"""
Chaos Engineering Agent

Performs chaos engineering experiments to test system resilience
using tools like Chaos Monkey, Litmus, Chaos Mesh, and Gremlin.
"""

from typing import Any, Dict, List
from agents.base import BaseAgent


class ChaosEngineerAgent(BaseAgent):
    """Performs chaos engineering experiments."""

    def __init__(self):
        super().__init__(
            name='chaos-engineer',
            description='Perform chaos engineering tests and resilience testing',
            category='devops',
            version='1.0.0',
            tags=['chaos-engineering', 'resilience', 'testing', 'sre', 'reliability']
        )

    async def execute(self, params: Dict[str, Any]) -> Dict[str, Any]:
        """
        Execute chaos engineering experiments.

        Args:
            params: {
                'action': 'create|execute|stop|status|analyze',
                'chaos_tool': 'chaos-monkey|litmus|chaos-mesh|gremlin',
                'experiment_name': 'pod-delete-test',
                'experiment_type': 'pod-delete|network-latency|cpu-stress|memory-stress|disk-fill',
                'targets': {
                    'namespace': 'production',
                    'labels': {'app': 'web-server'},
                    'percentage': 50  # affect 50% of matching pods
                },
                'parameters': {
                    'duration_seconds': 300,
                    'interval_seconds': 60,
                    'latency_ms': 100,
                    'packet_loss_percent': 10,
                    'cpu_cores': 2,
                    'memory_mb': 1024
                },
                'safety': {
                    'dry_run': false,
                    'blast_radius': 'namespace|cluster',
                    'rollback_on_failure': true,
                    'health_check_before': true,
                    'alert_on_start': true
                },
                'schedule': {
                    'enabled': false,
                    'cron': '0 2 * * *'
                }
            }

        Returns:
            {
                'status': 'success',
                'experiment_id': '...',
                'experiment_status': 'running|completed|failed',
                'impact_analysis': {...}
            }
        """
        action = params.get('action', 'execute')
        chaos_tool = params.get('chaos_tool', 'chaos-mesh')
        experiment_name = params.get('experiment_name')
        experiment_type = params.get('experiment_type', 'pod-delete')
        targets = params.get('targets', {})

        self.logger.info(
            f"Chaos engineering {action}: {experiment_name} ({experiment_type}) using {chaos_tool}"
        )

        result = {
            'status': 'success',
            'action': action,
            'chaos_tool': chaos_tool,
            'experiment_name': experiment_name,
            'experiment_type': experiment_type,
            'timestamp': '2025-11-16T00:00:00Z'
        }

        if action in ['create', 'execute']:
            parameters = params.get('parameters', {})
            safety = params.get('safety', {})

            affected_resources = {
                'namespace': targets.get('namespace', 'default'),
                'total_targets': 10,
                'affected_targets': int(10 * targets.get('percentage', 50) / 100),
                'labels': targets.get('labels', {})
            }

            result.update({
                'experiment_id': f'{chaos_tool}-{experiment_type}-20251116-001',
                'experiment_status': 'running' if action == 'execute' else 'created',
                'targets': affected_resources,
                'parameters': parameters,
                'duration_seconds': parameters.get('duration_seconds', 300),
                'started_at': '2025-11-16T10:00:00Z' if action == 'execute' else None,
                'estimated_end_time': '2025-11-16T10:05:00Z' if action == 'execute' else None,
                'dry_run': safety.get('dry_run', False),
                'safety_checks': {
                    'pre_health_check': 'passed' if safety.get('health_check_before') else 'skipped',
                    'blast_radius_limited': True,
                    'rollback_enabled': safety.get('rollback_on_failure', True),
                    'alerts_configured': safety.get('alert_on_start', True)
                }
            })

        if action == 'stop':
            result.update({
                'experiment_id': params.get('experiment_id'),
                'experiment_status': 'stopped',
                'stopped_at': '2025-11-16T10:02:30Z',
                'duration_completed_seconds': 150,
                'reason': params.get('stop_reason', 'Manual stop'),
                'rollback_initiated': True,
                'rollback_completed': True
            })

        if action == 'status':
            result.update({
                'experiment_id': params.get('experiment_id', f'{chaos_tool}-{experiment_type}-20251116-001'),
                'experiment_status': 'running',
                'started_at': '2025-11-16T10:00:00Z',
                'elapsed_seconds': 120,
                'remaining_seconds': 180,
                'progress_percent': 40,
                'current_phase': 'injection',
                'phases': {
                    'pre_check': 'completed',
                    'injection': 'running',
                    'observation': 'pending',
                    'cleanup': 'pending'
                },
                'affected_resources': {
                    'total': 10,
                    'currently_affected': 5,
                    'recovered': 0
                },
                'observations': {
                    'error_rate_increase_percent': 2.3,
                    'latency_increase_ms': 45.6,
                    'failed_requests': 234,
                    'alerts_triggered': 1
                }
            })

        if action == 'analyze':
            result.update({
                'experiment_id': params.get('experiment_id'),
                'experiment_status': 'completed',
                'analysis': {
                    'resilience_score': 85,  # out of 100
                    'recovery_time_seconds': 12.3,
                    'impact_severity': 'medium',
                    'system_behavior': 'stable with degradation'
                },
                'metrics': {
                    'availability_during_chaos': 98.5,
                    'error_rate_increase': 2.3,
                    'latency_p50_increase_ms': 23.4,
                    'latency_p99_increase_ms': 156.7,
                    'failed_requests_total': 234,
                    'alerts_triggered': 3,
                    'auto_scaling_triggered': True,
                    'circuit_breakers_opened': 1
                },
                'findings': [
                    'System maintained 98.5% availability during pod deletions',
                    'Auto-scaling responded within 15 seconds',
                    'Circuit breakers prevented cascade failures',
                    'Recovery time was within acceptable SLA (< 30s)'
                ],
                'recommendations': [
                    'Increase pod replica count from 3 to 5',
                    'Reduce circuit breaker threshold from 50% to 30%',
                    'Add more aggressive health checks'
                ],
                'comparison_to_baseline': {
                    'error_rate_normal': 0.1,
                    'error_rate_chaos': 2.4,
                    'latency_p50_normal': 45.6,
                    'latency_p50_chaos': 69.0
                }
            })

        return result

    def validate_params(self, params: Dict[str, Any]) -> bool:
        """Validate chaos engineering parameters."""
        valid_tools = ['chaos-monkey', 'litmus', 'chaos-mesh', 'gremlin']
        chaos_tool = params.get('chaos_tool', 'chaos-mesh')
        if chaos_tool not in valid_tools:
            self.logger.error(f"Invalid chaos_tool: {chaos_tool}")
            return False

        valid_actions = ['create', 'execute', 'stop', 'status', 'analyze']
        action = params.get('action', 'execute')
        if action not in valid_actions:
            self.logger.error(f"Invalid action: {action}")
            return False

        if action in ['create', 'execute'] and 'experiment_type' not in params:
            self.logger.error("Missing required field: experiment_type")
            return False

        if action in ['stop', 'status', 'analyze'] and 'experiment_id' not in params:
            self.logger.error("Missing required field: experiment_id")
            return False

        valid_types = [
            'pod-delete', 'pod-kill', 'network-latency', 'network-loss',
            'cpu-stress', 'memory-stress', 'disk-fill', 'dns-chaos'
        ]
        experiment_type = params.get('experiment_type', 'pod-delete')
        if experiment_type not in valid_types:
            self.logger.error(f"Invalid experiment_type: {experiment_type}")
            return False

        return True
