API 모의 데이터 생성기

JSON 스키마에서 핀테크 API 모의 행을 생성하세요.

Schema (JSON)

Row Count

결과

[
  {
    "accountId": "f2ca3e5d-41cd-4654-8caa-8bad6b1c4fe7",
    "amount": 23450.93,
    "date": "2026-02-02"
  },
  {
    "accountId": "4505a6a3-e775-49e5-9b3a-c4f25f2bacbf",
    "amount": 38971.9,
    "date": "2025-10-04"
  },
  {
    "accountId": "595f54cb-96b7-415f-9c4c-378e99c1beec",
    "amount": 7300.68,
    "date": "2026-04-10"
  },
  {
    "accountId": "0688026f-b2ea-4d6d-b98a-d64aeaef5acd",
    "amount": 26209.33,
    "date": "2025-08-01"
  },
  {
    "accountId": "09fe3af0-2f0f-4eca-967f-a58c08b04a5a",
    "amount": 8926.13,
    "date": "2025-12-23"
  },
  {
    "accountId": "305648e7-075a-4d98-b4aa-0e11db74b0e7",
    "amount": 41920.84,
    "date": "2025-08-13"
  },
  {
    "accountId": "2b1eb6cb-496f-472c-951f-9294e05e79c4",
    "amount": 4418.33,
    "date": "2026-04-28"
  },
  {
    "accountId": "7970ec01-ad13-47f2-903a-0fa5da2d528f",
    "amount": 42396.17,
    "date": "2026-06-26"
  },
  {
    "accountId": "73986ac3-a2aa-4af4-aee3-4ddac25a9601",
    "amount": 38159.9,
    "date": "2025-11-24"
  },
  {
    "accountId": "ca555c25-5126-4440-b214-0abdc9d30868",
    "amount": 4469.91,
    "date": "2025-12-03"
  }
]

이 도구가 마음에 드시나요? portfolios.tools를 영원히 무료로 유지하는 데 도움을 주세요.

$1$50

작동 방식

Paste a JSON schema (object or array of objects) and set the number of mock rows to generate. The tool creates realistic random data matching your schema. Paste a JSON schema with fields date, symbol, side, quantity, price to generate realistic brokerage transaction rows for frontend prototyping without connecting to production APIs. Developers building portfolio dashboards use this to populate tables before wiring live brokerage OAuth feeds. Start from a minimal single object template and add fields incrementally while watching the field type summary to confirm heuristics classify each key as expected. Paste OpenAPI schema fragment or sample JSON response: generator builds typed mock objects with realistic finance field names. Paste OpenAPI path response schema fragment to generate mocks matching production contract keys exactly. Paste OpenAPI schema fragment or sample JSON response: generator builds typed mock objects with realistic finance field names. Paste OpenAPI path response schema fragment to generate mocks matching production contract keys exactly.

Review the generated mock data rows, field type summary, and any validation errors. Copy or download the JSON for API testing or prototyping. Increase row count up to 1,000 to stress test table virtualization and pagination components in your dashboard UI. Validate that your frontend handles null optional fields by temporarily removing keys from the schema template and regenerating rows. Use copy button output directly in Postman mock servers or MSW handlers to simulate latency free local API responses during sprint demos. Copy mock JSON into frontend tests or Storybook fixtures so portfolio widgets render without live API keys during development. Finance field presets include ticker, cusip, quantity, cost basis, and market value keys for portfolio apps. Use generated mocks in Storybook stories for portfolio dashboard components without backend. Copy mock JSON into frontend tests or Storybook fixtures so portfolio widgets render without live API keys during development. Finance field presets include ticker, cusip, quantity, cost basis, and market value keys for portfolio apps. Use generated mocks in Storybook stories for portfolio dashboard components without backend.

widgets render without live API keys during development. Finance field presets include ticker, cusip, quantity, cost basis, and market value keys for portfolio apps. Use generated mocks in Storybook stories for portfolio dashboard components without backend. Copy mock JSON into frontend tests or Storybook fixtures so portfolio widgets render without live API keys during development. Finance field presets include ticker, cusip, quantity, cost basis, and market value keys for portfolio apps. Use generated mocks in Storybook stories for portfolio dashboard components without backend.

