device management (MDM) software where hyphenated IMEI formats are the expected input standard.
Ultimately, incorporating the imei2 function into your CI/CD pipeline enhances the overall reliability of your automated test suites. By providing structured, valid, and hyphenated mock data, mock-jutsu empowers developers to identify edge cases in string parsing and data storage early in the development process. This proactive approach to data generation reduces the friction of manual data entry and mitigates the risk of system failures caused by improperly formatted device identifiers, ensuring that your telecom-focused applications are production-ready and fully compliant with industry data standards.
mockjutsu generate imei2mockjutsu bulk imei2 --count 10mockjutsu export imei2 --count 10 --format jsonmockjutsu export imei2 --count 10 --format csvmockjutsu export imei2 --count 10 --format sql# --mask: regulation-compliant output (PCI DSS / GDPR / KVKK)mockjutsu generate imei2 --maskmockjutsu bulk imei2 --count 5 --maskfrom mockjutsu import jutsujutsu.generate('imei2')jutsu.bulk('imei2', count=10)jutsu.template(['imei2'], count=5)# mask=True: regulation-compliant outputjutsu.generate('imei2', mask=True)jutsu.bulk('imei2', count=5, mask=True)${__mockjutsu_telecom(imei2)}# JMeter Function: __mockjutsu_telecom# Parameter 1: imei2# Parameter 2: (not required for this function)# Add 'mask' keyword to get a regulation-compliant masked value${__mockjutsu_telecom(imei2,mask)}GET /generate/imei2# → {"type":"imei2","result":"...","status":"ok"}GET /bulk/imei2?count=10POST /template {"types":["imei2"],"count":1}# mask=true: regulation-compliant outputGET /generate/imei2?mask=trueGET /bulk/imei2?count=5&mask=true| Parameter | Values | Description |
|---|---|---|
| --mask | true | false | Return a regulation-compliant masked value (PCI DSS, GDPR, KVKK…) |