DEF CON Insights is a data analysis project that transforms DEF CON conference data into clean, structured formats for deeper exploration and visualization.

This repository currently provides scripts to fetch and process structured content (events, tags, speakers, locations) from DEF CON’s Firebase backend. A Quarto site with published statistics, trends, and visual insights is planned.

• Fetch raw data from DEF CON’s Firebase/Firestore
• Normalize and flatten nested fields into analysis-ready tables
• Combine multiple years for cross-year comparisons

scripts/
├── 01_fetch_firebase_data.py     # Downloads raw JSON data for a given DEF CON year
├── 02_process_defcon_data.py     # Transforms verbose Firestore exports into flat CSV/JSON
├── 03_combine_all_years.py       # Merges all processed files into a single dataset

run_pipeline.sh                    # Orchestrates the full data pipeline for selected DEF CON years

You can run the full pipeline for DEF CON 32 and 33 using:

bash run_pipeline.sh

This will:

1. Fetch raw data into data/raw/
2. Process cleaned files into data/processed/
3. Merge all processed years into data/combined/defcon_all_events.csv

This project leverages:

• Polars for fast, multi-threaded DataFrame transformations
• Requests to fetch raw JSON from Firebase
• Quarto (coming) for analysis notebooks and site publishing
• Plotnine (coming) for grammar-of-graphics plotting and visual insights

This project is MIT-licensed. See LICENSE for details.