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## 2024-05-25 - Avoid lambda functions in sorting loops
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**Learning:** In sorting operations over large lists (e.g. `events.sort` and `pending_metas.sort`), Python `lambda` functions combined with dynamic function calls or dict.get methods introduce unnecessary interpreter overhead. Specifically, using inline tuples with a pre-computed dictionary (`_priority_map.get`) instead of an inline function (`get_priority`) inside the sort key lambda reduces execution time by over ~50%, while `operator.itemgetter` completely bypasses Python function call overhead.
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**Action:** Always prefer `operator.itemgetter` for basic dict access in sort keys, and when mapping categorical priorities, use a predefined constant dictionary map inline rather than calling a local `def` function inside the lambda.
**Learning:** Checking for JSON string length before `json.loads("{}")` prevents throwing heavy exceptions inside tight mapping loops resulting in up to 10-15x iteration parsing speeds. Using inline bounders (`if raw_score < 1.0 else 1.0`) avoids Python C-API calls that exist using `min()` resulting in ~2.5x loop performance.
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**Action:** Extract inline checks before triggering expensive parsers (`json.loads`) inside tight loops to avoid exceptions, and replace global static mapping dictionaries (`_PHASE_WEIGHTS.get`) with explicit if-elif variable assignments inside hot functions.
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