portfolios.tools

API Mock Data Generator

Generate mock fintech API rows from JSON schemas.

Results
[
  {
    "accountId": "25b8f546-76c8-47f1-afe4-71582748e782",
    "amount": 23006.63,
    "date": "2026-04-29"
  },
  {
    "accountId": "9c4985c9-26bf-4e6a-8578-076625b17f67",
    "amount": 44569.72,
    "date": "2026-03-09"
  },
  {
    "accountId": "e6ca72e3-4894-471b-ae59-a1acd946079c",
    "amount": 16754.5,
    "date": "2025-11-22"
  },
  {
    "accountId": "bd67569b-9c68-42ae-b768-14e5b93c423d",
    "amount": 13500.16,
    "date": "2025-09-28"
  },
  {
    "accountId": "d7371c69-60d8-483d-b8ee-243cb3502567",
    "amount": 25696.04,
    "date": "2025-09-12"
  },
  {
    "accountId": "ae0e5ad4-bb67-4b3e-8d2c-6f805473348d",
    "amount": 46593.53,
    "date": "2025-12-10"
  },
  {
    "accountId": "78828770-dc35-4a9d-939d-92debe1c3b73",
    "amount": 2782.26,
    "date": "2025-09-25"
  },
  {
    "accountId": "87487827-e131-454a-b4d3-e4d0e97f87ca",
    "amount": 11733.14,
    "date": "2025-08-10"
  },
  {
    "accountId": "cad026a6-2eda-495f-9b6b-1017c585f9e4",
    "amount": 29370.66,
    "date": "2025-12-17"
  },
  {
    "accountId": "ef0d2760-f8fe-4a41-b96c-bb51a048eb98",
    "amount": 32491.83,
    "date": "2025-12-13"
  }
]

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$5
$1$50

How It Works

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.

Use API Mock Data Generator whenever inputs change: after market moves, new contributions, or revised personal assumptions. Bookmark the page for quick reruns without installing software.

Step by step

  1. Paste JSON schema and set row count
  2. Review generated mock data and field types
  3. Copy or download the generated JSON

Worked example

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

Adjust one input at a time to see sensitivity. API Mock Data Generator updates instantly so you can stress test optimistic and conservative assumptions before acting.

When to use this calculator

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.

Pair with related tools when the decision spans taxes, liquidity, or multi year projections beyond what one formula captures.

Common mistakes

Copying outputs without checking input units or stale market prices is a frequent error with API Mock Data Generator. Confirm tickers, percentages, and dates before acting.

Running a single baseline scenario ignores tail risks. Stress test with conservative inputs and compare against related tools listed below when the decision is material.

The Formula

Field inference walks JSON keys recursively. Value generation uses field name regex heuristics: /id|uuid/ → UUID, /email/ → email, /name/ → full name, /date|time/ → ISO date, /amount|price|balance/ → decimal 10-50000, /symbol|ticker/ → stock ticker.

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.

Limitations and assumptions

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. API Mock Data Generator does not replace personalized advice. Fees, slippage, account specific rules, and behavioral constraints may change real world outcomes.

Key terms

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.
Model assumption
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.

Compare alternatives

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

Internal links on portfolios.tools help you chain calculators: run API Mock Data Generator first, then validate edge cases with a specialized tool from the related section below.

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.

Can I use API Mock Data Generator on a phone or tablet?

Yes. API Mock Data Generator runs entirely in your mobile browser with the same formulas as desktop. Optional localStorage may remember inputs on your device when enabled in browser settings.

Where is my data stored when I use API Mock Data Generator?

Nowhere on our servers. Calculations execute locally in your browser. Optional localStorage saves form fields on your device only and never transmits portfolio numbers over the network.

Should I rely on API Mock Data Generator for tax or legal decisions?

No. API Mock Data Generator provides educational math only. Tax law, account rules, and personal circumstances vary. Consult a qualified tax or legal professional before transactions with material consequences.

Related Tools

Parse CSV exports with CSV to Financial JSON. Debug JWT auth with JWT Debugger. Schedule jobs with Cron Market Scheduler. Transform SQL schemas with SQL to TypeScript tool. Convert YAML configs with YAML JSON Portfolio tool. JSON to OpenAPI Converter documents the same API this generator mocks for full contract first workflows. JSON to OpenAPI Converter documents the same API this generator mocks for full contract first workflows.