feat: integrate pattern learning with config-based enable/disable#93
feat: integrate pattern learning with config-based enable/disable#93omsherikar merged 2 commits intomainfrom
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- Add pattern learning configuration options to RefactronConfig - enable_pattern_learning: master switch (default: true) - pattern_storage_dir: custom storage path (default: auto-detect) - pattern_learning_enabled: enable learning from feedback (default: true) - pattern_ranking_enabled: enable ranking by patterns (default: true) - Update Refactron initialization to respect config flags - Only initialize pattern components when enabled - Graceful degradation when disabled or initialization fails - Conditional initialization of learner and ranker based on flags - Add config validation for pattern learning settings - Boolean validation for enable flags - Path validation for storage directory - Update refactor() and record_feedback() to check config flags - Ranking only runs when pattern_ranking_enabled is true - Learning only triggers when pattern_learning_enabled is true - Add comprehensive tests for config-based enable/disable - Test pattern learning disabled entirely - Test individual component enable/disable - Test custom storage directory - Test feedback and refactor respect config flags - Update documentation with configuration examples - Add configuration section to FEATURES.md - Update QUICK_REFERENCE.md with pattern learning config - Add pattern learning settings to example config file - Update README.md with pattern learning mention Phase 8: Module Integration complete
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📝 WalkthroughWalkthroughAdds configuration-driven controls for pattern learning: new config fields and docs, conditional initialization of pattern-learning components, gating of ranking and feedback behavior in refactron, and tests validating enabled/disabled combinations. No public API signatures changed. Changes
Sequence Diagram(s)mermaid Note over Config,Refactron: Startup / initialization Note over User,Refactron: Refactor flow Note over User,Refactron: Feedback flow Estimated code review effort🎯 4 (Complex) | ⏱️ ~45 minutes Possibly related PRs
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Pull request overview
This PR adds comprehensive configuration options for enabling and disabling the pattern learning system in Refactron. The changes allow fine-grained control over pattern learning components through config flags while maintaining backward compatibility with defaults that enable all features.
Changes:
- Added four new configuration fields:
enable_pattern_learning(master switch),pattern_storage_dir(custom path),pattern_learning_enabled, andpattern_ranking_enabled - Updated Refactron initialization to conditionally initialize pattern components based on config flags
- Added validation for new boolean and path configuration fields
- Created comprehensive tests for config-based enable/disable scenarios
- Updated documentation (example config, quick reference, README)
Reviewed changes
Copilot reviewed 7 out of 7 changed files in this pull request and generated 5 comments.
Show a summary per file
| File | Description |
|---|---|
| tests/test_patterns_feedback.py | Added comprehensive test class for config-based pattern learning enable/disable scenarios |
| refactron/core/refactron.py | Implemented conditional initialization of pattern components and config-aware refactor/feedback methods |
| refactron/core/config_validator.py | Added validation for new pattern learning boolean and path fields |
| refactron/core/config.py | Added pattern learning configuration fields with sensible defaults and serialization support |
| examples/refactron_monitoring.yaml | Added pattern learning configuration section with detailed comments |
| docs/QUICK_REFERENCE.md | Added pattern learning configuration example to quick reference |
| README.md | Added brief mention of pattern learning feature in refactoring section |
Comments suppressed due to low confidence (1)
tests/test_patterns_feedback.py:570
- There is no test coverage for the edge case where
enable_pattern_learning=Truebut bothpattern_learning_enabled=Falseandpattern_ranking_enabled=False. This scenario would initialize storage, fingerprinter, and matcher but neither learner nor ranker. While this may be an unlikely configuration, adding a test would ensure the initialization logic handles this case correctly and documents the expected behavior.
class TestPatternLearningConfigIntegration:
"""Test Phase 8: Config-based pattern learning enable/disable."""
def test_pattern_learning_disabled(self, temp_storage_dir):
"""Test that pattern learning components are None when disabled."""
config = RefactronConfig(enable_pattern_learning=False)
refactron = Refactron(config)
assert refactron.pattern_storage is None
assert refactron.pattern_fingerprinter is None
assert refactron.pattern_learner is None
assert refactron.pattern_matcher is None
assert refactron.pattern_ranker is None
def test_pattern_learning_enabled(self, temp_storage_dir):
"""Test that pattern learning components are initialized when enabled."""
