Expense Tracking System

An Expense Tracking System built using Python, Streamlit, and FastAPI that helps users manage, analyze, and visualize their spending habits efficiently.
It provides an intuitive interface to add, update, and view expenses, attach notes, and view category-wise analytics (including total spent and percentage breakdown) with a visual bar chart representation.

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🖥️ Project Overview

The Expense Tracking System simplifies managing daily expenses by allowing users to input transactions along with categories and notes.
It also offers powerful analytics for a selected date range, showing:

• Total amount spent per category
• Percentage share of each category
• A clean, interactive bar chart visualization

The system supports persistent data storage using MySQL and ensures smooth integration between backend and frontend via FastAPI.

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⚙️ Tech Stack & Libraries Used

Technology / Library	Purpose
Python	Core programming language used for the entire project
Streamlit	Used for building the interactive web-based frontend interface
Pandas	Used for managing, processing, and analyzing tabular expense data
Pydantic	Used for validating data models in the backend (FastAPI)
FastAPI	Provides the backend API endpoints for managing and retrieving expense data
Requests	Used for making API calls between the Streamlit frontend and FastAPI backend
mysql-connector-python	Used to connect and interact with the MySQL database where expenses are stored
Pytest	Used for writing and running automated backend tests

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🌟 Main Features

🔹 Add / Update Expenses

• Enter the amount, category, and notes for each expense.
• Modify or add new entries dynamically.
• Supports categories like Rent, Food, Shopping, Entertainment, and more.

🔹 Category Selection

• Choose predefined categories via dropdown menus.
• Easily editable and extendable for new categories.

🔹 Notes Field

• Add custom notes for each expense entry (e.g., "Groceries for the week" or "Monthly rent payment").

🔹 Expense Analytics

• Select a date range to view summarized analytics.
• Displays a bar chart showing percentage share of each category.
• A table view lists category-wise totals and percentages for quick reference.

🔹 Persistent Data Storage

• All expense entries are stored securely in a MySQL database.

🔹 Automated Testing

• Backend routes and logic are verified using Pytest to ensure reliability.

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📊 Example Screenshots

➕ Add/Update Expenses

📈 Analytics Dashboard

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🚀 How to Run the Project

1️⃣ Clone the Repository

git clone https://github.com/4nshhh/Expense-Tracking-System.git
cd Expense-Tracking-System

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Run the Backend (FastAPI)

cd "./backend"
uvicorn server:app --reload

4️⃣ Run the Frontend (Streamlit)

cd "./frontend"
streamlit run app.py

🧑‍💻 Author

GitHub: 4nshhh

📚 Future Improvements

• Add authentication (login/signup)

• Export analytics reports as PDF/CSV

• Add pie chart visualization

• Enable category customization