입력값이 변경될 때마다 API 모의 데이터 생성기을(를) 사용하세요: 시장 변동, 새로운 기여금 또는 수정된 개인 가정 후. 소프트웨어 설치 없이 빠른 재실행을 위해 페이지를 북마크하세요.

단계별 안내

API 모의 데이터 생성기을(를) 열고 현재 입력값을 입력하세요.
계산된 출력과 요약 테이블을 검토하세요.
가정을 조정하고 시나리오를 나란히 비교하세요.

실전 예제

Example scenario for API Mock Data Generator: 1,000. Enter those values above to reproduce the walkthrough described in How it works.

한 번에 하나의 입력을 조정하여 민감도를 확인하세요. API 모의 데이터 생성기은(는) 즉시 업데이트되므로 행동하기 전에 낙관적 및 보수적 가정을 스트레스 테스트할 수 있습니다.

이 계산기를 사용할 때

Reach for API Mock Data Generator when generate mock fintech api rows from json schemas.. It suits quick what if analysis before trades, allocation changes, or plan updates.

결정이 세금, 유동성 또는 하나의 공식이 포착하는 것 이상의 다년 전망을 포괄할 때 관련 도구와 함께 사용하세요.

흔한 실수

입력 단위나 오래된 시장 가격을 확인하지 않고 출력을 복사하는 것은 API 모의 데이터 생성기에서 흔한 오류입니다. 행동하기 전에 티커, 백분율 및 날짜를 확인하세요.

단일 기준 시나리오만 실행하면 꼬리 위험을 무시합니다. 보수적 입력으로 스트레스 테스트하고 결정이 중요할 때 아래 나열된 관련 도구와 비교하세요.

공식

Seeded random generation produces deterministic output for same schema and row count. Random generation is not seeded across page reloads unless schema and row count match prior session inputs exactly. Unicode and emoji field values are not generated by default heuristics and remain literal template strings. Mock values are synthetic not market accurate: replace prices with fixture files for screenshot tests. Regenerate button creates new random samples while schema shape stays constant. Regenerated mocks use faker style variation while preserving JSON schema types for each field. Fixed random seed per session keeps mock data stable across hot reload during dev. Mock ticker symbols are fictional: replace with your watchlist symbols before screenshot tests. Mock values are synthetic not market accurate: replace prices with fixture files for screenshot tests. Regenerate button creates new random samples while schema shape stays constant. Regenerated mocks use faker style variation while preserving JSON schema types for each field. Fixed random seed per session keeps mock data stable across hot reload during dev.

제한 사항 및 가정

주요 용어

How are mock values generated: The tool parses a JSON schema template, infers field names and types, then generates realistic mock values: random UUIDs for ID fields, random names from a pool, financial amounts in appropriate ranges, dates within the past year, and ticker symbols.
What schema formats are supported: Schema must be a JSON object or array of objects.
모델 가정: Field name heuristics: id/uuid → UUID, email → email address, name → full name, date/time → ISO date, amount/price/balance → 10-50000, account → ACC-xxxxxx, symbol/ticker → AAPL/MSFT/etc.

대안 비교

Parse CSV exports with CSV to Financial JSON. Use those calculators when api mock data generator alone does not capture the full decision.

portfolios.tools의 내부 링크는 계산기 체인을 도와줍니다: 먼저 API 모의 데이터 생성기을(를) 실행한 다음, 아래 관련 섹션의 전문 도구로 엣지 케이스를 검증하세요.

FAQ

How are mock values generated?

