django-recommender-search-backend-patterns

Experimental Django Recommender + Search Backend Best Practices

Implementation patterns for a Django backend serving mixed-results recommendations (Personalize / Databricks / microservice fan-out) and OpenSearch-backed search/feeds. 48 rules across 8 categories, ordered by execution lifecycle impact — earlier categories cascade through everything downstream.

This is the backend peer of the react-fetch-cache-patterns skill. React handles client-side waterfalls and caching; this skill handles server-side fan-out, downstream protection, OpenSearch query design, and ML-blend orchestration.

When to Apply

• Building or reviewing Django views that fan out to AWS Personalize, Databricks Model Serving, internal microservices, or any ML inference downstream
• Designing OpenSearch query endpoints (search results, infinite feeds, faceted search)
• Implementing a recommendations endpoint that blends multiple ranker outputs
• Investigating "Django backend slow when downstream is degraded" or "Personalize quota exhausted"
• Adding caching, retry, circuit breakers, or rate limiting to outbound calls
• Choosing between sync and async Django views, configuring uvicorn vs gunicorn
• Designing DRF response shapes for paginated feeds, partial results, or degraded paths

Rule Categories by Priority

Quick Reference

1. Fan-out Orchestration (CRITICAL)

• orch-parallel-fanout-asyncio-gather — Use asyncio.gather for independent downstream calls; never await sequentially
• orch-return-exceptions-on-fanout — return_exceptions=True so one failure doesn't poison the whole gather
• orch-propagate-request-deadline — Pass a deadline through every downstream call to bound whole-request latency
• orch-reuse-async-clients — One httpx.AsyncClient per downstream at module scope; never per-request
• orch-bounded-fanout-concurrency — Cap per-request fan-out with asyncio.Semaphore to protect the pool
• orch-no-blocking-in-async-view — Never block the event loop with sync ORM/IO in async views
• orch-avoid-await-in-loop — for item in items: await ... is serial; use asyncio.gather with comprehension
• orch-batch-with-bulk-endpoint — Bulk endpoint over N parallel calls; DataLoader pattern for batchers