LogiTrack : Inventory Management System

LogiTrack is a modern, web-based inventory management system built with Python and Streamlit. It provides real-time optimization of warehouse inventory distribution, order management, and supply chain analytics.

a) Features

1) Dashboard & Analytics

• Real-time inventory tracking
• Warehouse utilization metrics
• Order fulfillment statistics
• Supply chain performance indicators
• Interactive data visualizations

🗺2) Inventory Distribution

• Multi-warehouse optimization
• Geographic distribution mapping
• Cost-effective allocation algorithms
• Real-time route visualization

3) Order Management

• Order tracking and status updates
• Priority-based fulfillment
• Delivery deadline monitoring
• Automated allocation suggestions

4) Warehouse Management

• Capacity utilization tracking
• Stock level monitoring
• Storage cost optimization
• Location-based analytics

5) Supplier Management

• Supplier performance metrics
• Reliability scoring
• Lead time tracking
• Quality assessment

b) Getting Started

Prerequisites

• Python 3.9 or higher
• pip package manager
• Git (optional)

Installation

1. Clone the repository:

   git clone https://github.com/tanishpoddar/logitrack.git
   cd logitrack

2. Create and activate virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Run the application:

   streamlit run src/app.py

c) Project Structure

logitrack/
├── src/
│   ├── app.py              # Main Streamlit application
│   ├── backend/
│   │   ├── __init__.py
│   │   ├── data_loader.py  # Data handling and processing
│   │   └── optimizer.py    # Optimization algorithms
│   └── utils/
│       └── helpers.py      # Utility functions
├── data/
│   ├── sample_warehouses.csv
│   ├── sample_sales.csv
│   └── other sample data...
├── tests/
│   └── test files...
├── docs/
│   └── documentation files...
├── requirements.txt
├── README.md
└── LICENSE

d) Usage

1. Login: Enter your credentials to access the system.
2. Data Source: Choose between:
   • Sample data
   • Upload your data (CSV)
   • Database connection
3. Navigation: Use the sidebar to access different features:
   • Overview
   • Inventory Management
   • Order Management
   • Supplier Management
   • Optimization
   • User Guide

e) Data Format

Warehouse Data (CSV)

warehouse_id,name,capacity,current_stock,location,storage_cost,latitude,longitude
W001,Mumbai Central,10000,7500,Mumbai,1200,19.0760,72.8777
W002,Singapore Hub,15000,12000,Singapore,1500,1.3521,103.8198

Order Data (CSV)

order_id,date,product_id,quantity,delivery_deadline,status,delivery_latitude,delivery_longitude
ORD001,2025-03-24,P001,500,2025-03-26,Pending,19.0760,72.8777
ORD002,2025-03-24,P002,750,2025-03-25,Urgent,1.3521,103.8198

f) Configuration

The system supports various configuration options:

• Database connections (MySQL, PostgreSQL, SQLite)
• Optimization parameters
• Visualization preferences
• Time zone settings

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch:

   git checkout -b feature/AmazingFeature

3. Commit your changes:

   git commit -m 'Add some AmazingFeature'

4. Push to the branch:

   git push origin feature/AmazingFeature

5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Made with ❤️ by Tanish Poddar