Architecture

Architecture

The architecture of Expense Tracker is designed to be clean, modular, and student-developer friendly. This is how all the moving parts sync all up.

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🧠 Core Components

Module	Description
app.py	Main entry point. Ties everything together.
backend/	Handles income/expense data, filtering logic, calculations.
data/	Stores user session data in local files (JSON/CSV).
ui/	Streamlit layout logic, input widgets, and chart rendering.

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🧩 Architecture Breakdown

1. Backend Layer

• Written in Python

• Uses Pandas for data manipulation

• Functions include:

  • add_income()

  • add_expense()

  • load_data()

  • filter_data()

2. Data Storage

• JSON files used for local storage

• Optimized to be storage-lite

• Easy to extend into cloud (Firebase, Supabase, etc.)

3. UI Layer (Streamlit)

• Renders user input fields, charts, filters

• Reacts to changes in real-time

• Responsive and intuitive flow for users

4. Visualization Layer

• Uses Matplotlib + Plotly to render:

  • Pie Charts

  • Bar Graphs

  • Line Charts

• All updates reflect user interactions instantly

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🔐 Security & Privacy

• No third-party storage by default

• All data saved locally

• No analytics, tracking, or shady background jobs

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