What is a JSON validator?

A JSON validator checks whether text follows the JSON syntax rules and reports the exact line and column of the first problem. This tool validates as you type, so you know at once whether an API, app or config loader will be able to parse your JSON.

What is the difference between a JSON validator, formatter and converter?

A validator checks that JSON is correct. A formatter (beautifier or minifier) only changes whitespace so JSON is easier to read or smaller to send. A converter turns the same data into another format such as XML, YAML, CSV or TypeScript. This page does all three in one workspace.

Why is my JSON invalid?

The usual causes are trailing commas, single quotes instead of double quotes, unquoted keys, comments, missing commas or brackets, and Python-style True, False or None. The status bar shows the line and column, and the Auto-fix button repairs the common syntax mistakes in one click.

Does Auto-fix change my data?

Auto-fix repairs syntax only: it removes comments and trailing commas, converts single quotes to double quotes, quotes bare keys, and turns True, False, None and undefined into true, false and null. Values are not otherwise rewritten, but review the result before you use it. Structural errors such as a missing bracket cannot be repaired automatically.

How do I convert JSON to CSV?

Paste a JSON array of objects, choose CSV in the output format menu, then use Copy or Download (the file is saved as converted.csv). Nested objects are flattened into dotted column names such as address.city, and nested arrays are kept as JSON text inside the cell.

Can I convert XML, YAML or CSV back to JSON?

Yes. Set the Input menu to YAML, XML or CSV, paste your data or drop a .yaml, .xml or .csv file, and choose JSON as the output. The Use as input button lets you chain one conversion into the next.

How do I expand or collapse all nodes in JSON?

In the Output tab use Expand all, Collapse all or the depth menu to open a set number of levels, or click the arrow next to any line to fold just that node. The same controls are in the Tree tab. Folding only changes what you see: Copy and Download always use the full text. The input box is an editable text area, so use Beautify and then fold in the Output or Tree tab.

How can I see the size of my JSON?

The Input panel shows the size and line count of what you pasted, and the output toolbar shows the size of the converted result and its percentage change against the input. Hover either badge for the character count.

What is JSONPath and how do I use it here?

JSONPath is a query syntax for picking values out of JSON, for example $.items[*].name returns the name of every item. Open the Tree tab, type the expression into the search box, and click a result to copy its path. Plain text search on keys and values works too.

Is my data uploaded or stored anywhere?

No. Validation and conversion run in your browser and nothing you paste is sent to a server. History is kept only in your own browser storage and can be cleared at any time. Two features touch the network only when you use them: From URL fetches the address you type directly from your browser, and Share places your data in the link itself, so anyone you give that link to can read it.

Is there a size limit?

There is no fixed limit, but because everything runs locally, very large files depend on your device's memory. History skips inputs over 200,000 characters and Share links work for inputs up to 3,000 characters, so use Download for bigger data.

Which JSON Schema features does the Schema tab support?

It supports a practical draft-07 subset: type, required, properties, items, enum, minimum and maximum, string and array length limits, pattern, additionalProperties and anyOf. Each mismatch is listed with where it occurred in your data.

Yes. It is free to use, with no account or sign-up required.

Free Mock Data Generator: Fake JSON, CSV & SQL

Generate realistic fake users, orders and addresses as JSON, CSV, SQL INSERTs or JSON Lines. Repeatable with a seed, customisable fields, free and private.

Dataset

Rows

Seed

Output format

ID style

FieldsRename keys, untick to remove, or build your own columns.

What is a mock data generator?

A mock data generator creates realistic but fake records, such as users, orders and addresses, so you can build and test software without real data. Instead of typing sample rows by hand or copying production data, you generate as many as you need in the format your tool expects.

This free generator produces JSON, CSV, SQL INSERT statements and JSONL. It runs in your browser, gives repeatable results through a seed, and lets you choose exactly which fields to include.

Realistic

Related fields agree with each other.

Repeatable

The same seed gives the same data.

Flexible

JSON, CSV, SQL and JSONL output.

Your settings

Dataset: Users
Rows:    2
Seed:    demo
Format:  CSV

↓ Generate ↓

Output

id,firstName,lastName,email,isActive
1,Ravi,Kim,ravi.kim69@sample.io,true
2,Hugo,Ali,hugo.ali54@mail.test,true

What is it useful for?

Test data is needed at every stage of development. Here is where this generator saves the most time.

Use case	What you need	How this tool helps
Prototype a UI before the API exists	Realistic rows to fill tables, cards and forms	Generate users, orders or addresses as JSON and wire them into your frontend.
Seed a development database	INSERT statements that match your schema	Export SQL with CREATE TABLE and child tables for MySQL, PostgreSQL or SQL Server.
Feed a mock API	A JSON file a mock server can return	Save the JSON and serve it, as in our mock API from an OpenAPI spec tutorial.
Load and import tests	Hundreds of rows in CSV or JSON Lines	Generate up to 1,000 rows per run, and change the seed for more batches.
Demos, docs and screenshots	Believable data without real customers	Everything is fictional, with example email domains and made-up names.
Repeatable automated tests	The same data on every run	Fix the seed and your fixtures never change, so failures are easy to reproduce.

Fake data, private by design

Everything is generated in your browser and nothing is uploaded. All values are fictional, but because they are random they can occasionally resemble real ones, so do not use them as real personal data.

Every feature, explained

What each control means, and exactly how to use it.

Datasets

Ready-made users, orders and addresses whose fields agree with each other: emails match names, and order totals match their line items.

HowPick Users, Orders or Addresses at the top of the settings panel.

Row count

Chooses how many records to create, from 1 to 1,000.

HowType a number in Rows. The output updates instantly.