config = RefactronConfig(
enable_pattern_learning=True,
pattern_storage_dir=temp_storage_dir,
)
refactron = Refactron(config)
assert refactron.pattern_storage is not None
assert refactron.pattern_fingerprinter is not None
assert refactron.pattern_matcher is not None
def test_pattern_learning_enabled_but_learning_disabled(self, temp_storage_dir):
"""Test that learner is None when learning is disabled."""
config = RefactronConfig(
enable_pattern_learning=True,
pattern_learning_enabled=False,
pattern_storage_dir=temp_storage_dir,
)
refactron = Refactron(config)
assert refactron.pattern_storage is not None
assert refactron.pattern_fingerprinter is not None
assert refactron.pattern_matcher is not None
assert refactron.pattern_learner is None
def test_pattern_ranking_disabled(self, temp_storage_dir):
"""Test that ranker is None when ranking is disabled."""
config = RefactronConfig(
enable_pattern_learning=True,
pattern_ranking_enabled=False,
pattern_storage_dir=temp_storage_dir,
)
refactron = Refactron(config)
assert refactron.pattern_storage is not None
assert refactron.pattern_fingerprinter is not None
assert refactron.pattern_matcher is not None
assert refactron.pattern_ranker is None
def test_record_feedback_respects_config(self, temp_storage_dir):
"""Test that record_feedback respects enable_pattern_learning config."""
config = RefactronConfig(enable_pattern_learning=False)
refactron = Refactron(config)
operation = RefactoringOperation(
operation_type="extract_method",
file_path=Path("test.py"),
line_number=10,
description="Extract method",
old_code="def foo(): pass",
new_code="def bar(): pass",
risk_score=0.5,
)
# Should return early without error
refactron.record_feedback(
operation_id=operation.operation_id,
action="accepted",
operation=operation,
)
# Verify no storage was created
assert refactron.pattern_storage is None
def test_refactor_respects_ranking_config(self, temp_storage_dir):
"""Test that refactor respects pattern_ranking_enabled config."""
with tempfile.TemporaryDirectory() as tmpdir:
test_file = Path(tmpdir) / "test.py"
test_file.write_text("def foo():\n x = 100\n return x\n")
# Ranking disabled
config = RefactronConfig(
enable_pattern_learning=True,
pattern_ranking_enabled=False,
pattern_storage_dir=temp_storage_dir,
)
refactron = Refactron(config)
result = refactron.refactor(test_file, preview=True)
# Operations should not have ranking_score when ranking is disabled
if result.operations:
for op in result.operations:
assert "ranking_score" not in op.metadata
def test_custom_storage_dir(self, temp_storage_dir):
"""Test that custom pattern_storage_dir is respected."""
custom_dir = temp_storage_dir / "custom_patterns"
config = RefactronConfig(
enable_pattern_learning=True,
pattern_storage_dir=custom_dir,
)
refactron = Refactron(config)
assert refactron.pattern_storage is not None
assert refactron.pattern_storage.storage_dir == custom_dir
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| def test_pattern_learning_enabled(self, temp_storage_dir): | ||
| """Test that pattern learning components are initialized when enabled.""" | ||
| config = RefactronConfig( | ||
| enable_pattern_learning=True, | ||
| pattern_storage_dir=temp_storage_dir, | ||
| ) | ||
| refactron = Refactron(config) | ||
|
|
||
| assert refactron.pattern_storage is not None | ||
| assert refactron.pattern_fingerprinter is not None | ||
| assert refactron.pattern_matcher is not None |
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The test test_pattern_learning_enabled is incomplete. When enable_pattern_learning=True and both pattern_learning_enabled and pattern_ranking_enabled default to True, the learner and ranker should also be initialized. The test should verify that refactron.pattern_learner is not None and refactron.pattern_ranker is not None to ensure complete validation of the default configuration behavior.
| @@ -1,4 +1,4 @@ | |||
| """Tests for Phase 3: Feedback Collection System.""" | |||
| """Tests for Phase 3: Feedback Collection System and Phase 8: Module Integration.""" | |||
There was a problem hiding this comment.
The PR description mentions updating FEATURES.md with a configuration section, but FEATURES.md does not exist in the repository. This documentation update is either missing from the PR or the description is inaccurate. Please either add the missing documentation update or correct the PR description to reflect what was actually changed.
refactron/core/refactron.py
Outdated
| # Matcher is needed for both learning and ranking | ||
| self.pattern_matcher = PatternMatcher(storage=self.pattern_storage) | ||
|
|
||
| # Initialize ranker only if ranking is enabled | ||
| if self.config.pattern_ranking_enabled: |
There was a problem hiding this comment.
