Choose columns for your fixture
Start with id, name, email and created_at, then add fields such as city, country, company, boolean, integer or UUID. Names must be unique ASCII identifiers. Up to twelve fields and ten thousand rows are supported.
Reuse the result
For a minimal fixture, set two fields: id with type ID and active with type Boolean. Choose English, three rows, seed 42 and JSON output. The current generator produces:
[
{
"id": 1,
"active": true
},
{
"id": 2,
"active": false
},
{
"id": 3,
"active": false
}
]Keep the seed, field order and library version stable when snapshot tests depend on these values. Adding a new field may consume random draws and change later generated values. A seed makes a test repeatable; it does not turn fake data into a representative production dataset.
JSON output can be sent to the existing conversion and SQLite tools. CSV and TSV output quote separators and prefixes text that could be interpreted as a spreadsheet formula. XML output wraps scalar field values in named elements. SQL output contains INSERT statements for a table named mock_data; create a compatible table before running them.
Keep test data repeatable
Set a fixed seed to compare output across test runs. The generator loads only the selected English or Chinese locale and runs in a cancellable worker. Generation has a twenty-second timeout and a two-million-character output limit.
Send fixture JSON to JSON to TypeScript, inspect it with JSON Viewer, or compare it with an existing JSON Schema. Use JSON Schema to Example when the schema, rather than a field list, must drive the generated record.
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Frequently asked questions
Will the same seed reproduce the output?
The same fields, order, language, seed and Faker version produce the same values. Date generation uses a fixed 2020–2030 reference range. Updating the library can change generated values.
Does this create real personal information?
Values are synthetic test fixtures and may coincidentally resemble real people or places. Email fields use example domains. Generated values are not passwords or authentication secrets.
How is this different from Schema to Example?
This tool builds a table from user-selected field types. JSON Schema to Example generates a record that is checked against a supplied schema. This generator does not validate against a schema.
Sources
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