The in_epic function is a specialized utility within the mock-jutsu library designed to generate realistic Indian Voter ID numbers, commonly referred to as the Electoral Photo Identity Card (EPIC). In the realm of global application development, producing high-quality mock data that adheres to specific regional standards is essential for robust software verification. By utilizing the in_epic generator, developers can instantly create identifiers that mirror the official format mandated by the Election Commission of India, ensuring that validation logic remains accurate during the early stages of the development lifecycle.
Technically, the in_epic function produces a ten-character alphanumeric string consisting of three uppercase letters followed by a seven-digit numerical sequence, such as ABC1234567. This specific structure is the standard for modern EPIC identifiers across India. When generating test data with mock-jutsu, the library ensures that every output follows this strict pattern, which is vital for testing regular expression (regex) filters, database schema constraints, and front-end input masks. Whether you are building a government-tech portal or a financial services application requiring KYC verification, having access to predictable yet randomized identifiers helps maintain data integrity throughout your testing environment.
Integration is seamless across various workflows, making mock-jutsu a versatile choice for modern DevOps pipelines. Python developers can invoke the generator using the jutsu.generate('in_epic') method, while performance testers can leverage the JMeter plugin with the ${__mockjutsu(in_epic,)} syntax. For quick localized testing or script-based automation, the CLI command mockjutsu generate in_epic provides immediate results. This multi-platform support allows teams to synchronize their test data strategies across different departments, from backend engineering to quality assurance, without needing to maintain separate data generation scripts.
Beyond simple string generation, using in_epic offers significant benefits in terms of security and compliance. By using synthetically generated mock data instead of real PII (Personally Identifiable Information), organizations can safeguard user privacy while still performing comprehensive stress tests and edge-case analysis. This approach minimizes the risk of data breaches in staging environments and accelerates the time-to-market by removing the hurdles associated with sourcing production-like datasets. With mock-jutsu, generating compliant Indian Voter IDs becomes a one-line task, empowering developers to focus on building features rather than manual data entry.
mockjutsu generate in_epicmockjutsu bulk in_epic --count 10mockjutsu export in_epic --count 10 --format jsonmockjutsu export in_epic --count 10 --format csvmockjutsu export in_epic --count 10 --format sql# --mask: regulation-compliant output (PCI DSS / GDPR / KVKK)mockjutsu generate in_epic --maskmockjutsu bulk in_epic --count 5 --maskfrom mockjutsu import jutsujutsu.generate('in_epic')jutsu.bulk('in_epic', count=10)jutsu.template(['in_epic'], count=5)# mask=True: regulation-compliant outputjutsu.generate('in_epic', mask=True)jutsu.bulk('in_epic', count=5, mask=True)${__mockjutsu_intl_ids(in_epic)}# JMeter Function: __mockjutsu_intl_ids# Parameter 1: in_epic# Parameter 2: (not required for this function)# Add 'mask' keyword to get a regulation-compliant masked value${__mockjutsu_intl_ids(in_epic,mask)}GET /generate/in_epic# → {"type":"in_epic","result":"...","status":"ok"}GET /bulk/in_epic?count=10POST /template {"types":["in_epic"],"count":1}# mask=true: regulation-compliant outputGET /generate/in_epic?mask=trueGET /bulk/in_epic?count=5&mask=true| Parameter | Values | Description |
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| --mask | true | false | Return a regulation-compliant masked value (PCI DSS, GDPR, KVKK…) |