auto-claude: 021-consolidate-stats-overview-into-single-query-using #85
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…nditional aggregation - Import case from sqlalchemy for conditional aggregation - Consolidate total_messages, messages_24h, and duplicates_24h into single query - Use func.sum(case(...)) pattern for conditional counts - Reduce database round-trips from 4 to 2 - Keep active_channels query separate (different table) - Maintain user isolation via user_channels join Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
When the database has no messages, func.sum() returns NULL instead of 0. Wrap conditional aggregations with func.coalesce() to convert NULL to 0, ensuring the API always returns integers as expected. This follows the existing pattern in the codebase (see stats.py lines 236, 242). Fixes: test_overview_stats_empty_database Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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The
get_overview_statsendpoint inapp/api/stats.pyexecutes 4 separate sequentialawait db.execute()calls to compute total_messages, active_channels, messages_24h, and duplicates_24h. Each query independently joins through user_channels for user scoping, causing 4 full round-trips to the database. PostgreSQL's FILTER clause or CASE-based conditional aggregation can collapse the 3 message counts into a single query, reducing total DB round-trips from 4 to 2 (one for messages, one for channels).