Generate realistic synthetic datasets with a simple and powerful API.

DataForge is a modern Python library for generating realistic fake datasets for testing, machine learning, software development, education, and demonstrations.

• Generate thousands of records in seconds
• Simple and intuitive API
• Export to CSV
• Export to JSON
• Export to Excel (.xlsx)
• Export to SQLite
• Custom schemas
• Built on top of Pandas
• Cross-platform

pip install dataforge

Or install locally

git clone https://github.com/yourusername/DataForge.git

cd DataForge

pip install -e .

from dataforge import forge

df = forge(
    rows=100,
    schema={
        "name": "name",
        "email": "email",
        "phone": "phone",
        "salary": "salary"
    }
)

print(df.head())

from dataforge import forge

df = forge(
    rows=500,
    schema={
        "name":"name",
        "email":"email"
    }
)

df.to_csv("users.csv", index=False)

df.to_excel("users.xlsx", index=False)

df.to_json("users.json")

• CSV Export
• JSON Export
• Excel Export
• SQLite Export
• YAML Schema
• REST API
• CLI Tool
• AI Dataset Generator
• PostgreSQL Export
• MongoDB Export

DataForge/
│
├── dataforge/
├── examples/
├── tests/
├── docs/
├── README.md
├── setup.py
└── pyproject.toml

• Python 3.10+
• Pandas
• Faker
• OpenPyXL

MIT License

Khan Aatif

Pull requests are welcome.

If you find bugs or have feature requests, please open an issue.