The in_epic function is a specialised tool within the mock-jutsu library designed to generate realistic test data for Indian Voter ID cards, officially known as the Elector’s Photo Identity Card (EPIC). In the context of software development and quality assurance, having access to validly formatted identifiers is crucial for building robust applications that serve the Indian market. By using mock-jutsu, developers can instantly produce strings that mirror the official standard mandated by the Election Commission of India, ensuring that validation logic and database constraints are tested against accurate data structures without compromising real citizen information.
Technically, the in_epic generator follows a strict alphanumeric format consisting of three uppercase letters followed by a seven-digit sequence. This specific 10-character structure is the modern standard for Voter IDs in India. Whether you are working in a Python environment using jutsu.generate('in_epic'), executing commands via the CLI, or conducting performance testing in JMeter with the mock-jutsu plugin, the function provides a seamless way to inject high-quality mock data into your workflow. This versatility makes it an essential asset for engineering teams focused on internationalisation and regional compliance across various platforms.
Utilising in_epic offers significant benefits for several testing scenarios, particularly those involving Know Your Customer (KYC) workflows, financial service registrations, and government-tech portals. Because the generated mock data is synthetic, it allows teams to remain compliant with data protection regulations such as the Digital Personal Data Protection (DPDP) Act, as no actual PII (Personally Identifiable Information) is used during the development lifecycle. This mitigates the risk of data breaches in staging environments while providing the necessary volume of test data for stress testing and UI layout verification.
Beyond simple data generation, mock-jutsu ensures that the in_epic function integrates effortlessly into automated CI/CD pipelines. Developers no longer need to manually curate spreadsheets of dummy IDs or write complex regex-based scripts to simulate Indian identifiers. By automating the creation of these IDs, the library reduces manual overhead and accelerates the time-to-market for applications requiring regional identity verification. This focus on developer experience and data integrity makes mock-jutsu a premier choice for modern software engineering teams working on globalised applications.
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…) |