Mockachu - Mock Data Generator | Fake Data Generator | Test Data Generator

🎲 Free Open Source Mock Data Generator - A powerful desktop application and REST API for generating realistic fake data, test data, and sample data for testing, development, and prototyping.

Keywords: mock data generator, fake data generator, test data generator, sample data, dummy data, random data generator, API testing data, database seed data, JSON generator, CSV generator

What is Mockachu?

Mockachu is a free, open-source mock data generator that helps developers, testers, and data analysts create realistic test data quickly and efficiently. Whether you need fake user profiles, sample financial data, or dummy API responses, Mockachu generates high-quality mock data in multiple formats.

Perfect for:

🧪 API Testing - Generate sample data for REST API development and testing
🏗️ Database Seeding - Create realistic data to populate development databases
📊 Data Analysis - Generate datasets for testing analytics and reporting tools
🎯 Prototyping - Create sample data for demos and proof-of-concepts
🚀 Development - Mock external API responses during development
📱 Mobile App Testing - Generate user profiles and content for mobile apps

🚀 Key Features & Capabilities

🖥️ Desktop Application (GUI)

User-Friendly Interface - Cross-platform desktop app with intuitive PyQt6 GUI
15+ Data Generators - Generate realistic data for:
- 👥 Personal Data: Names, emails, addresses, phone numbers, ages
- 💳 Financial Data: Credit cards, IBANs, currencies, bank information
- 🌍 Geographic Data: Cities, countries, coordinates, timezones
- 🚗 Automotive Data: Car brands, models, VIN numbers
- 🎨 Design Data: Colors (hex, RGB, names), HTML color codes
- 🎬 Entertainment: Movies, TV series, random text content
- 💻 Technical Data: UUIDs, IP addresses, MAC addresses, domains, URLs
- 📅 Date & Time: Timestamps, date ranges, custom formats
- � Numeric Data: Random numbers, sequences, decimal values
Multiple Export Formats - JSON, CSV, XML, SQL, HTML output
Advanced Customization - Configure nullable fields, custom patterns, parameters
Configuration Management - Save, load, and share field configurations

🌐 REST API for Developers

RESTful HTTP API - Generate mock data programmatically via HTTP requests
Easy Integration - Simple JSON-based API calls for any programming language
Interactive Documentation - Built-in Swagger UI at /swagger for API testing
High Performance - Generate up to 100,000 rows per request
CORS Enabled - Cross-origin requests supported for web applications
Multiple Response Formats - Return data as JSON, CSV, or XML
No Authentication Required - Perfect for development and testing environments

💡 Popular Use Cases & Examples

For Developers

API Development: Generate sample user profiles, orders, products for REST API testing
Database Seeding: Create realistic test data for MySQL, PostgreSQL, MongoDB databases
Unit Testing: Generate mock objects and test fixtures for automated testing
Frontend Development: Create placeholder content for React, Vue, Angular applications
Microservices Testing: Generate data for testing service integrations

For QA Engineers & Testers

Load Testing: Generate large datasets for performance testing with JMeter, K6
Test Data Management: Create consistent test data across different environments
Automation Testing: Generate dynamic test data for Selenium, Cypress tests
API Testing: Create varied request payloads for Postman, Insomnia testing
Edge Case Testing: Generate boundary values and edge cases for thorough testing

For Data Analysts & Scientists

Data Pipeline Testing: Create sample datasets for ETL process validation
Analytics Development: Generate data for testing reports, dashboards, visualizations
Machine Learning: Create training datasets for ML model development
Data Modeling: Generate sample data for database schema validation
A/B Testing: Create consistent test datasets for experiment analysis

Common Search Terms This Tool Helps With:

mock data generator, fake data generator, test data generator, dummy data creator, sample data generator, random user generator, JSON data generator, CSV test data, API mock data, database seed data, lorem ipsum generator, fake person generator, random address generator, credit card number generator, phone number generator, email generator, UUID generator, timestamp generator

📦 Installation

Pre-built Executables (No Python Required)

For users who prefer standalone applications without installing Python:

⚠️ Security Note: Pre-built executables will show security warnings on first run because they're not code-signed. This is normal and safe. See the Security Information section below for details on how to bypass these warnings.

