"""Test complete integration of all new features."""

import pytest

from tests.base_test import (
    BaseCrackerjackFeatureTest,
)


class TestEndToEndIntegration(BaseCrackerjackFeatureTest):
    """Test complete integration of all new features."""

    @pytest.mark.asyncio
    async def test_complete_workflow_with_all_features(self, test_project_structure):
        """Test complete crackerjack workflow with all new features enabled."""
        # # Configure options with all new features
        # options = Options(
        #     strip_code=False,  # Semantic naming
        #     ai_fix=True,  # AI-powered fixing
        #     run_tests=True,  # Run tests
        #     version_bump="auto",  # Intelligent version analysis
        #     comprehensive=True,  # Full quality checks
        # )
        #
        # # Mock dependencies
        # with ExitStack() as stack:
        #     mock_changelog = stack.enter_context(
        #         patch("crackerjack.services.changelog_automation.ChangelogAutomator")
        #     )
        #     mock_version_analyzer = stack.enter_context(
        #         patch("crackerjack.services.version_analyzer.VersionAnalyzer")
        #     )
        #     mock_monitoring = stack.enter_context(
        #         patch("crackerjack.monitoring.CrackerjackMonitoringServer")
        #     )
        #
        #     # Configure mocks
        #     mock_version_analyzer.return_value.analyze_version_bump.return_value = (
        #         VersionBumpRecommendation(level="minor", confidence=0.8, reasons=[])
        #     )
        #     mock_changelog.return_value.update_changelog_for_version.return_value = True
        #
        #     # Execute workflow
        #     orchestrator = WorkflowOrchestrator(options, test_project_structure)
        #     result = await orchestrator.execute_complete_workflow()
        #
        #     # Verify all features were integrated
        #     assert result.success
        #     assert result.quality_score >= 85.0
        #
        #     # Verify new features were called
        #     mock_version_analyzer.return_value.analyze_version_bump.assert_called()
        #     mock_monitoring.return_value.record_metric.assert_called()
        pass

    @pytest.mark.asyncio
    async def test_semantic_cli_end_to_end(self, test_project_structure):
        """Test semantic CLI integration in real workflow."""
        # # Test with semantic command names
        # command = [
        #     "python",
        #     "-m",
        #     "crackerjack",
        #     "--strip-code",  # Semantic: was --clean
        #     "--ai-fix",  # Semantic: was --ai-agent
        #     "--version-bump",
        #     "auto",  # Semantic: was --bump
        #     "--run-tests",
        # ]
        #
        # # Parse and execute
        # result = await execute_command_integration_test(command, test_project_structure)
        #
        # # Verify semantic options were parsed correctly
        # assert result.options.strip_code is True
        # assert result.options.ai_fix is True
        # assert result.options.version_bump == "auto"
        # assert result.options.run_tests is True
        pass

    @pytest.mark.asyncio
    async def test_intelligent_automation_integration(self, test_project_structure):
        """Test intelligent commit and changelog automation."""
        # # Setup git repository with changes
        # git_service = GitService(test_project_structure)
        # await git_service.init_repository()
        # await git_service.stage_changes(["crackerjack/services/new_feature.py"])
        #
        # # Test intelligent commit message generation
        # commit_service = IntelligentCommitService()
        # commit_message = await commit_service.generate_commit_message(
        #     [Path("crackerjack/services/new_feature.py")]
        # )
        #
        # # Should generate semantic commit message
        # assert commit_message.startswith("feat")
        # assert "new_feature" in commit_message.lower()
        #
        # # Test changelog integration
        # changelog_service = ChangelogAutomator(git_service)
        # success = await changelog_service.update_changelog_for_version("2.0.0")
        #
        # assert success
        # changelog_path = test_project_structure / "CHANGELOG.md"
        # changelog_content = changelog_path.read_text()
        # assert "## [2.0.0]" in changelog_content
        pass

    @pytest.mark.asyncio
    async def test_performance_optimization_integration(
        self, performance_benchmark_context
    ):
        """Test performance optimizations in real workflow."""
        # # Create realistic workload
        # large_codebase = performance_benchmark_context["large_codebase"]
        # issues = create_mock_issues(
        #     count=large_codebase["issues"],
        #     types=8,  # Mixed issue types
        #     complexity_distribution="realistic",
        # )
        #
        # # Test with optimizations disabled
        # coordinator_baseline = AgentCoordinator(
        #     parallel_execution=False, issue_caching=False, smart_selection=False
        # )
        #
        # start_time = time.time()
        # baseline_result = await coordinator_baseline.handle_issues(issues)
        # baseline_time = time.time() - start_time
        #
        # # Test with all optimizations enabled
        # coordinator_optimized = AgentCoordinator(
        #     parallel_execution=True,
        #     issue_caching=True,
        #     smart_selection=True,
        #     progressive_enhancement=True,
        # )
        #
        # start_time = time.time()
        # optimized_result = await coordinator_optimized.handle_issues(issues)
        # optimized_time = time.time() - start_time
        #
        # # Verify results are equivalent
        # assert baseline_result.fixed_count == optimized_result.fixed_count
        #
        # # Verify performance improvement meets target (30-50%)
        # self.assert_performance_improvement(
        #     baseline_time, optimized_time, min_improvement=0.30
        # )
        #
        # # Verify cache effectiveness
        # cache_hit_rate = coordinator_optimized.get_cache_hit_rate()
        # assert cache_hit_rate >= 0.60  # Target: 60% hit rate
        pass