The PatternMatcher is only used by the RefactoringRanker (passed as a parameter on line 157), but it's being initialized unconditionally whenever enable_pattern_learning=True, even when pattern_ranking_enabled=False. This means unnecessary resources are being allocated when ranking is disabled. Consider making the matcher initialization conditional on either pattern_learning_enabled or pattern_ranking_enabled being true. The comment on line 150 stating "Matcher is needed for both learning and ranking" appears to be inaccurate - the matcher is only needed for ranking.
| # Matcher is needed for both learning and ranking | |
| self.pattern_matcher = PatternMatcher(storage=self.pattern_storage) | |
| # Initialize ranker only if ranking is enabled | |
| if self.config.pattern_ranking_enabled: | |
| # Matcher is only needed when ranking is enabled | |
| if self.config.pattern_ranking_enabled: | |
| self.pattern_matcher = PatternMatcher(storage=self.pattern_storage) | |
| # Initialize ranker only if ranking is enabled |
| def test_pattern_learning_enabled_but_learning_disabled(self, temp_storage_dir): | ||
| """Test that learner is None when learning is disabled.""" | ||
| config = RefactronConfig( | ||
| enable_pattern_learning=True, | ||
| pattern_learning_enabled=False, | ||
| pattern_storage_dir=temp_storage_dir, | ||
| ) | ||
| refactron = Refactron(config) | ||
|
|
||
| assert refactron.pattern_storage is not None | ||
| assert refactron.pattern_fingerprinter is not None | ||
| assert refactron.pattern_matcher is not None | ||
| assert refactron.pattern_learner is None |
There was a problem hiding this comment.
The test should verify that refactron.pattern_ranker is not None since pattern_ranking_enabled defaults to True when not explicitly set. The test currently only checks that the learner is None but doesn't verify that the ranker was properly initialized, which would make the test more complete and catch potential issues with the default ranking behavior.
| def test_pattern_ranking_disabled(self, temp_storage_dir): | ||
| """Test that ranker is None when ranking is disabled.""" | ||
| config = RefactronConfig( | ||
| enable_pattern_learning=True, | ||
| pattern_ranking_enabled=False, | ||
| pattern_storage_dir=temp_storage_dir, | ||
| ) | ||
| refactron = Refactron(config) | ||
|
|
||
| assert refactron.pattern_storage is not None | ||
| assert refactron.pattern_fingerprinter is not None | ||
| assert refactron.pattern_matcher is not None | ||
| assert refactron.pattern_ranker is None |
There was a problem hiding this comment.
The test should verify that refactron.pattern_learner is not None since pattern_learning_enabled defaults to True when not explicitly set. The test currently only checks that the ranker is None but doesn't verify that the learner was properly initialized, which would make the test more complete and catch potential issues with the default learning behavior.
- Fix critical resource waste: PatternMatcher now only initializes when ranking is enabled - PatternMatcher is only used by RefactoringRanker, not PatternLearner - Saves memory and initialization time when ranking is disabled - Move PatternMatcher initialization inside pattern_ranking_enabled check - Improve test completeness for default behavior - test_pattern_learning_enabled: verify all components initialized with defaults - test_pattern_learning_enabled_but_learning_disabled: verify ranker initialized when ranking enabled - test_pattern_ranking_disabled: verify learner initialized when learning enabled Addresses code review comments about resource optimization and test coverage.
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Pull request overview
Copilot reviewed 7 out of 7 changed files in this pull request and generated 1 comment.
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| class TestPatternLearningConfigIntegration: | ||
| """Test Phase 8: Config-based pattern learning enable/disable.""" | ||
|
|
||
| def test_pattern_learning_disabled(self, temp_storage_dir): |
There was a problem hiding this comment.
The temp_storage_dir parameter is declared but never used in this test. Since pattern learning is disabled in this test, the storage directory is not needed. Consider removing this parameter to keep the test signature clean.
| def test_pattern_learning_disabled(self, temp_storage_dir): | |
| def test_pattern_learning_disabled(self): |
1 participant
Add pattern learning configuration options to RefactronConfig
Update Refactron initialization to respect config flags
Add config validation for pattern learning settings
Update refactor() and record_feedback() to check config flags
Add comprehensive tests for config-based enable/disable
Update documentation with configuration examples
Summary by CodeRabbit
New Features
Documentation
Tests
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