Download Links

Windows: Download Mockachu-Windows.zip from Releases
macOS: Download Mockachu-macOS.zip from Releases
Linux: Download Mockachu-Linux.tar.gz from Releases

Installation Instructions

Windows:

Download and extract Mockachu-Windows.zip
Run Mockachu.exe
No installation required!

macOS:

Download and extract Mockachu-macOS.zip
Move Mockachu.app to your Applications folder
Right-click and select "Open" (required for first run due to Gatekeeper)

Linux:

Download and extract Mockachu-Linux.tar.gz
Make executable: chmod +x mockdatagenerator
Run: ./mockdatagenerator

Note: Pre-built executables include both the GUI application and the API server. Use command-line flags to choose which component to run.

From PyPI (Recommended for Developers)

# Install API only (lightweight)
pip install mockachu

# Install with GUI support
pip install mockachu[gui]

# Install with development tools
pip install mockachu[dev]

# Install everything
pip install mockachu[all]

From Source

git clone https://github.com/sahzudin/mockachu.git
cd mockachu
pip install -e ".[gui,dev]"

🔒 Security Information

Pre-built Executable Security Warnings

When running pre-built executables, you may encounter security warnings. This is normal and expected for unsigned applications:

macOS

Warning: "macOS cannot verify the app is free of malware"

Solutions:

Right-click method (Recommended):
- Right-click the app → Select "Open"
- Click "Open" in the security dialog
System Preferences method:
- Go to System Preferences → Security & Privacy
- Click "Open Anyway" for Mockachu

Terminal method:

xattr -d com.apple.quarantine /path/to/Mockachu.app

Windows

Warning: "Windows protected your PC" or SmartScreen filter

Solution:

Click "More info" → "Run anyway"
Or go to Settings → Update & Security → Windows Security → App & browser control

Linux

Issue: Downloaded file may not be executable

Solution:

chmod +x mockdatagenerator

Why These Warnings Occur

Code Signing Cost: Apple Developer ($99/year) and Windows certificates ($200-400/year)
Open Source: This project prioritizes accessibility over commercial code signing
False Positive: The warnings don't indicate actual malware - just lack of expensive certificates

Alternative: Run from Source

If you prefer to avoid security warnings entirely:

git clone https://github.com/sahzudin/mockachu.git
cd mockachu
pip install -e ".[gui]"
python app.py

Quick Start

Desktop Application

Install with GUI support
```
pip install mockachu[gui]
```
Run the Application
```
mockachu
# or
python app.py
```

API Server

Install the package
```
pip install mockachu
```

Start the API Server

mock-data-api
# or
python api_server.py

Or with custom options:

python api_server.py --host 0.0.0.0 --port 8000 --debug

Access API Documentation
```
http://localhost:8843/docs
```

API Documentation

Base URL

http://localhost:8843

Authentication

No authentication required for local development.

🔍 GET / - API Information

Get basic API information and available endpoints.

Response:

{
  "name": "Mockachu API",
  "version": "1.0.0",
  "description": "REST API for generating realistic mock data",
  "endpoints": {
    "GET /": "API information",
    "GET /health": "Health check",
    "GET /generators": "List available generators and actions",
    "POST /generate": "Generate mock data",
    "GET /docs": "API documentation"
  },
  "documentation": "/docs"
}

💚 GET /health - Health Check

Check if the API server is running properly.

Response:

{
  "status": "healthy",
  "timestamp": "2025-08-16T10:30:00.000Z",
  "version": "1.0.0"
}

🛠️ GET /generators - Available Generators

Get a list of all available generators and their actions.

Response:

{
  "generators": [
    {
      "name": "PERSON_GENERATOR",
      "display_name": "Persons",
      "actions": [
        {
          "name": "RANDOM_FIRST_NAME",
          "display_name": "First name"
        },
        {
          "name": "RANDOM_LAST_NAME", 
          "display_name": "Last name"
        }
      ]
    }
  ]
}

🎲 POST /generate - Generate Mock Data

Generate mock data based on field configuration.

