Django Index Design

Use this skill to add or change indexes only after profiling shows a specific query can benefit. Indexes speed selected reads and constraints, but they add write cost, migration risk, and maintenance overhead.

Workflow

1. Start from a query plan.

• Capture the SQL, filters, joins, ordering, selected columns, table sizes, and current indexes.
• Confirm that the query is important enough to optimize.

1. Choose the index shape.

• Equality filters first, then range/order fields when useful.
• Match ORDER BY for LIMIT queries when possible.
• Use partial indexes for highly queried subsets.
• Use covering indexes only when selected columns are stable and index-only scans are plausible.
• Use GIN for JSONB containment, arrays, and full-text patterns; do not expect a B-tree to solve those.

1. Express the index in Django models or migrations.

• Prefer Meta.indexes for normal model-owned indexes.
• Prefer AddIndexConcurrently and RemoveIndexConcurrently for live PostgreSQL tables.
• Use raw SQL only when Django cannot express the index.

1. Validate on production-like data.

• Re-run QuerySet.explain() or EXPLAIN ANALYZE.
• Verify the planner uses the index for the target query.
• Check write-path impact when the indexed table is hot.

See index-patterns.md for index examples and migration templates.

Production Rules

• For PostgreSQL live tables, use concurrent index operations and set the migration atomic = False.
• Keep names short, stable, and explicit.
• Do not add duplicate indexes that are already covered by a unique constraint or a left-prefix composite index.
• Remove unused indexes only after checking production usage and deployment rollback needs.

Verification

Finish with before/after plan evidence, the exact migration operation, and the operational risk assessment for locks, writes, and rollback.