datagen-cli 0.1.3
A colorful and interactive CLI tool to generate customizable synthetic datasets.
License: MIT
Requires Python: >=3.8
Keywords: dataset, data-generator, cli, faker, synthetic-data

# DataGen CLI — Synthetic Dataset Generator

**Created by:** Rishabh Kumar  
**Version:** 0.1.3 
**License:** Rishabh License --MIT(Non-Commercial) (For commercial use need to contact the developer)

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## Command to Run

Once installed, simply launch the generator using: datagen

```bash
datagen
## Overview

DataGen CLI is a command-line tool that allows you to generate synthetic datasets with customizable columns, formats, and sizes.  
It is designed for developers, data analysts, and machine learning practitioners who need realistic data for testing, demonstrations, or prototyping.

---

## Features

- 50+ predefined column types (customer, sales, weather, system logs, etc.)
- Supports multiple output formats: CSV, Excel (XLSX), and JSON
- Interactive CLI prompts for easy configuration
- Color-coded terminal interface using Rich
- Custom date range support for time-based data
- Lightweight and fast (powered by Typer, Faker, and Pandas)

---

## Installation

Install directly from PyPI (once published):

```bash
pip install datagen-cli
Verify installation:


datagen --help
Quick Start


----- To generate your first dataset, run: datagen


Example Output in Terminal

────────────────────────────────────────────────────────────
        DataGen CLI - Synthetic Dataset Generator
────────────────────────────────────────────────────────────
Created by: Rishabh Kumar
Version: 0.1.3
Description: A CLI tool to generate customizable synthetic datasets
────────────────────────────────────────────────────────────
Use 'datagen --help' to see available commands

Tip: Run 'datagen generate' to create your first dataset.
────────────────────────────────────────────────────────────
Example Usage

Step 1: Start the Generator

datagen generate
Step 2: Follow Prompts
vbnet
Enter number of rows to generate: 10000
Enter start date (YYYY-MM-DD): 2022-01-01
Enter end date (YYYY-MM-DD): 2024-12-31

Available Columns:
1. OrderID   2. CustomerName   3. Country   4. Sales   5. Profit  ... up to 50
Enter column numbers to include (comma-separated): 1,2,4,5

Enter folder path to save file: ./data/
Enter file name: sample_sales
Choose file type (csv/xlsx/json): csv
Data is generated and saved automatically:


Data generated successfully and saved to: ./data/sample_sales.csv
Supported Column Types
Category	Example Columns
Customer Info	Name, Email, Gender, Age, Country, City
Sales Data	OrderID, Quantity, Sales, Profit, Discount
Employment	EmployeeName, Department, JobTitle, Salary
System Logs	IP_Address, Browser, DeviceType, LoginTime
Weather	Temperature, Humidity, WeatherCondition
Finance	AccountBalance, CreditScore, TransactionID
Miscellaneous	RandomText, BooleanFlag, Region, State

--- Total Columns: 50 predefined and ready to use.

Technical Details
Component	Library
CLI Framework	Typer
Terminal UI	Rich
Fake Data	Faker
Data Handling	Pandas
Excel Support	OpenPyXL

Developer Information
Author: Rishabh Kumar
Email: rishabh@example.com
GitHub: github.com/rishabhkumar

License
This project is licensed under the MIT License (if not for commercial use).
You are free to use, modify, and distribute this software(non-commercial).

---- For commercial use contact rishabh.contact.info@gmail.com

Contributing
Fork the repository

Create your feature branch (git checkout -b feature/new-feature)

Commit your changes (git commit -m 'Add new feature')

Push to the branch (git push origin feature/new-feature)


Notes--
Good datasets lead to better models.
DataGen CLI helps you build, test, and experiment faster with clean and realistic synthetic data.