Content-Type: application/json

Request Body:

{
  "fields": [
    {
      "name": "field_name",
      "generator": "GENERATOR_NAME", 
      "action": "ACTION_NAME",
      "nullable_percentage": 0,
      "parameters": []
    }
  ],
  "rows": 10,
  "format": "JSON"
}

Parameters:

Field	Type	Required	Description
`fields`	Array	✅	Array of field configurations
`fields[].name`	String	✅	Field name in output
`fields[].generator`	String	✅	Generator to use (see `/generators`)
`fields[].action`	String	✅	Action to perform (see `/generators`)
`fields[].nullable_percentage`	Number	❌	Percentage of null values (0-100)
`fields[].parameters`	Array	❌	Additional parameters for the action (can contain numbers, strings, etc.)
`rows`	Number	❌	Number of rows to generate (default: 10, max: 100,000)
`format`	String	❌	Output format: `JSON`, `CSV`, `XML` (default: JSON)

Response:

{
  "success": true,
  "data": [
    {
      "first_name": "John",
      "email": "john.doe@example.com"
    }
  ],
  "metadata": {
    "rows_generated": 1,
    "fields_count": 2,
    "format": "JSON",
    "generation_time_seconds": 0.045,
    "timestamp": "2025-08-16T10:30:00.000Z"
  }
}

API Examples

Basic Person Data

curl -X POST http://localhost:8843/generate \\
  -H "Content-Type: application/json" \\
  -d '{
    "fields": [
      {
        "name": "first_name",
        "generator": "PERSON_GENERATOR",
        "action": "RANDOM_FIRST_NAME"
      },
      {
        "name": "last_name", 
        "generator": "PERSON_GENERATOR",
        "action": "RANDOM_LAST_NAME"
      },
      {
        "name": "email",
        "generator": "IT_GENERATOR",
        "action": "RANDOM_EMAIL"
      }
    ],
    "rows": 5
  }'

Numbers with Parameters

curl -X POST http://localhost:8843/generate \\
  -H "Content-Type: application/json" \\
  -d '{
    "fields": [
      {
        "name": "user_id",
        "generator": "STRING_GENERATOR",
        "action": "RANDOM_NUMBER",
        "parameters": [1000, 9999]
      },
      {
        "name": "price",
        "generator": "STRING_GENERATOR", 
        "action": "RANDOM_DECIMAL_NUMBER",
        "parameters": [10.0, 1000.0, 2]
      }
    ],
    "rows": 3,
    "format": "CSV"
  }'

Geographic Data with Patterns

curl -X POST http://localhost:8843/generate \\
  -H "Content-Type: application/json" \\
  -d '{
    "fields": [
      {
        "name": "location",
        "generator": "GEO_GENERATOR",
        "action": "RANDOM_GEO_DATA_PATTERN",
        "parameters": ["{city}, {country}"]
      },
      {
        "name": "phone",
        "generator": "IT_GENERATOR",
        "action": "RANDOM_PHONE_NUMBER", 
        "parameters": ["+1-___-___-____"]
      }
    ],
    "rows": 10
  }'

Currency and Financial Data

curl -X POST http://localhost:8843/generate \\
  -H "Content-Type: application/json" \\
  -d '{
    "fields": [
      {
        "name": "currency_info",
        "generator": "MONEY_GENERATOR",
        "action": "RANDOM_CURRENCY_PATTERN",
        "parameters": ["{currency} ({code})"]
      },
      {
        "name": "credit_card",
        "generator": "MONEY_GENERATOR",
        "action": "RANDOM_CREDIT_CARD_NUMBER"
      },
      {
        "name": "iban",
        "generator": "MONEY_GENERATOR", 
        "action": "RANDOM_IBAN"
      }
    ],
    "rows": 5
  }'

Available Generators

Generator	Description	Example Actions
`PERSON_GENERATOR`	Personal data	`RANDOM_FIRST_NAME`, `RANDOM_LAST_NAME`, `RANDOM_AGE`
`IT_GENERATOR`	IT-related data	`RANDOM_EMAIL`, `RANDOM_IPV4`, `RANDOM_PHONE_NUMBER`
`GEO_GENERATOR`	Geographic data	`RANDOM_CITY`, `RANDOM_COUNTRY`, `RANDOM_COORDINATES`
`MONEY_GENERATOR`	Financial data	`RANDOM_CURRENCY`, `RANDOM_CREDIT_CARD_NUMBER`, `RANDOM_IBAN`
`CAR_GENERATOR`	Automotive data	`RANDOM_CAR_BRAND`, `RANDOM_CAR_MODEL`, `RANDOM_CAR_VIN`
`COLOR_GENERATOR`	Color data	`RANDOM_COMMON_COLOR`, `RANDOM_HTML_COLOR_HEX`
`STRING_GENERATOR`	Text and numbers	`RANDOM_WORD`, `RANDOM_NUMBER`, `RANDOM_DECIMAL_NUMBER`
`CALENDAR_GENERATOR`	Date and time	`RANDOM_DATE`, `RANDOM_TIME`, `RANDOM_DATE_TIME`
`BIOLOGY_GENERATOR`	Biological data	`RANDOM_ANIMAL`, `RANDOM_PLANT`
`CINEMA_GENERATOR`	Entertainment	`RANDOM_MOVIE`, `RANDOM_SERIES`
`FILE_GENERATOR`	File-related	`RANDOM_FILE_NAME`, `RANDOM_FILE_EXTENSION`
`YES_NO_GENERATOR`	Boolean values	`YES`, `NO`, `RANDOM_BOOLEAN`
`SEQUENCE_GENERATOR`	Sequential data	`SEQUENTIAL_NUMBER`
`CUSTOM_LIST_GENERATOR`	Custom lists	`RANDOM_CUSTOM_LIST_ITEM`
`FIELD_BUILDER_GENERATOR`	Field combinations	`FIELD_JOIN`

