Django DB-Side Computation

Use this skill when Django fetches rows into Python to compute values the database can compute more efficiently or more consistently.

Workflow

1. Identify the Python computation.

   • Counts, sums, min/max, booleans, latest related rows, rankings, denormalized totals, or per-row derived fields.
   • Confirm whether the computed value must be exact, current, and transactionally consistent.

2. Pick the SQL expression level.

   • filter(), exclude(), and F() for simple comparisons and updates.
   • annotate() and aggregates for per-object counts and totals.
   • Filtered aggregates for conditional counts and sums.
   • Exists() for yes/no related-row checks.
   • Subquery() with OuterRef() for latest or scalar related values.
   • Window() for ranks and running calculations.
   • GeneratedField for deterministic same-row computed columns when the database supports it.

3. Validate query shape.

   • Inspect generated SQL or QuerySet.explain().
   • Clear unintended ordering before grouping when needed.
   • Confirm indexes support joins, filters, and ordering.

4. Decide whether the result should be stored.

   • Use annotations for request-time values.
   • Use generated fields for same-row deterministic values.
   • Use materialized views or denormalized tables when cross-row aggregate queries are too expensive and can be stale.

See aggregation-patterns.md for Django expression examples.

Safety Notes

• Database computation is not always faster; complex queries can overload the database or block OLTP work.
• Generated fields have database-specific restrictions and PostgreSQL supports only persisted generated columns.
• Subqueries and annotations can duplicate work if composed carelessly. Read the plan.

Verification

Compare correctness against the old Python calculation on representative data, then measure SQL time and total response time.