    @pytest.mark.asyncio
    async def test_monitoring_dashboard_integration(self, test_project_structure):
        """Test monitoring dashboard integration with workflow."""
        # # Start monitoring system
        # monitoring_server = CrackerjackMonitoringServer()
        # await monitoring_server.start(port=8675)
        #
        # try:
        #     # Connect WebSocket client to monitor workflow
        #     async with websockets.connect("ws://localhost:8675") as websocket:
        #         # Subscribe to workflow metrics
        #         await websocket.send(
        #             json.dumps({"type": "subscribe", "channel": "workflow_metrics"})
        #         )
        #
        #         # Execute workflow in background
        #         options = Options(ai_fix=True, run_tests=True)
        #         workflow_task = asyncio.create_task(
        #             WorkflowOrchestrator(
        #                 options, test_project_structure
        #             ).execute_workflow()
        #         )
        #
        #         # Collect metrics during workflow
        #         metrics_received = []
        #         while not workflow_task.done():
        #             try:
        #                 message = await asyncio.wait_for(websocket.recv(), timeout=1.0)
        #                 metric_data = json.loads(message)
        #                 if metric_data["type"] == "metric_update":
        #                     metrics_received.append(metric_data["data"])
        #             except asyncio.TimeoutError:
        #                 continue
        #
        #         await workflow_task
        #
        #         # Verify metrics were streamed during workflow
        #         assert len(metrics_received) > 0
        #
        #         # Verify metric types
        #         metric_types = {m["metric_type"] for m in metrics_received}
        #         expected_types = {"quality_score", "execution_time", "test_coverage"}
        #         assert len(metric_types.intersection(expected_types)) > 0
        #
        # finally:
        #     await monitoring_server.stop()
        pass

    def test_documentation_generation_integration(self, test_project_structure):
        """Test documentation generation integration."""
        # doc_system = AIOptimizedDocumentationSystem()
        #
        # # Generate complete documentation set
        # result = doc_system.generate_complete_documentation(test_project_structure)
        #
        # # Verify all documentation outputs
        # assert result.ai_reference_generated
        # assert result.agent_capabilities_generated
        # assert result.error_patterns_generated
        # assert result.readme_enhanced
        #
        # # Verify files were created
        # assert (test_project_structure / "ai" / "AI-REFERENCE.md").exists()
        # assert (test_project_structure / "ai" / "AGENT-CAPABILITIES.json").exists()
        # assert (test_project_structure / "ai" / "ERROR-PATTERNS.yaml").exists()
        #
        # # Verify content quality
        # ai_ref_content = (test_project_structure / "ai" / "AI-REFERENCE.md").read_text()
        # assert "| Use Case |" in ai_ref_content  # Table format for AI
        # assert "python -m crackerjack" in ai_ref_content  # Commands included
        pass

    @pytest.mark.asyncio
    async def test_regression_prevention(self, test_project_structure):
        """Test that new features don't break existing functionality."""
        # # Baseline: Run workflow with original feature set
        # baseline_options = Options(
        #     run_tests=True,
        #     comprehensive=True,
        #     ai_fix=False,  # Disable new features
        # )
        #
        # baseline_orchestrator = WorkflowOrchestrator(
        #     baseline_options, test_project_structure
        # )
        # baseline_result = await baseline_orchestrator.execute_workflow()
        #
        # baseline_metrics = {
        #     "success": baseline_result.success,
        #     "quality_score": baseline_result.quality_score,
        #     "execution_time": baseline_result.execution_time,
        #     "issues_fixed": baseline_result.issues_fixed,
        # }
        #
        # # Enhanced: Run workflow with all new features
        # enhanced_options = Options(
        #     strip_code=False,  # New semantic naming
        #     ai_fix=True,  # New AI features
        #     run_tests=True,
        #     comprehensive=True,
        #     version_bump="auto",  # New version analysis
        # )
        #
        # enhanced_orchestrator = WorkflowOrchestrator(
        #     enhanced_options, test_project_structure
        # )
        # enhanced_result = await enhanced_orchestrator.execute_workflow()
        #
        # enhanced_metrics = {
        #     "success": enhanced_result.success,
        #     "quality_score": enhanced_result.quality_score,
        #     "execution_time": enhanced_result.execution_time,
        #     "issues_fixed": enhanced_result.issues_fixed,
        # }
        #
        # # Verify no regression in core functionality
        # self.assert_no_regression(baseline_metrics, enhanced_metrics)
        #
        # # Enhanced version should maintain or improve quality
        # assert enhanced_metrics["quality_score"] >= baseline_metrics["quality_score"]
        # assert enhanced_metrics["success"] == baseline_metrics["success"]
        pass

    def test_backward_compatibility(self, test_project_structure):
        """Test backward compatibility of new features."""
        # # Test that existing workflows still work
        # legacy_workflow_configs = [
        #     {"ai_agent": True, "run_tests": True},  # Legacy option name
        #     {"clean": True, "comprehensive": True},  # Legacy option name
        #     {"all": "patch", "skip_hooks": True},  # Legacy option names
        # ]
        #
        # for config in legacy_workflow_configs:
        #     # Should handle gracefully with deprecation warnings
        #     with pytest.warns(DeprecationWarning, match="renamed"):
        #         options = Options(**translate_legacy_options(config))
        #
        #         # Workflow should still execute successfully
        #         orchestrator = WorkflowOrchestrator(options, test_project_structure)
        #         # Test would execute workflow and verify success
        #         # Actual execution omitted for test performance
        #         assert True  # Placeholder for workflow execution test
        pass
