Random JSON Generator for Test Data and Fixtures Online
Random JSON Generator creates random JSON data from a schema-like specification, so you can make mock values for tests and development without writing every value by hand. Define fields as strings, numbers, booleans, objects, or arrays, then set array lengths and nesting depth. Add a seed when you need deterministic output that can be generated again.
Random JSON Generator is a browser-based tool for creating random JSON from a schema-like specification. Define fields using string, number, boolean, object, or array types, then generate data for tests, fixtures, and development. Instead of writing every sample value manually, you can describe the kinds of JSON values you need and let the generator create them.
The available options control the shape of the generated data. Set array lengths to specify how many items arrays contain, and choose a nesting depth to control how deeply the JSON structure is nested. You can also provide a seed for deterministic output, which is helpful when you want generated data you can reproduce. The tool is based on a specification; it does not require you to start with an existing JSON document.
JSON represents structured data using values such as objects, arrays, strings, numbers, and booleans. Random JSON is useful when you need sample data to exercise code without relying on production data or creating every value by hand. Adjusting the field types, array lengths, and nesting depth helps you create samples that fit different test scenarios, while a seed can make the generated output repeatable.
Random JSON Generator runs entirely in your browser, and your input is processed on your own device rather than sent to a server. Once the page has loaded, it continues to work offline. Developers and DevOps engineers can use it to prepare mock data, build test fixtures, or create seed data for development workflows.
Step 1: Choose fields and their types in the schema-like specification. Use string, number, boolean, object, or array for the JSON values you need.
Step 2: Set array lengths and nesting depth. These options shape the generated arrays and how deeply the JSON data is nested.
Step 3: Add a seed if you want deterministic output. Seeded generation lets you reproduce output for testing.
Step 4: Generate the JSON, then copy the values you need. Use the result as mock data, a test fixture, or seed data.
Use case: Create random JSON values for tests, fixtures, or seed data. Specifying the fields and types helps you get data in the structure your test needs.
Use case: Generate a whole batch of values instead of inventing each one by hand. This can save time when you need several examples for development or testing.
Use case: Use randomly generated values rather than guesses typed at a keyboard. This gives you varied data to work with in tests and mockups.
Use case: Create test data with a particular mix of strings, numbers, booleans, objects, and arrays. The schema-like specification lets you describe the kinds of values to generate.
Use case: Set array lengths and nesting depth to create JSON structures that match the shape your code expects. This is useful when testing code that handles nested data.
Use case: Add a seed when you need deterministic output for a test run. Reproducible data can make it easier to investigate behavior across repeated runs.