The Processing Pipeline

Data Pipeline Workflow

We utilize an entirely uncoupled architecture focused heavily on extreme durability over varying data sources.

Data Extraction (Scraping)

Python-based scraping agents configured inside GitHub Actions run on automated chron jobs. These agents are instructed to safely gather source data and intercept unstable updates from legacy infrastructure naturally.

Data Normalization

Once the source logic is acquired, rigid validation scripts normalize the resulting string feeds into standardized JSON outputs enforcing standard structural formats (e.g. strict boolean states, ISO 8601 datetimes).

CDN Edge Deployment

Finally, those generated structures are committed as static assets and synced instantly via Cloudflare Pages. This shifts all rendering and querying bandwidth directly out to the edge network resulting in practically zero load times.

Error Handling

Failures across the extraction step immediately abort the deployment phase. This ensures that the last known good configuration of data natively stays live until an automated correction is deployed.