healthflow-data-refresh

To safely refresh health data, implement atomic database writes using a temporary SQLite path and os.replace, preventing partial-update corruption. Combine this with a layered fetch, cache, and seed fallback strategy for reliable ETL pipelines.

The best way to handle HTTP fetch failures in an ETL pipeline is enforcing a deterministic fetcher contract where download functions return None on any failure. This is paired with guarded environment tokens, controlled httpx timeouts, and a SEED fallback mechanism.

Cached JSON data changes types because JSON serialization loses tuple and set semantics, converting them to lists. Ensuring cache correctness requires explicitly handling JSON round-trips to restore the intended list, tuple, or set behavior upon data rehydration.

Yes, you can use httpx to fetch public health datasets by configuring controlled timeouts and a layered fallback strategy. If the httpx download fails, the pipeline logs the degraded state and safely loads SEED data to maintain operations.

To implement TTL caching for API responses, use a load-or-fetch mechanism that checks cache age before making HTTP requests. This reduces external API calls and provides a valid cached layer when network fetches fail before falling back to seeds.

A limitation of atomic writes with SQLite is the requirement for temporary file handling and sufficient disk space for the .tmp file. This approach prevents partial database updates but requires careful path management during the os.replace operation.