개념 및 지식 허브
모의 데이터(Mock Data) 대량 생성기 (JSON, CSV, SQL)
모의 데이터(Mock Data) 대량 생성기 (JSON, CSV, SQL)
본 도구는 100% 클라이언트 환경(브라우저)에서 작동합니다. 소스 코드, 토큰, 기밀 데이터가 외부 서버로 절대 전송되지 않습니다.
핵심 아키텍처 및 수학 공식
JSON Schema Definition ➔ Iterative Loop (1 to N) ➔ Random Data Injection ➔ Output Blob
The engine parses your desired fields (e.g., 'First Name', 'Credit Card') and iterates through thousands of loops, pulling from local arrays to construct realistic JSON or CSV files instantly.
모범 사례 및 필수 지침
- Never Use Production Data Locally: Developers often download production database dumps to test local features. If their laptop is stolen, millions of user records are breached. Always use synthetic mock data.
- Test Extreme Edge Cases: Don't just generate standard 'John Smith' names. Configure the mock generator to include massive unicode strings, null fields, and negative integers to ensure your frontend UI doesn't crash.
- Use Relational Foreign Keys: If generating SQL inserts for multiple tables (e.g., Users and Orders), ensure the User IDs match the Foreign Keys in the Orders table, otherwise your database constraints will reject the import.
자주 묻는 질문 (FAQ)
Is the generated data truly random?
Yes, it uses mathematical pseudorandom number generators to pick dictionary items. The emails, phone numbers, and IP addresses generated do not belong to real people.
Can I generate SQL Insert statements?
Yes. In addition to JSON and CSV, advanced tools can wrap the mock data directly into `INSERT INTO table_name VALUES(...)` syntax, allowing you to instantly seed a MySQL or PostgreSQL database.
Why do I need mock data for UI design?
A UI card might look perfect with a 5 letter name, but break entirely when it receives a 25 letter name. Mock data allows frontend developers to test grid layouts against chaotic, real world text lengths.