🏦 Banking System (Streamlit App)

A feature-complete Banking System MVP built using Python + Streamlit, supporting core banking operations such as user login, fund transfers, balance checks, transaction history, and PDF statement downloads.

This project intentionally demonstrates two database implementations to reflect real-world development and deployment constraints.

🚀 Features

• User login and account access
• Pre-loaded demo users (alice, bob, charlie)
• Send and receive money between users
• Real-time balance updates
• Transaction history tracking
• Downloadable bank statement (PDF)
• Modular backend design

🧱 Project Structure

Banking-System/
│
├── app.py          # PostgreSQL-based implementation (local development)
├── app1.py         # SQLite-based implementation (deployment-friendly)
├── db.py           # Database helper functions (PostgreSQL)
├── pdf_utils.py    # PDF statement generation
├── schema.sql      # PostgreSQL database schema
├── requirements.txt
├── README.md

🗄️ Database Implementations (Important)

This project contains two working database approaches, each used for a specific purpose.

🔹 1. PostgreSQL Version (Host Machine / Local Development)

Files involved:

• app.py
• db.py
• schema.sql

How this version works:

• Uses PostgreSQL installed on the host machine
• Database schema is defined in schema.sql
• Credentials are configured locally
• Full relational database behavior is supported

Why this version exists:

• Represents a proper backend architecture

• Shows experience with:

  • Relational databases
  • SQL schema design
  • Persistent data storage

• Suitable for:

  • Local development
  • Academic projects
  • Backend system design demonstrations

⚠️ Note: This version is not deployed publicly, as Streamlit Cloud does not support external database services directly.

🔹 2. SQLite Version (Streamlit Cloud / Public Deployment)

File involved:

• app1.py

Why SQLite was used:

• Streamlit Cloud does not allow uploading or managing external databases
• Environment variables and persistent DB services are restricted
• SQLite allows the app to run out-of-the-box for any viewer

How this version works:

• Uses SQLite as an embedded database
• Database and tables are created automatically at runtime
• Demo users (alice, bob, charlie) are inserted programmatically
• All banking features remain identical to the PostgreSQL version

This is the version used for:

• GitHub hosting
• Streamlit Cloud deployment
• Public demos and portfolio viewing

🔄 Why Two Versions?

This dual-approach reflects real-world engineering trade-offs:

Environment	Database
Local / Host Machine	PostgreSQL
Cloud / Public Deployment	SQLite

Instead of removing PostgreSQL, the project adapts to deployment constraints while preserving backend design integrity.

This demonstrates:

• Practical problem solving
• Deployment awareness
• Production-safe decision making

▶️ How to Run

Run SQLite Version (Recommended for GitHub / Streamlit)

streamlit run app1.py

No setup required.

Run PostgreSQL Version (Local Machine Only)

1. Install PostgreSQL
2. Create database using schema.sql
3. Configure credentials in db.py
4. Run:

streamlit run app.py

📄 PDF Statements

Users can download their transaction history as a PDF bank statement, generated using pdf_utils.py.

🧠 Key Takeaways

• Demonstrates backend + frontend integration
• Shows adaptability across environments
• Clean separation of concerns
• Production-aware architecture choices