Seed (repeatable data)

The starting value for the random generator. The same seed always gives identical data.

HowKeep your seed to get the same data again. Click 🎲 for a new one, or type your own.

Output formats

JSON for APIs, CSV for spreadsheets, SQL for databases, and JSONL (one JSON object per line) for logs and pipelines.

HowChoose a format under Output format.

SQL options

Sets the table name and SQL dialect, and can add CREATE TABLE. Arrays such as order items become a linked child table.

HowChoose SQL, then set the table name, dialect and CREATE TABLE option.

ID style

Sequential numbers (1, 2, 3) suit databases. UUIDs suit APIs and distributed systems.

HowSwitch ID style between Sequential numbers and UUIDs.

Field picker

Includes only the fields you need, so the output matches your own schema.

HowUntick any field chip. The output updates immediately.

Copy and download

Takes the result out of the page as text or as a file named after the dataset.

HowClick Copy or Download above the output.

Open in JSON tool

Sends generated JSON to the JSON validator and converter to reformat it or convert it to XML, YAML or TypeScript.

HowWith JSON selected, click Open in JSON tool.

Custom fields and key names

Rename any key to match your schema, or add your own columns. Pick a type such as UUID, number range, date, name, email, text, a list of values or a fixed value.

HowEdit a name in Fields, or click + Add custom field, name it and choose a type. Click Clear all fields to remove the presets and build your own from scratch, and Restore defaults to bring them back.

Full screen

Gives the settings and a large output the whole window, which helps with big result sets.

HowClick Full screen above the output. Press Esc to exit.

How to use the mock data generator

Four steps from an empty page to ready-to-use test data.

01
Pick a dataset
Choose Users, Orders or Addresses, then set how many rows you need.
02
Choose your fields
Untick fields you do not need, and choose sequential or UUID ids.
03
Select a format
Pick JSON, CSV, SQL or JSONL. For SQL, set the table name and dialect.
04
Copy or download
Copy the result, download a file, or open it in the JSON tool.

Common workflows

Seed a database

Test data for MySQL, PostgreSQL or SQL Server

Choose Orders and set the rows.
Select SQL and your dialect.
Keep Include CREATE TABLE ticked.
Copy and run it in your database.

Data for a mock API

JSON your mock server can return

Choose Users and JSON.
Pick fields to match your schema.
Download users.json.
Serve it from your mock API.

Spreadsheet test data

Import into Excel or Google Sheets

Choose any dataset.
Select CSV.
Click Download.
Open the file in your spreadsheet.

Datasets and output formats

What is inside each dataset, and which format to choose.

Dataset	Fields	Good for
Users	id, firstName, lastName, email, username, phone, dateOfBirth, jobTitle, company, role, isActive, address, createdAt	Accounts, profiles and login tests
Orders	id, orderNumber, customerName, customerEmail, status, paymentMethod, currency, items, subtotal, tax, shipping, total, orderDate, shippedAt, shippingAddress	Shop and checkout flows, reports
Addresses	id, label, recipient, street, city, state, zip, country, countryCode, latitude, longitude, phone, isDefault	Forms, maps and shipping tests

Format	What you get	Best for
JSON	Pretty-printed array of objects, with nested data	APIs, frontends, fixtures
CSV	Header row and one row per record; nested keys become `address.city`	Spreadsheets and imports
SQL	CREATE TABLE and batched INSERTs; nested keys become `address_city`, arrays become child tables	Seeding databases
JSONL	One compact JSON object per line	Logs, streaming and data pipelines

Frequently asked questions

Quick answers about fake data, seeds and SQL output.

Is the generated data real?

No. All names, emails, phone numbers and addresses are made up. Emails use example domains, and nothing comes from a real person or customer. Because values are random, a result can look like a real one by coincidence, so never use it as real personal data.

How do I get the same data every time?

Use the Seed field. The same seed, dataset, row count and ID style always produce the same output, which makes tests and demos repeatable.

How are nested objects handled in CSV and SQL?

CSV flattens nested objects into columns with dots, such as address.city. SQL flattens them with underscores, such as address_city, and turns arrays of objects, like order items, into a child table with a foreign key to the parent id.

Which SQL databases are supported?

The generated SQL works with MySQL, PostgreSQL and SQL Server. The dialect setting changes identifier quoting, boolean and timestamp types, and string escaping. Check column types before using it in production.

Why is there a 1,000 row limit?

Everything is generated in your browser, so the limit keeps the page fast on any device. For more rows, generate several batches with different seeds.

Is my data uploaded anywhere?

No. The generator runs entirely in your browser. Nothing is sent to a server, and it is free to use without an account.

Can I rename fields or add my own columns?

Yes. Edit any key name in the Fields list, untick fields you do not need, and use Add custom field to create extra columns. Custom columns can be UUIDs, numbers in a range, dates, names, emails, short text, values picked from your own list, or a fixed value. Use Clear all fields to remove the preset fields and start from a blank list, and Restore defaults to bring them back.

Need to check or convert your data?

Validate the JSON you generated, follow the mock API tutorial, or explore more free developer tools.

Open the JSON tool Mock API tutorial All free tools

Free Mock Data Generator: Fake JSON, CSV & SQL

What is a mock data generator?

Realistic

Repeatable

Flexible

What is it useful for?

Every feature, explained

Datasets

Row count

Seed (repeatable data)

Output formats

SQL options

ID style

Field picker

Copy and download

Open in JSON tool

Custom fields and key names

Full screen

How to use the mock data generator

Pick a dataset

Choose your fields

Select a format

Copy or download

Common workflows

Seed a database

Data for a mock API

Spreadsheet test data

Datasets and output formats

Frequently asked questions

Need to check or convert your data?