An interactive full-stack web dashboard designed for Grazioso Salvare to streamline animal rescue data analysis. This application bridges raw database records with actionable insights, allowing shelter staff to identify search-and-rescue candidates in seconds.
- Framework: Dash (View & Controller)
- Database: MongoDB (Model)
- Data Processing: Python, Pandas, Pymongo
- Visualization: Plotly (Charts), Dash Leaflet (Geolocation)
- Dynamic Filtering: Real-time data filtering for specific rescue profiles (Water, Mountain/Wilderness, Disaster/Tracking).
- Interactive Visualization: Includes a paginated DataTable, breed-breakdown pie charts, and responsive geolocation mapping.
- Full-Stack MVC Architecture: Modular design separating the database logic (Model) from the UI and application flow (View & Controller).
- Robust Error Handling: Implements dynamic index-checking logic to maintain application stability during rapid UI state changes and data filtering.
The application utilizes an MVC (Model-View-Controller) pattern:
- Model: MongoDB provides a flexible, document-oriented storage solution, allowing for seamless mapping of semi-structured animal shelter data to Python dictionaries.
- View: Dash enables the construction of responsive, high-performance web interfaces using pure Python.
- Controller: Dash
@app.callbackdecorators manage the application state, handling user interactions and triggering targeted database queries.
Default/Reset State:
Water Rescue:
Mountain or Wildlife Rescue:
Disaster of Individual Tracking:
Map Interaction:
