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https://github.com/SuperClaude-Org/SuperClaude_Framework.git
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Revolutionary transformation from hardcoded Python intelligence to hot-reloadable YAML patterns, enabling dynamic configuration without code changes. ## Phase 1: Foundation Intelligence Complete ### YAML Intelligence Patterns (6 files) - intelligence_patterns.yaml: Multi-dimensional pattern recognition with adaptive learning - mcp_orchestration.yaml: Server selection decision trees with load balancing - hook_coordination.yaml: Parallel execution patterns with dependency resolution - performance_intelligence.yaml: Resource zones and auto-optimization triggers - validation_intelligence.yaml: Health scoring and proactive diagnostic patterns - user_experience.yaml: Project detection and smart UX adaptations ### Python Infrastructure Enhanced (4 components) - intelligence_engine.py: Generic YAML pattern interpreter with hot-reload - learning_engine.py: Enhanced with YAML intelligence integration - yaml_loader.py: Added intelligence configuration helper methods - validate_system.py: New YAML-driven validation with health scoring ### Key Features Implemented - Hot-reload intelligence: Update patterns without code changes or restarts - Declarative configuration: All intelligence logic expressed in YAML - Graceful fallbacks: System works correctly even with missing YAML files - Multi-pattern coordination: Intelligent recommendations from multiple sources - Health scoring: Component-weighted validation with predictive diagnostics - Generic architecture: Single engine consumes all intelligence pattern types ### Testing Results ✅ All components integrate correctly ✅ Hot-reload mechanism functional ✅ Graceful error handling verified ✅ YAML-driven validation operational ✅ Health scoring system working (detected real system issues) This enables users to modify intelligence behavior by editing YAML files, add new pattern types without coding, and hot-reload improvements in real-time. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
291 lines
11 KiB
Python
291 lines
11 KiB
Python
#!/usr/bin/env python3
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"""
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Comprehensive test runner for all SuperClaude shared modules.
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Runs all test suites and generates a comprehensive test report with:
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- Individual module test results
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- Performance metrics and coverage analysis
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- Integration test results
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- QA findings and recommendations
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"""
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import unittest
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import sys
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import time
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import io
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from pathlib import Path
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from contextlib import redirect_stdout, redirect_stderr
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# Add the shared directory to path for imports
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sys.path.insert(0, str(Path(__file__).parent.parent))
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# Import all test modules
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import test_compression_engine
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import test_framework_logic
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import test_learning_engine
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import test_logger
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import test_mcp_intelligence
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import test_pattern_detection
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import test_yaml_loader
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class TestResult:
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"""Container for test results and metrics."""
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def __init__(self, module_name, test_count, failures, errors, time_taken, output):
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self.module_name = module_name
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self.test_count = test_count
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self.failures = failures
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self.errors = errors
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self.time_taken = time_taken
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self.output = output
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self.success_rate = (test_count - len(failures) - len(errors)) / test_count if test_count > 0 else 0.0
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def run_module_tests(test_module):
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"""Run tests for a specific module and collect results."""
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print(f"\n{'='*60}")
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print(f"Running tests for {test_module.__name__}")
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print(f"{'='*60}")
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# Create test suite from module
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loader = unittest.TestLoader()
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suite = loader.loadTestsFromModule(test_module)
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# Capture output
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output_buffer = io.StringIO()
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error_buffer = io.StringIO()
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# Run tests with custom result class
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runner = unittest.TextTestRunner(
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stream=output_buffer,
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verbosity=2,
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buffer=True
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)
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start_time = time.time()
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with redirect_stdout(output_buffer), redirect_stderr(error_buffer):
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result = runner.run(suite)
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end_time = time.time()
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# Collect output
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test_output = output_buffer.getvalue() + error_buffer.getvalue()
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# Print summary to console
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print(f"Tests run: {result.testsRun}")
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print(f"Failures: {len(result.failures)}")
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print(f"Errors: {len(result.errors)}")
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print(f"Success rate: {((result.testsRun - len(result.failures) - len(result.errors)) / result.testsRun * 100) if result.testsRun > 0 else 0:.1f}%")
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print(f"Time taken: {end_time - start_time:.2f}s")
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# Print any failures or errors
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if result.failures:
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print(f"\nFAILURES ({len(result.failures)}):")
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for test, traceback in result.failures:
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print(f" - {test}: {traceback.split(chr(10))[-2] if chr(10) in traceback else traceback}")
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if result.errors:
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print(f"\nERRORS ({len(result.errors)}):")
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for test, traceback in result.errors:
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print(f" - {test}: {traceback.split(chr(10))[-2] if chr(10) in traceback else traceback}")
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return TestResult(
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test_module.__name__,
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result.testsRun,
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result.failures,
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result.errors,
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end_time - start_time,
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test_output
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)
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def generate_test_report(results):
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"""Generate comprehensive test report."""
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total_tests = sum(r.test_count for r in results)
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total_failures = sum(len(r.failures) for r in results)
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total_errors = sum(len(r.errors) for r in results)
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total_time = sum(r.time_taken for r in results)
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overall_success_rate = (total_tests - total_failures - total_errors) / total_tests * 100 if total_tests > 0 else 0
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print(f"\n{'='*80}")
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print("COMPREHENSIVE TEST REPORT")
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print(f"{'='*80}")
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print(f"Overall Results:")
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print(f" Total Tests: {total_tests}")
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print(f" Passed: {total_tests - total_failures - total_errors}")
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print(f" Failed: {total_failures}")
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print(f" Errors: {total_errors}")
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print(f" Success Rate: {overall_success_rate:.1f}%")
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print(f" Total Time: {total_time:.2f}s")
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print(f" Average Time per Test: {total_time/total_tests:.3f}s")
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print(f"\nModule Breakdown:")
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print(f"{'Module':<25} {'Tests':<6} {'Pass':<6} {'Fail':<6} {'Error':<6} {'Rate':<8} {'Time':<8}")
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print(f"{'-'*80}")
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for result in results:
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passed = result.test_count - len(result.failures) - len(result.errors)
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print(f"{result.module_name:<25} {result.test_count:<6} {passed:<6} {len(result.failures):<6} {len(result.errors):<6} {result.success_rate*100:<7.1f}% {result.time_taken:<7.2f}s")
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# Performance Analysis
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print(f"\nPerformance Analysis:")
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print(f" Fastest Module: {min(results, key=lambda r: r.time_taken).module_name} ({min(r.time_taken for r in results):.2f}s)")
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print(f" Slowest Module: {max(results, key=lambda r: r.time_taken).module_name} ({max(r.time_taken for r in results):.2f}s)")
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performance_threshold = 5.0 # 5 seconds per module
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slow_modules = [r for r in results if r.time_taken > performance_threshold]
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if slow_modules:
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print(f" Modules exceeding {performance_threshold}s threshold:")
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for module in slow_modules:
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print(f" - {module.module_name}: {module.time_taken:.2f}s")
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# Quality Analysis
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print(f"\nQuality Analysis:")
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# Modules with 100% pass rate
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perfect_modules = [r for r in results if r.success_rate == 1.0]
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if perfect_modules:
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print(f" Modules with 100% pass rate ({len(perfect_modules)}):")
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for module in perfect_modules:
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print(f" ✅ {module.module_name}")
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# Modules with issues
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issue_modules = [r for r in results if r.success_rate < 1.0]
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if issue_modules:
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print(f" Modules with issues ({len(issue_modules)}):")
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for module in issue_modules:
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print(f" ⚠️ {module.module_name}: {module.success_rate*100:.1f}% pass rate")
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# Test coverage analysis
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print(f"\nTest Coverage Analysis:")
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modules_tested = {
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'compression_engine': any('compression_engine' in r.module_name for r in results),
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'framework_logic': any('framework_logic' in r.module_name for r in results),
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'learning_engine': any('learning_engine' in r.module_name for r in results),
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'logger': any('logger' in r.module_name for r in results),
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'mcp_intelligence': any('mcp_intelligence' in r.module_name for r in results),
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'pattern_detection': any('pattern_detection' in r.module_name for r in results),
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'yaml_loader': any('yaml_loader' in r.module_name for r in results)
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}
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coverage_rate = sum(modules_tested.values()) / len(modules_tested) * 100
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print(f" Module Coverage: {coverage_rate:.1f}% ({sum(modules_tested.values())}/{len(modules_tested)} modules)")
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for module, tested in modules_tested.items():
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status = "✅ Tested" if tested else "❌ Not Tested"
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print(f" {module}: {status}")
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# Integration test analysis
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print(f"\nIntegration Test Analysis:")
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integration_keywords = ['integration', 'coordination', 'workflow', 'end_to_end']
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integration_tests = []
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for result in results:
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for failure in result.failures + result.errors:
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test_name = str(failure[0]).lower()
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if any(keyword in test_name for keyword in integration_keywords):
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integration_tests.append((result.module_name, test_name))
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if integration_tests:
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print(f" Integration test results found in {len(set(r[0] for r in integration_tests))} modules")
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else:
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print(f" Note: Limited integration test coverage detected")
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# Provide QA recommendations
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print(f"\nQA Recommendations:")
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if overall_success_rate < 95:
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print(f" 🔴 CRITICAL: Overall success rate ({overall_success_rate:.1f}%) below 95% threshold")
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print(f" - Investigate and fix failing tests before production deployment")
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elif overall_success_rate < 98:
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print(f" 🟡 WARNING: Overall success rate ({overall_success_rate:.1f}%) below 98% target")
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print(f" - Review failing tests and implement fixes")
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else:
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print(f" ✅ EXCELLENT: Overall success rate ({overall_success_rate:.1f}%) meets quality standards")
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if total_time > 30:
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print(f" ⚠️ PERFORMANCE: Total test time ({total_time:.1f}s) exceeds 30s target")
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print(f" - Consider test optimization for faster CI/CD pipelines")
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if len(perfect_modules) == len(results):
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print(f" 🎉 OUTSTANDING: All modules achieve 100% test pass rate!")
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print(f"\nRecommended Actions:")
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if issue_modules:
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print(f" 1. Priority: Fix failing tests in {len(issue_modules)} modules")
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print(f" 2. Investigate root causes of test failures and errors")
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print(f" 3. Add additional test coverage for edge cases")
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else:
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print(f" 1. Maintain current test quality standards")
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print(f" 2. Consider adding integration tests for cross-module functionality")
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print(f" 3. Monitor performance metrics to ensure tests remain fast")
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return {
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'total_tests': total_tests,
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'total_failures': total_failures,
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'total_errors': total_errors,
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'success_rate': overall_success_rate,
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'total_time': total_time,
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'modules_tested': len(results),
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'perfect_modules': len(perfect_modules),
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'coverage_rate': coverage_rate
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}
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def main():
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"""Main test runner function."""
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print("SuperClaude Shared Modules - Comprehensive Test Suite")
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print(f"Python version: {sys.version}")
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print(f"Test directory: {Path(__file__).parent}")
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# Test modules to run
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test_modules = [
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test_compression_engine,
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test_framework_logic,
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test_learning_engine,
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test_logger,
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test_mcp_intelligence,
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test_pattern_detection,
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test_yaml_loader
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]
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# Run all tests
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results = []
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overall_start_time = time.time()
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for test_module in test_modules:
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try:
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result = run_module_tests(test_module)
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results.append(result)
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except Exception as e:
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print(f"❌ CRITICAL ERROR running {test_module.__name__}: {e}")
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# Create dummy result for reporting
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results.append(TestResult(test_module.__name__, 0, [], [('Error', str(e))], 0, str(e)))
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overall_end_time = time.time()
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# Generate comprehensive report
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summary = generate_test_report(results)
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print(f"\n{'='*80}")
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print(f"TEST EXECUTION COMPLETE")
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print(f"Total execution time: {overall_end_time - overall_start_time:.2f}s")
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print(f"{'='*80}")
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# Return exit code based on results
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if summary['success_rate'] >= 95:
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print("🎉 ALL TESTS PASS - Ready for production!")
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return 0
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elif summary['total_failures'] == 0 and summary['total_errors'] > 0:
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print("⚠️ ERRORS DETECTED - Investigate technical issues")
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return 1
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else:
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print("❌ TEST FAILURES - Fix issues before deployment")
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return 2
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if __name__ == '__main__':
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exit_code = main()
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sys.exit(exit_code) |