datagen-cli 0.2.0

A colorful and interactive CLI tool to generate customizable synthetic datasets.

Schema-driven synthetic data generation for developers & data scientists

⚡ Python API & CLI • 📊 DataFrame Ready • 🔍 Strict Validation • 📁 CSV / JSON / Excel

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🚀 DataGen CLI

Built an official Python library with 12K+ downloads — designed to solve a real problem faced by data science students and developers:
getting clean, structured, and usable datasets instantly.

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✨ About

Most tools generate random, unrealistic data.

DataGen CLI is different.

👉 Define your own schema
👉 Generate meaningful, constraint-aware datasets
👉 Use directly in Python or via CLI

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🔥 Key Features

• 🧠 Schema-driven generation
• 📊 Returns pandas DataFrame
• 💻 Python + CLI support
• 📁 Export to CSV, JSON, Excel
• 🔍 Strict validation system
• ⚡ Lightweight & fast
• 🧪 Fully tested (24/24 tests passed)

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⚡ Quick Demo

🐍 Python

from datagen import generate_dataset

schema = {
    "rows": 5,
    "columns": [
        {"name": "name"},
        {"name": "age", "generator": "int", "params": {"min": 18, "max": 60}},
        {"name": "salary", "generator": "int", "params": {"min": 30000, "max": 100000}}
    ]
}

df = generate_dataset(schema)
print(df)

💻 CLI

datagen generate schema.json --rows 100 --output data.csv

🧾 Example Output

        name   age    salary
0   Rahul Sharma   25   54000
1   Priya Verma   32   72000
2   Aman Gupta    28   61000

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🧩 Architecture

datagen/
│
├── core/
│   ├── engine.py
│   ├── defaults.py
│   ├── schema_normalizer.py
│   └── schema_validator.py
│
├── cli/
│   ├── app.py
│   └── main.py
│
├── __init__.py
│
tests/
├── test_cli.py
└── test_core.py

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⚙️ Phase 1 — Core Engine (Completed ✅)

✔️ Implemented

• Schema-driven engine (DataGenerationEngine)
• Python API (generate() → DataFrame)
• CLI (Typer-based interface)
• Schema normalization
• Strict validation system
• File export support
• Testing suite

🔒 Validation Rules

• ✔️ min <= max for numeric fields
• ✔️ Precision must be positive
• ✔️ Date ranges must be valid
• ✔️ Choice fields must not be empty
• ✔️ Unsupported types are rejected

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🚀 Installation

pip install datagen

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💻 CLI Commands

Command	Description
generate	Generate dataset
preview	Preview sample data
validate	Validate schema

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📤 Export Formats

• CSV
• JSON
• Excel (.xlsx)

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⚡ Performance

• ⚡ Lightweight package (KBs only)
• 🚀 Tested with 1 crore rows × 17 columns
• 🧠 Efficient memory usage

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🔮 Roadmap

Phase 2 (Next)

• 🌍 Region-based datasets (India 🇮🇳, US 🇺🇸)
• 🔗 Relationship-aware data (city → state, salary → role)

Phase 3

• 🤖 Smart generation (learning from real datasets)

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🧪 Testing

24 passed, 0 failed ✅

Includes:

• Core engine tests
• CLI tests
• Validation tests

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🤝 Contributing

git clone https://github.com/your-username/datagen-cli
cd datagen-cli
pip install -r requirements.txt

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👨‍💻 Author

Rishabh Kumar

• Built to solve a real-world problem faced during learning data science
• Already helping thousands generate datasets instantly
• Now evolving into a full-scale synthetic data engine

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⭐ Support

If this project helped you:

👉 Star the repo
👉 Share it
👉 Use it in your projects

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💡 Vision

Data shouldn't be the bottleneck.
It should be generated instantly.