⚡ Bolt: Use pre-computed tuples for static iterations

[bashandbone]

💡 What: Pre-computed the self._classification_methods tuple of classification methods within the __init__ constructor instead of creating an inline list structure every time the classify loop was executed.
🎯 Why: When a static collection of instance methods needs to be repeatedly iterated over, constructing the collection over and over incurs double overhead: the allocation of the list memory and the creation of the bound instance method objects themselves.
📊 Impact: Reduces object creation time and decreases list allocation processing within the AST-based Node classification hotloop, improving raw iteration evaluation speeds.
🔬 Measurement: Verified using targeted tests (mise //:test tests/unit/engine/chunker/) to ensure no regressions during classifications.

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PR created automatically by Jules for task 2745804533802310033 started by @bashandbone

Summary by Sourcery

Pre-compute and reuse the classifier’s bound method collection to reduce allocation overhead in the classification hot loop and document this optimization pattern in the Bolt guidelines.

Enhancements:

• Pre-compute the tuple of classification methods in the classifier initializer and reuse it during thing classification to avoid per-call list construction and bound method creation.

Documentation:

• Add a Bolt guideline documenting the performance benefits of pre-computing bound method collections for hot loops.

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[sourcery-ai]

Reviewer's guide (collapsed on small PRs)

Reviewer's Guide

Precomputes and stores the classifier’s bound classification methods as a tuple during initialization and then reuses it in the hot classification loop, plus documents this performance pattern in the Bolt guidelines.

Class diagram for precomputed classification_methods tuple in classifier

classDiagram
    class SemanticClassifier {
        - _classification_map
        - _classification_methods
        + __init__()
        + classify_thing(thing, language)
        - _classify_known_exceptions(thing, language)
        - _classify_by_can_be_anywhere(thing, language)
        - _classify_from_token_purpose(thing, language)
        - _classify_multi_tier_things(thing, language)
        - _classify_from_category(thing, language)
        - _classify_from_direct_connections(thing, language)
        - _classify_by_cross_language_lookup(thing, language)
    }

    class GrammarClassificationResult {
    }

    SemanticClassifier ..> GrammarClassificationResult : uses

    note for SemanticClassifier "_classification_methods = (_classify_known_exceptions, _classify_by_can_be_anywhere, _classify_from_token_purpose, _classify_multi_tier_things, _classify_from_category, _classify_from_direct_connections, _classify_by_cross_language_lookup)"

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Flow diagram for classify_thing using precomputed method tuple

flowchart TD
    A[classify_thing called] --> B[Initialize results list]
    B --> C[Iterate over self._classification_methods]
    C --> D[Call current method with thing and language]
    D --> E{classification value returned?}
    E -->|No| C
    E -->|Yes| F{Is instance of GrammarClassificationResult?}
    F -->|Yes| G[Append classification to results]
    F -->|No| H[Unpack classification tuple into results]
    G --> C
    H --> C
    C --> I[Loop ends]
    I --> J[Return results]

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File-Level Changes

Change	Details	Files
Precompute and reuse a tuple of bound classification methods to eliminate per-call list and bound method allocation in the classification hot loop.	Add _classification_methods tuple attribute in init containing the ordered sequence of classification methods Refactor classify_thing to iterate over self._classification_methods instead of constructing an inline list on each call	src/codeweaver/semantic/classifier.py
Document the precomputation pattern for bound method collections in Bolt micro-optimization guidelines.	Add a new guideline entry describing the cost of constructing bound method collections in hot paths Recommend precomputing static method collections in init as tuples and reusing them	.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:

• Storing bound methods in __init__ means subclasses that override any of the _classify_* methods will keep using the base implementation unless they rebuild _classification_methods; consider either documenting this explicitly or building the tuple dynamically in a way that respects overrides (e.g., via a helper that subclasses can extend).
• Since the order of _classification_methods controls classification behavior, it may be worth centralizing that ordering in a single helper or clearly documenting it to reduce the risk of future changes accidentally altering classification precedence.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- Storing bound methods in `__init__` means subclasses that override any of the `_classify_*` methods will keep using the base implementation unless they rebuild `_classification_methods`; consider either documenting this explicitly or building the tuple dynamically in a way that respects overrides (e.g., via a helper that subclasses can extend).
- Since the order of `_classification_methods` controls classification behavior, it may be worth centralizing that ordering in a single helper or clearly documenting it to reduce the risk of future changes accidentally altering classification precedence.

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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 the grammar-based semantic node classification hot loop by hoisting a static set of classifier steps out of classify_thing() and into GrammarBasedClassifier.__init__, reducing repeated allocations during frequent classifications.

Changes:

• Precomputes self._classification_methods once in GrammarBasedClassifier.__init__ and iterates it in classify_thing().
• Updates the Jules “bolt” log with the micro-optimization learning/action note.

Reviewed changes

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

File	Description
src/codeweaver/semantic/classifier.py	Hoists the classification method iteration list into a precomputed tuple on the classifier instance.
.jules/bolt.md	Documents the optimization pattern (precomputing bound method collections) for future reference.

Comments suppressed due to low confidence (1)

src/codeweaver/semantic/classifier.py:862

• The inline comment claims GrammarClassificationResult is a NamedTuple/tuple, but it’s defined in this module as a BasedModel (Pydantic model). This is misleading given the branching here is really distinguishing a single result vs a tuple of results from some classifiers; consider updating the comment to reflect the actual types returned by classification methods.

            if classification := method(thing, language):
                # Check if it's a tuple but NOT a GrammarClassificationResult (which is a NamedTuple, hence a tuple)
                if not isinstance(classification, GrammarClassificationResult):
                    results.extend(classification)

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