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Optimized the \`manual_lending\` route by replacing O(N) loop-based database lookups with efficient MongoDB aggregation pipelines. This reduces the number of database roundtrips from O(N) to O(1), significantly improving page load performance when many active lendings or recent consumable usages exist. - Replaced active tool lending loop with aggregation using \$lookup and \$project. - Replaced recent consumable usage loop with aggregation using \$lookup and \$project. - Maintained existing sorting logic and data structure for full compatibility. Co-authored-by: Woschj <81321922+Woschj@users.noreply.github.com>
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The `manual_lending` route in `app/routes/admin/system.py` suffered from a classic N+1 query problem. For every active lending and every recent consumable usage displayed on the page, the application performed two additional `find_one` queries to retrieve tool/consumable and worker names.
This optimization replaces these iterative lookups with two single MongoDB aggregation pipelines. By using `$lookup` (joins) and `$project` (formatting), we've moved the data association to the database layer.
Performance Impact:
Verification was performed using a benchmark script in `mongomock` to ensure data correctness and logic parity.
PR created automatically by Jules for task 755098390866371333 started by @Woschj