⚡ Bolt: Optimize results filtering in fix_encoding.py

[daggerstuff]

💡 What: Refactored the results filtering blocks in print_results and save_results from using four separate list comprehensions to a single for loop that categorizes items into successful, failed, skipped, and fixed in one pass.

🎯 Why: The previous implementation traversed the results list 4 times (and its derived successful list twice) which was unnecessarily slow for larger inputs. By using a single loop, we avoid unnecessary iteration overhead.

📊 Measured Improvement: In a microbenchmark with a mock list of 100,000 generated results dicts run 100 times, the old method took ~1.68s while the new single-pass loop method took ~1.09s, yielding a measurable ~35% performance improvement in the execution time of that block.

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PR created automatically by Jules for task 15413752457738335225 started by @daggerstuff

Summary by Sourcery

Enhancements:

• Refactor results categorization in print_results and save_results to use a single-pass loop instead of multiple list comprehensions.

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Summary by cubic

Optimized results filtering in training/scripts/fix_encoding.py by switching print_results and save_results to a single-pass categorization. This cuts iteration overhead and speeds up large runs (~35% faster in microbenchmarks).

• Refactors
  • Consolidated filtering into one loop that builds successful, failed, skipped, and fixed in both print_results and save_results.
  • Minor cleanup: inlined the logger setLevel call.

^{Written for commit 7bfd665. Summary will update on new commits.}

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Project	Deployment	Actions	Updated (UTC)
ai	Error		Mar 31, 2026 7:43pm

[sourcery-ai]

Reviewer's Guide

Refactors results categorization in fix_encoding.py to use a single-pass loop for computing successful, failed, skipped, and fixed results, improving performance and slightly cleaning up logging configuration formatting.

File-Level Changes

Change	Details	Files
Optimize results categorization in print_results and save_results to compute all derived lists in a single pass over results.	Replace four separate list comprehensions with a single for-loop that classifies each result into successful, failed, skipped, and fixed lists in one traversal. Ensure skipped and fixed are derived only from successful results by nesting the skipped/fixed branching inside the success check. Preserve existing semantics of success/skipped handling while reducing the number of passes over the results collection for better performance.	training/scripts/fix_encoding.py
Minor formatting cleanup of logger configuration line for S3DatasetLoader.	Collapse multi-line logging.getLogger(...).setLevel(...) call into a single line while keeping behavior identical.	training/scripts/fix_encoding.py

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ℹ️ Review info

⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

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Run ID: 53a62a79-9e22-46b7-a4a7-b690b5543f6b

📥 Commits

Reviewing files that changed from the base of the PR and between 2e5eb05 and 7bfd665.

📒 Files selected for processing (1)

• training/scripts/fix_encoding.py

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[sourcery-ai]

Hey - I've left some high level feedback:

• Since both print_results and save_results now perform identical single-pass categorization, consider extracting that logic into a shared helper function to avoid duplication and keep future changes centralized.
• Double-check that the new categorization loop preserves the previous ordering semantics of successful/failed/skipped/fixed items, as subtle changes in order could affect downstream consumers of these result lists.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- Since both print_results and save_results now perform identical single-pass categorization, consider extracting that logic into a shared helper function to avoid duplication and keep future changes centralized.
- Double-check that the new categorization loop preserves the previous ordering semantics of successful/failed/skipped/fixed items, as subtle changes in order could affect downstream consumers of these result lists.

Fix all in Cursor

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No issues found across 1 file