⚡ Bolt: [O(N*M) to O(N) loop optimization]#147
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Replaced O(N*M) nested loops with O(N) hash map lookups in MaterialExtractor and RAGIndexer to improve performance when matching solutions to exercises. Co-authored-by: glacy <1131951+glacy@users.noreply.github.com>
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Pull request overview
This PR optimizes solution-to-exercise matching by replacing per-exercise linear scans over solutions (nested loops) with precomputed dictionaries for near O(1) lookups, reducing total matching time to O(N+M) in the extraction/indexing pipeline.
Changes:
- Optimized
MaterialExtractor.get_all_exercisesby precomputingsolutions_by_label(preserving first-match semantics for duplicates). - Optimized
RAGIndexer.index_materialssolution matching similarly, alongside substantial formatting/quoting normalization. - Added a small performance benchmark script and recorded the optimization as a “Bolt” learning.
Reviewed changes
Copilot reviewed 4 out of 4 changed files in this pull request and generated 5 comments.
| File | Description |
|---|---|
test_perf.py |
Adds a benchmark comparing nested-loop matching vs dict lookup matching. |
evolutia/rag/rag_indexer.py |
Uses a solutions-by-label dict to avoid O(N*M) matching during indexing; also reformats and normalizes quoting. |
evolutia/material_extractor.py |
Uses a solutions-by-label dict to avoid O(N*M) matching when assembling exercises. |
.jules/bolt.md |
Documents the O(N*M)→O(N) lookup optimization learning/action. |
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| from pathlib import Path | ||
| from typing import Dict, List, Any | ||
| import hashlib |
| def index_exercise( | ||
| self, exercise: Dict, analysis: Dict, metadata: Dict = None | ||
| ) -> List[str]: |
| """Limpia la colección (útil para re-indexar).""" | ||
| collection_name = self.collection.name | ||
| self.client.delete_collection(name=collection_name) | ||
| _ = self.config.get("vector_store", {}) | ||
| self.collection = self.client.create_collection( |
| try: | ||
| cache_entry = self._file_cache[file_path] | ||
| _ = self._file_cache[file_path] | ||
| file_mtime = file_path.stat().st_mtime |
| import time | ||
|
|
||
| materials = [{ | ||
| 'file_path': 'test.md', | ||
| 'frontmatter': {}, |
💡 What: Replaced$O(N \times M)$ nested loops with $O(N)$ hash map lookups when matching solutions to exercises in $O(N \times M)$ performance bottleneck. A hash map allows for $O(1)$ lookups, bringing the total time to $O(N + M)$ .
MaterialExtractorandRAGIndexer.🎯 Why: The original nested loop iterated through all solutions for each exercise, causing an
📊 Impact: Expected to significantly reduce processing time for materials with many exercises and solutions. In a synthetic test with 1000 items, time dropped from ~0.08s to ~0.001s.
🔬 Measurement: Verified via custom performance benchmark script. The optimization was successfully tested and no regressions were introduced. Format and lint checks have been applied.
PR created automatically by Jules for task 11832616852439219504 started by @glacy