Slippi Ranked South America Map 🐸

This project consists of an interactive map of Slippi Netplay players in South America, using data collected through web scraping techniques and processed in a spatial database system.

The interactive map can be viewed at: vagnertxr.github.io/game_map/.

Functioning and Architecture

The project is structured as an automated data pipeline (ETL):

• Data Collection: Uses Python to scrape an online player ranking available at Slippi SA Leaderboard
• Storage and Processing: Collected data is processed and stored in a PostgreSQL + PostGIS database
• Geospatial Data Publishing: Data is made available in GeoJSON format for application consumption using GeoServer
• Interactive Visualization: The map is built with the MapLibre GL JavaScript library, allowing fluid navigation and real-time data display

Automation

The data update routine is executed weekly on a local Linux server.

Execution flow:

• Weekly repository synchronization via scheduled routine
• Data scraping, processing and merging
• Update of spatial tables in the local database and its deployment as a layer in GeoServer
• Export of updated GeoJSON files locally
• Automatic deploy of new data to GitHub Pages

Technologies Used

Python: Data collection and processing

PostgreSQL + PostGIS: Spatial database

GeoServer: Geospatial data publishing

MapLibre GL: Interactive map data visualization