Click "Generate Data" above to start...
The JSON Mock Data Generator is a developer-focused online tool that quickly generates structured random test data. Whether you're developing API endpoints, frontend pages, or database testing, this tool helps you generate mock data that matches your requirements.
1. Select Data Fields: Check the data types you need to generate above, such as names, emails, addresses, etc. Each field can be selected independently—you can freely combine them based on your needs.
2. Set Generation Options: In the "Generation Options" section, you can set the number of records (1-10,000), data language (English/Chinese/Mixed), output format (JSON/CSV), and JSON indentation style.
3. Generate and Export: After clicking "Generate Data", the results will appear below. You can copy JSON data directly to clipboard or click "Download" to save it as a file.
The tool includes 20+ built-in data types covering personal information, network data, numeric values, and more. All data is pseudorandom algorithmically generated and contains no real personal information.
For complex data needs, you can generate base data with this tool and then further process it in your code. For example, generate a user list and add custom fields and logic on top of it.
API Development and Testing: When developing RESTful APIs, you need large amounts of test data to validate endpoints. Use this tool to quickly generate JSON data that matches your data structures, usable directly as request or response bodies.
Frontend Prototype Design: When designing data lists, tables, cards, and other components, you need realistic data to demonstrate effects. This tool generates mock data including names, avatar URLs, status fields, and more.
Database Seeding and Testing: In development and testing environments, you may need to insert large amounts of test data into databases. Use the CSV export feature to directly import into MySQL, PostgreSQL, and other databases.
Automated Testing Scripts: When writing automated test cases, use generated random data as input parameters to test how your system handles different data scenarios.
Data Visualization Development: When developing charts, dashboards, and other data visualization components, you need many data points to verify rendering. This tool generates structured data suitable for charts.
What is Mock Data? Mock data refers to fictional data used during software development to simulate real data. It doesn't involve real user privacy while meeting development and testing data needs. In modern frontend-backend separation workflows, mock data is especially important since frontend developers can start building before backend APIs are ready.
Why Do You Need Mock Data? In agile development, frontend and backend teams often work in parallel. Using mock data allows frontend developers to start page development and functional testing before backend APIs are complete, significantly improving development efficiency. Mock data is also useful for demos, education, and prototype validation.
Mock Data Best Practices: Generated mock data should closely match real data formats. For example, emails should include @ symbols and valid domains, phone numbers should follow formatting rules, and dates should fall within reasonable ranges. The data generated by this tool follows these best practices.
JSON vs CSV: JSON format is suitable for structured data, supports nested objects and arrays, and is the preferred format for modern web development. CSV format is suitable for tabular data, can be opened directly in Excel, and is ideal for data analysts and non-technical users.
No. All data is pseudorandom algorithmically generated and is not associated with any real person, company, or address in the real world. It is completely safe to use in any scenario.
The current version generates flat structures. For nested structure needs, we recommend generating base data with this tool and then processing it further in your code or JSON editor.
Currently JSON and CSV export formats are supported. JSON format supports custom indentation (2 spaces / 4 spaces / no indent). CSV format is suitable for importing into Excel or databases.
By default, each generation is random, and duplicate values may exist within the same generation. If you need unique values, we recommend deduplicating in your code after generation.
Currently supports name, email, phone, ID card, address, company, job title, username, URL, IP address, UUID, date, timestamp, random number, boolean, color, paragraph, avatar URL, domain, and amount—over 20 data types.
Yes. This tool is fully responsive and works on phones, tablets, and desktops. The interface automatically adapts to different screen sizes.
The core data generation functionality works offline. Only the initial page load and Google Analytics require a network connection. All data generation happens locally in your browser.
You can contact us via the email at the bottom of the page, or submit an issue on GitHub. We read every piece of feedback and continuously improve the tool.