For a complete list of actions and parameters, use the /generators endpoint.

Error Handling

The API returns appropriate HTTP status codes and error messages:

400 Bad Request

{
  "error": "Missing required field: 'fields'"
}

500 Internal Server Error

{
  "error": "Generation failed: Invalid generator configuration"
}

Limits

Maximum rows per request: 100,000
Maximum fields per request: 50
Request timeout: 30 seconds
No rate limiting (development server)

Python Client Example

import requests

# Initialize API client
api_url = "http://localhost:8843"

def generate_mock_data(fields, rows=10, format="JSON"):
    """Generate mock data using the API"""
    payload = {
        "fields": fields,
        "rows": rows,
        "format": format
    }
    
    response = requests.post(f"{api_url}/generate", json=payload)
    
    if response.status_code == 200:
        return response.json()
    else:
        raise Exception(f"API Error: {response.text}")

# Example usage
fields = [
    {
        "name": "user_id",
        "generator": "STRING_GENERATOR",
        "action": "RANDOM_NUMBER",
        "parameters": [1000, 9999]
    },
    {
        "name": "username",
        "generator": "IT_GENERATOR", 
        "action": "RANDOM_USERNAME"
    },
    {
        "name": "email",
        "generator": "IT_GENERATOR",
        "action": "RANDOM_EMAIL"
    }
]

result = generate_mock_data(fields, rows=100)
print(f"Generated {len(result['data'])} records")

JavaScript/Node.js Client Example

const axios = require('axios');

async function generateMockData(fields, rows = 10, format = 'JSON') {
  try {
    const response = await axios.post('http://localhost:8843/generate', {
      fields: fields,
      rows: rows,
      format: format
    });
    
    return response.data;
  } catch (error) {
    throw new Error(`API Error: ${error.response?.data?.error || error.message}`);
  }
}

// Example usage
const fields = [
  {
    name: 'product_name',
    generator: 'STRING_GENERATOR',
    action: 'RANDOM_WORD'
  },
  {
    name: 'price',
    generator: 'STRING_GENERATOR',
    action: 'RANDOM_DECIMAL_NUMBER',
    parameters: [10.0, 1000.0, 2]
  },
  {
    name: 'currency',
    generator: 'MONEY_GENERATOR',
    action: 'RANDOM_CURRENCY_CODE'
  }
];

generateMockData(fields, 50)
  .then(result => {
    console.log(`Generated ${result.data.length} records`);
    console.log(result.data.slice(0, 3)); // Show first 3 records
  })
  .catch(error => console.error(error));

Development

Running Tests

# Start the API server
python api_server.py

# In another terminal, run tests
python test_api.py

Production Deployment

For production use, deploy with a proper WSGI server like Gunicorn:

pip install gunicorn
gunicorn -w 4 -b 0.0.0.0:8000 api_server:app

Developer Notes

About the Developer: I'm primarily a C# and Java developer who codes Python as a hobby. This project represents my exploration into Python development.

AI-Generated Code: Most of this codebase has been generated with AI assistance. While thoroughly tested, there may be bugs or non-idiomatic Python patterns. Contributions and improvements are welcome!

Code Quality: As this is a hobby project with AI-generated components, please review code carefully before using in production environments. Feel free to submit issues or pull requests for any improvements.

🤔 Frequently Asked Questions (FAQ)

Q: How to generate fake user data for testing?

