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Test Data Generator — Custom Schema Builder

Generate realistic fake records for testing and QA. Define a field schema, pick data types — UUID, email, name, phone, date, and more — set a row count, and export as JSON or CSV. 100% client-side and free.

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How to Use Test Data Generator — Custom Schema Builder

How to Use the Test Data Generator

Step 1: Load a Preset or Define Your Schema

Start from a preset schema (User Accounts, Orders, Support Tickets, Employees) or build your own from scratch. Presets provide a ready-to-use field structure — click any preset button to load it into the schema builder immediately.

Step 2: Define Your Fields

Each row in the schema builder represents one field in your output records. Enter a field name (e.g., user_id, email, created_at) and pick a data type from the dropdown. You can add as many fields as needed using the Add Field button, or remove fields with the trash icon.

Step 3: Choose a Data Type for Each Field

Supported types include:

  • UUID — generates a unique UUID v4 string
  • Integer — sequential integers starting from 1 (ideal for auto-increment IDs)
  • Float — random decimal numbers between 1.00 and 999.99
  • Boolean — random true or false
  • First Name / Last Name / Full Name — realistic names from a built-in pool
  • Username — lowercase first_last + number (e.g., alice_smith42)
  • Email — realistic email addresses (e.g., alice.smith@example.com)
  • Phone — US-format phone numbers: (NNN) NNN-NNNN
  • Company — company names from a built-in pool
  • URL — realistic HTTPS URLs with paths
  • IP Address — random IPv4 addresses
  • Date — random dates between 2020 and 2025 in ISO format (YYYY-MM-DD)
  • Word — a single lowercase word from a built-in wordlist
  • Paragraph — a Lorem Ipsum sentence of 10–20 words

Step 4: Set the Number of Rows

Enter a row count between 1 and 500. For quick manual testing, 5–10 rows is typically enough. For seeding a database or stress-testing an import pipeline, use 100–500 rows.

Step 5: Generate

Click Generate Data. The tool immediately builds all records in your browser and displays the output. Both JSON and CSV formats are generated simultaneously — no need to regenerate to switch formats.

Step 6: Switch Between JSON and CSV

Use the JSON / CSV toggle in the output panel to switch views. JSON output is a formatted array of objects. CSV output includes a header row followed by one row per record, with values properly quoted if they contain commas.

Step 7: Copy or Download

Click Copy to copy the current format to your clipboard, or Download to save the file as test-data.json or test-data.csv. Downloaded files are ready to import into databases, REST clients, spreadsheets, or test fixtures.

Step 8: Reset

Click Reset to restore the default 3-field schema (id, full_name, email) and clear all generated output.

Common Use Cases:

  • Database seeding: Populate dev/staging databases with realistic records
  • API testing: Generate request payloads or mock response bodies
  • UI development: Create sample data to fill tables, lists, and cards in the browser
  • Import testing: Verify CSV import pipelines with edge cases and varied values
  • Load testing: Generate large datasets for performance benchmarks
  • QA fixtures: Create test fixture files for unit and integration tests
  • Prototyping: Quickly populate a new schema with realistic-looking data
  • Demo environments: Seed a demo database with safe, non-real records

Tips and Best Practices:

  • Use UUID for primary keys to ensure uniqueness across generated rows
  • Integer type generates sequential values (1, 2, 3…) — good for auto-increment IDs
  • Field names are used as JSON keys and CSV headers — use snake_case for database compatibility
  • Load a preset first, then add or remove fields to customize it
  • Paragraph fields work well for description, bio, or notes columns
  • Boolean fields are randomly true or false — useful for testing conditional UI states
  • Generate 5–10 rows first to verify the schema looks right, then increase to the full count
  • CSV output quotes values containing commas automatically
  • All data is synthetic — safe to use in demos, screenshots, and documentation

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