⚡ Bolt: Optimize linear lookups in file extension checks

[bashandbone]

💡 What: Optimized the is_doc and is_data property getters in src/codeweaver/core/metadata.py by replacing next((...)) generator expressions with standard for loops that use early returns. Suppressed the ruff rule SIM110 with # noqa to ensure the manual loop is preserved over an any() generator.

🎯 Why: In CPython, evaluating generator comprehensions inside functions like next() or any() involves allocating a generator object and evaluating its frames. When performing a simple linear search to find a matching extension, manually writing out a for loop that returns early avoids this overhead completely. These properties are accessed frequently during file discovery, making this a small but compounding speedup.

📊 Impact: Reduces evaluation overhead in file metadata extension lookups by entirely bypassing generator frame allocations, yielding faster linear lookups.

🔬 Measurement: The optimization can be verified by profiling calls to FileMetadata.is_doc and FileMetadata.is_data over a large list of files compared to their previous implementations, seeing a drop in generator allocation overhead.

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PR created automatically by Jules for task 7415917703769671111 started by @bashandbone

Summary by Sourcery

Optimize file metadata extension classification checks and document the performance guideline in the optimization playbook.

Enhancements:

• Improve performance of documentation and data file extension checks by replacing generator-based lookups with explicit loops and early returns.

Documentation:

• Extend the Bolt optimization guide with a new rule recommending explicit for-loops over generator expressions in hot-path linear lookups.

[google-labs-jules]

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[sourcery-ai]

Reviewer's guide (collapsed on small PRs)

Reviewer's Guide

Optimizes FileMetadata extension classification by replacing generator-based lookups with explicit for-loop early returns in hot paths, and documents this pattern in the Bolt optimization guide.

Flow diagram for optimized FileMetadata extension lookups (is_doc / is_data)

flowchart TD
    A[Start is_doc / is_data] --> B[Import DOC_FILES_EXTENSIONS or DATA_FILES_EXTENSIONS]
    B --> C[for ext in DOC_FILES_EXTENSIONS / DATA_FILES_EXTENSIONS]
    C --> D{ext.ext == self.ext}
    D -- Yes --> E[return True]
    D -- No --> F{More extensions?}
    F -- Yes --> C
    F -- No --> G[return False]
    E --> H[End]
    G --> H[End]

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File-Level Changes

Change	Details	Files
Optimize FileMetadata.is_doc linear extension lookup to avoid generator allocation overhead.	Replaced next()-wrapped generator expression with an explicit for loop and early return when checking documentation file extensions. Added a performance-focused comment explaining the rationale for avoiding generator frame allocation in this hot path. Suppressed ruff SIM110 for the loop to prevent automatic refactoring back to a comprehension or any().	src/codeweaver/core/metadata.py
Optimize FileMetadata.is_data linear extension lookup in the same way as is_doc for consistency and performance.	Replaced next()-wrapped generator expression with an explicit for loop and early return when checking data file extensions. Added a performance comment mirroring is_doc to justify the manual loop. Suppressed ruff SIM110 for the loop to preserve the optimization.	src/codeweaver/core/metadata.py
Document the generator-to-for-loop optimization pattern in the Bolt micro-optimizations guide.	Added a new dated entry describing why replacing next()-wrapped generator expressions with for loops can speed up linear lookups. Recorded an action item recommending this pattern in hot paths and noting the need to suppress SIM110 where applicable.	.jules/bolt.md

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[github-actions]

🤖 Hi @bashandbone, I've received your request, and I'm working on it now! You can track my progress in the logs for more details.

[sourcery-ai]

Hey - I've left some high level feedback:

• Given that DOC_FILES_EXTENSIONS and DATA_FILES_EXTENSIONS appear to be static collections, consider using a precomputed set or mapping of ext values for O(1) membership checks instead of repeated linear scans, which will likely outperform the micro-optimization from removing the generator.
• The is_doc and is_data implementations are now almost identical; consider extracting a shared helper (e.g., _has_ext(self.ext, EXT_COLLECTION)) to avoid duplication and keep future changes to the lookup logic in one place.
• If you keep the # noqa: SIM110 suppression, it may be worth tightening the comment to explicitly reference this being a measured hot path (or add a short note about the specific context) so future readers understand why the usual readability preference is intentionally bypassed here.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- Given that `DOC_FILES_EXTENSIONS` and `DATA_FILES_EXTENSIONS` appear to be static collections, consider using a precomputed set or mapping of `ext` values for O(1) membership checks instead of repeated linear scans, which will likely outperform the micro-optimization from removing the generator.
- The `is_doc` and `is_data` implementations are now almost identical; consider extracting a shared helper (e.g., `_has_ext(self.ext, EXT_COLLECTION)`) to avoid duplication and keep future changes to the lookup logic in one place.
- If you keep the `# noqa: SIM110` suppression, it may be worth tightening the comment to explicitly reference this being a measured hot path (or add a short note about the specific context) so future readers understand why the usual readability preference is intentionally bypassed here.

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[github-actions]

🤖 I'm sorry @bashandbone, but I was unable to process your request. Please see the logs for more details.

[Copilot]

Pull request overview

Optimizes frequent file-extension category checks in ExtLangPair by replacing next((...)) generator expressions with explicit for loops and early returns, reducing generator allocation overhead during linear lookups.

Changes:

• Rewrote ExtLangPair.is_doc and ExtLangPair.is_data to use explicit loops with early returns (and added # noqa: SIM110 to preserve this pattern).
• Added a Bolt learning entry documenting the “for-loop over generator/next” optimization pattern for hot paths.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.

File	Description
src/codeweaver/core/metadata.py	Replaces generator/next()-based linear lookups with early-return loops for is_doc/is_data.
.jules/bolt.md	Documents the optimization rationale/pattern for future reference.

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