A: Use the PERSON_GENERATOR with actions like RANDOM_PERSON_FIRST_NAME, RANDOM_PERSON_LAST_NAME, and RANDOM_EMAIL to create realistic user profiles.

Q: Can I generate test data for databases?

A: Yes! Export data in SQL format or use JSON/CSV to import into MySQL, PostgreSQL, MongoDB, or any database.

Q: How to create mock API responses?

A: Use the REST API endpoints to generate JSON data that matches your API schema requirements.

Q: Is this free to use commercially?

A: Yes, this is open source software free for both personal and commercial use.

Q: How to generate credit card numbers for testing?

A: Use MONEY_GENERATOR with RANDOM_CREDIT_CARD_NUMBER action. Note: These are fake numbers for testing only.

Q: Can I generate addresses and phone numbers?

A: Yes, use GEO_GENERATOR for addresses and IT_GENERATOR for phone numbers with custom patterns.

Q: How to generate large datasets?

A: The API supports up to 100,000 rows per request. For larger datasets, make multiple requests.

Q: Does it work with Postman/Insomnia?

A: Yes! Use the REST API endpoints in any HTTP client. Check /swagger for interactive documentation.

🏷️ Tags & Keywords

Mock Data Generator, Fake Data Generator, Test Data Generator, Random Data Generator, Sample Data Creator, Dummy Data Generator, API Testing Tool, Database Seeding Tool, JSON Generator, CSV Generator, Python Mock Data, REST API Testing, Test Data Management, QA Testing Tool, Development Tool, Data Generation API, Faker Alternative, Mock Server, Test Fixtures Generator

License

This project is open source. Feel free to use it for your development and testing needs.

Support

For issues, feature requests, or questions:

Create an issue in the repository
Check the API documentation at /docs
Test endpoints using the provided examples

Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
.github/workflows		.github/workflows
.vscode		.vscode
mockachu		mockachu
tests		tests
.gitignore		.gitignore
CONTRIBUTING.md		CONTRIBUTING.md
GITHUB_SEO.md		GITHUB_SEO.md
LICENSE		LICENSE
MANIFEST.in		MANIFEST.in
Makefile		Makefile
README.md		README.md
api.py		api.py
app.py		app.py
build.spec		build.spec
build_enhanced.py		build_enhanced.py
mockachu.manifest		mockachu.manifest
mockachu_app.py		mockachu_app.py
pyproject.toml		pyproject.toml
pytest.ini		pytest.ini
requirements.txt		requirements.txt
run_tests.py		run_tests.py
test_copy_functionality.py		test_copy_functionality.py
version_info.txt		version_info.txt

Folders and files

Latest commit

History

Repository files navigation

Mockachu - Mock Data Generator | Fake Data Generator | Test Data Generator

What is Mockachu?

Perfect for:

🚀 Key Features & Capabilities

🖥️ Desktop Application (GUI)

🌐 REST API for Developers

💡 Popular Use Cases & Examples

For Developers

For QA Engineers & Testers

For Data Analysts & Scientists

Common Search Terms This Tool Helps With:

📦 Installation

Pre-built Executables (No Python Required)

Download Links

Installation Instructions

From PyPI (Recommended for Developers)

From Source

🔒 Security Information

Pre-built Executable Security Warnings

macOS

Windows

Linux

Why These Warnings Occur

Alternative: Run from Source

Quick Start

Desktop Application

API Server

API Documentation

Base URL

Authentication

🔍 GET / - API Information

💚 GET /health - Health Check

🛠️ GET /generators - Available Generators

🎲 POST /generate - Generate Mock Data

API Examples

Basic Person Data

Numbers with Parameters

Geographic Data with Patterns

Currency and Financial Data

Available Generators

Error Handling

400 Bad Request

500 Internal Server Error

Limits

Python Client Example

JavaScript/Node.js Client Example

Development

Running Tests

Production Deployment

Developer Notes

🤔 Frequently Asked Questions (FAQ)

Q: How to generate fake user data for testing?

Q: Can I generate test data for databases?

Q: How to create mock API responses?

Q: Is this free to use commercially?

Q: How to generate credit card numbers for testing?

Q: Can I generate addresses and phone numbers?

Q: How to generate large datasets?

Q: Does it work with Postman/Insomnia?

🏷️ Tags & Keywords

License

Support

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Topics

Resources

License

Contributing

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