🧾 Billing Analytics Automation — Python

📌 Project Overview

A desktop-based Automated Billing System built with Python and Tkinter. It allows businesses to manage customer transactions, select products across categories, auto-calculate taxes, and generate itemized bills — all through a clean GUI interface.

🛠️ Tools & Technologies

Tool	Purpose
Python	Core programming language
Tkinter & ttk	GUI / Desktop interface
String & Float parsing	Data calculation logic
OOP & Event-driven programming	App architecture

📊 Key Features

• ✅ 3-level product selection — Category → Subcategory → Product
• ✅ Dynamic dropdowns — subcategory and product lists update automatically
• ✅ Cart system — Add multiple items with price × quantity calculation
• ✅ Auto tax calculation — 18% GST applied on subtotal
• ✅ Bill area — Live text display of all cart items
• ✅ Action buttons — Add to Cart, Total, Print, Save, Clear, Email, Exit
• ✅ Customer details form — Name, Phone, Bill Number with Search

🗂️ Product Catalogue (Built-in)

Category	Subcategory	Sample Products
Electronics	Mobile, Headphone, Earbuds	iPhone, Sony WH-1000XM4, AirPods
Clothing	Pant, Shirt, T-Shirt	Jeans, Formal Shirt, Polo T-Shirt
Books	Fiction, Sci-Fi, Drama	1984, Dune, Hamlet

📁 Project Structure

Billing-Analytics-Automation/ │ ├── main.py # Full application — GUI + logic ├── main.py.zip # Compressed version └── README.md # Project documentation

🚀 How to Run

# No external libraries needed — uses Python standard library only
python main.py

Requires Python 3.x installed on your system.

🧠 Logic Highlights (For Technical Reviewers)

• add_to_cart() — calculates price × quantity and appends to bill textarea
• calculate_total() — parses bill text, sums all Total Price lines, applies 18% GST
• category_selected() / subcategory_selected() — event-driven cascade filtering
• clear_fields() — resets all form fields and bill area to default state

📈 Business Value

Simulates a real retail POS (Point of Sale) system used in shops, pharmacies, and billing counters. Demonstrates skills in:

• Data input validation & processing
• Business rule implementation (tax logic)
• User interface design for non-technical end users

👩‍💻 Author

Arifa Sarkar — Aspiring Data Analyst
GitHub