The tool parses a JSON schema template, infers field names and types, then generates realistic mock values: random UUIDs for ID fields, random names from a pool, financial amounts in appropriate ranges, dates within the past year, and ticker symbols. Field name heuristics map id to UUID, email to sample addresses, amount to decimal dollars, and ticker to rotating symbols like AAPL and MSFT. Boolean fields named active, enabled, or isOpen receive true or false values suitable for form toggle testing. Currency code fields default to USD unless field names include eur or gbp substrings. Nested arrays of holdings generate multiple sample rows with tickers, quantities, and market values for table components. Nested portfolio object with holdings array generates realistic finance demo data for dashboard prototypes. Holdings array mock includes ticker quantity cost basis and market value for table UI tests. Nested arrays of holdings generate multiple sample rows with tickers, quantities, and market values for table components. Nested portfolio object with holdings array generates realistic finance demo data for dashboard prototypes. Holdings array mock includes ticker quantity cost basis and market value for table UI tests.

What schema formats are supported?

Schema must be a JSON object or array of objects. Nested objects are supported recursively. Arrays in the template are preserved as is. Fields not recognized by name heuristics get type based random values. Nested objects recurse depth first. Arrays in the template pass through unchanged while sibling fields receive generated values. Empty string fields in templates are replaced with generated samples rather than left blank. Invalid JSON paste shows validation errors before any rows generate so you can fix syntax quickly. Random seed is fixed per session so mocks stay stable across hot reload until you click regenerate. Random seed is fixed per session so mocks stay stable across hot reload until you click regenerate.

How does the tool decide what mock data to generate?

Field name heuristics: id/uuid → UUID, email → email address, name → full name, date/time → ISO date, amount/price/balance → 10-50000, account → ACC-xxxxxx, symbol/ticker → AAPL/MSFT/etc. Unrecognized field names receive type based random strings or numbers depending on JSON schema type hints when present. Phone and address fields generate plausible formatted strings when field names include tel or address substrings. Array length parameter controls how many sample holdings appear in mock response. Array length parameter controls how many sample holdings appear in mock response.

How many rows can I generate?

Set row count from 1 to 1,000. The tool generates that many independent mock records, each with fresh randomized values following the same schema pattern. Download JSON for import into Postman collections or mock service workers during offline development. Large row counts help QA teams verify sorting and filtering logic before production data volumes arrive. Nullable fields in schema produce null samples in some rows to test empty state UI paths. Nullable fields in schema produce null samples in some rows to test empty state UI paths.

Can I generate realistic financial data?

For financial APIs, include fields named date, symbol, type, quantity, price, amount. The tool will generate plausible trading transaction rows. Financial schemas with transaction type enums generate buy sell and dividend rows when type field names match heuristics. Portfolio summary schemas with totalValue and dayChange fields populate realistic aggregate numbers for dashboard header components. Export mocks into MSW handlers for integration tests that mirror production response shapes. Wire mocks into Playwright tests so CI runs without staging API credentials or rate limits. Export mocks into MSW handlers for integration tests that mirror production response shapes. Wire mocks into Playwright tests so CI runs without staging API credentials or rate limits.

휴대폰이나 태블릿에서 API 모의 데이터 생성기을(를) 사용할 수 있나요?

예. 이 도구는 데스크톱과 동일한 공식으로 모바일 브라우저에서 완전히 실행됩니다. 선택적 localStorage는 브라우저 설정에서 활성화된 경우 기기에 입력값을 기억할 수 있습니다.

API 모의 데이터 생성기을(를) 사용할 때 내 데이터는 어디에 저장되나요?

당사 서버 어디에도 없습니다. 계산은 브라우저에서 로컬로 실행됩니다. 선택적 localStorage는 기기에서만 양식 필드를 저장하며 네트워크를 통해 포트폴리오 번호를 전송하지 않습니다.

세금 또는 법적 결정에 API 모의 데이터 생성기에 의존해야 하나요?

아니요. 이 도구는 교육용 수학만 제공합니다. 세법, 계좌 규칙 및 개인 상황은 다양합니다. 중대한 결과를 초래하는 거래 전에 자격을 갖춘 세무 또는 법률 전문가와 상담하세요.