ojt-data-generator 0.1.1

A powerful Python package for generating realistic fake data with 6 pre-built templates - perfect for testing, development, and prototyping

🎲 OJT Data Generator

A powerful and easy-to-use Python package for generating realistic fake data for testing, development, and prototyping. Built with Python's Faker library and Pandas, OJT Data Generator provides an interactive command-line interface and programmatic API to quickly generate structured datasets for various use cases.

🎯 Why OJT Data Generator?

Whether you're building a new application, testing database schemas, creating demos, or learning data analysis, you need realistic sample data. OJT Data Generator makes this process effortless by providing:

• Pre-built Templates: 6 ready-to-use data templates covering common use cases
• Interactive CLI: User-friendly command-line interface requiring no coding
• Programmatic API: Import and use in your Python scripts for automation
• Reproducible Data: Set seeds to generate consistent datasets
• Export Ready: Save generated data directly to CSV files
• Pandas Integration: Data returned as pandas DataFrames for easy manipulation

✨ Features

Generate realistic fake data with 6 pre-built templates:

• 👤 User Data - Full name, username, email, phone number, gender, date of birth
• 💼 Employee Data - Full name, employee ID, company email, department, salary
• 🎓 Student Data - Full name, student ID, GPA, academic year
• 📦 Product Data - Product name, price, stock quantity
• 🏦 Bank Account Data - Account number, account holder, balance
• 🏥 Patient Data - Full name, patient ID, height (cm), weight (kg)

📦 Installation

pip install ojt-data-generator

🚀 Quick Start

After installation, simply run the interactive CLI:

ojt

The tool will guide you through:

1. Selecting a data template
2. Choosing the number of rows to generate
3. Optionally setting a seed for reproducible data
4. Viewing the generated data
5. Saving to CSV if needed

💡 Example Usage

$ ojt
Select a template:
1. User
2. Employee
3. Student
4. Product
5. Bank Account
6. Patient
Enter template number: 1
Number of rows (default 1): 5
Seed (optional): 42

# Generated data will be displayed as a pandas DataFrame
# Option to save as CSV file

🔧 Use as a Library

You can also import and use OJT in your Python scripts for automation:

from ojt import generate_data, TEMPLATE_NAMES
import pandas as pd

# Generate 10 user records with a seed for reproducibility
data = generate_data(template_number=1, n_rows=10, seed=42)
df = pd.DataFrame(data)
print(df)

# Save to CSV
df.to_csv('users.csv', index=False)

# Generate employee data
employee_data = generate_data(template_number=2, n_rows=50)
employees_df = pd.DataFrame(employee_data)

# Generate student data for testing
student_data = generate_data(template_number=3, n_rows=100, seed=123)
students_df = pd.DataFrame(student_data)

📊 Template Details

1. User Template

Perfect for user registration, authentication systems, and social platforms.

• Full Name
• Username
• Email Address
• Phone Number
• Gender (male/female/other)
• Date of Birth (ISO format)

2. Employee Template

Ideal for HR systems, payroll applications, and organizational databases.

• Full Name
• Employee ID (8-character UUID)
• Company Email
• Department (HR/Engineering/Sales)
• Salary ($30,000 - $120,000)

3. Student Template

Great for educational platforms, learning management systems, and academic tools.

• Full Name
• Student ID (5-digit number)
• GPA (2.0 - 4.0)
• Academic Year (1-4)

4. Product Template

Useful for e-commerce platforms, inventory systems, and retail applications.

• Product Name
• Price ($100 - $5,000)
• Stock Quantity (0-1,000 units)

5. Bank Account Template

Perfect for financial applications, banking systems, and payment platforms.

• Account Number (8-digit)
• Account Holder Name
• Balance ($0 - $1,000,000)

6. Patient Template

Designed for healthcare applications, medical records, and health tracking systems.

• Full Name
• Patient ID (8-character UUID)
• Height (50-200 cm)
• Weight (3-150 kg)

🎓 Use Cases

• Software Testing: Generate test data for unit tests, integration tests, and QA
• Database Seeding: Populate development and staging databases
• Demos & Presentations: Create realistic demo data for product showcases
• Learning & Training: Practice data analysis, SQL queries, and data visualization
• Prototyping: Quickly mock up applications with realistic data
• API Testing: Generate payloads for API endpoint testing

📋 Requirements

• Python >= 3.7
• faker >= 18.0.0
• pandas >= 1.3.0

🤝 Contributing

Contributions are welcome! Feel free to open issues or submit pull requests.

📄 License

MIT License - see LICENSE file for details

👨‍💻 Author

Kushal Kotiny

🔗 Links

• PyPI: https://pypi.org/project/ojt-data-generator/
• GitHub: https://github.com/kushalkotiny/ojt