"""
Advanced Features Demo & Documentation

Showcases Query Replay, Model Blueprints, Live Dashboard, 
Model Contracts, and Quantum Queries with comprehensive examples.
"""

import time
import json
from datetime import datetime
from typing import Dict, List, Any, Optional

# ============================================================================
# QUERY REPLAY - Record and replay database operations
# ============================================================================

class QueryReplay:
    """Record and replay database operations for debugging and testing"""
    
    def __init__(self):
        self.recordings: Dict[str, List[Dict[str, Any]]] = {}
        self.is_recording = False
        self.current_session: Optional[str] = None
        
    def start_recording(self, session_name: str) -> None:
        """Start recording operations"""
        self.is_recording = True
        self.current_session = session_name
        self.recordings[session_name] = []
        print(f"[REPLAY] Recording started: {session_name}")
        
    def record_operation(self, operation: str, details: Dict[str, Any]) -> None:
        """Record an operation"""
        if self.is_recording and self.current_session:
            record = {
                "timestamp": datetime.now().isoformat(),
                "operation": operation,
                "details": details
            }
            self.recordings[self.current_session].append(record)
            
    def stop_recording(self) -> None:
        """Stop recording operations"""
        if self.current_session:
            count = len(self.recordings[self.current_session])
            print(f"[REPLAY] Recording stopped: {count} operations recorded")
        self.is_recording = False
        self.current_session = None
        
    def replay_session(self, session_name: str, verbose: bool = True) -> List[Dict]:
        """Replay recorded operations"""
        if session_name not in self.recordings:
            raise ValueError(f"Session not found: {session_name}")
            
        operations = self.recordings[session_name]
        if verbose:
            print(f"\n[REPLAY] Replaying {session_name} ({len(operations)} operations)")
            print("-" * 70)
            
        for i, record in enumerate(operations, 1):
            if verbose:
                print(f"{i}. {record['operation']}: {record['details']}")
            time.sleep(0.01)  # Simulate execution
            
        if verbose:
            print("-" * 70)
            print(f"[REPLAY] Replay complete\n")
            
        return operations
        
    def export_session(self, session_name: str, filename: str) -> None:
        """Export session to JSON"""
        if session_name not in self.recordings:
            raise ValueError(f"Session not found: {session_name}")
            
        with open(filename, 'w') as f:
            json.dump(self.recordings[session_name], f, indent=2)
        print(f"[REPLAY] Session exported: {filename}")
        
    def get_session_stats(self, session_name: str) -> Dict[str, Any]:
        """Get statistics for a session"""
        if session_name not in self.recordings:
            raise ValueError(f"Session not found: {session_name}")
            
        ops = self.recordings[session_name]
        operations_by_type = {}
        for op in ops:
            op_type = op['operation']
            operations_by_type[op_type] = operations_by_type.get(op_type, 0) + 1
            
        return {
            "session": session_name,
            "total_operations": len(ops),
            "operations_by_type": operations_by_type,
            "start_time": ops[0]['timestamp'] if ops else None,
            "end_time": ops[-1]['timestamp'] if ops else None
        }


# ============================================================================
# MODEL BLUEPRINTS - Data generation with realistic patterns
# ============================================================================

class ModelBlueprint:
    """Generate realistic test data for models"""
    
    def __init__(self, model_class, style: str = "default"):
        self.model_class = model_class
        self.style = style
        self.config = self._get_style_config(style)
        
    def _get_style_config(self, style: str) -> Dict[str, Any]:
        """Get configuration for data generation style"""
        styles = {
            "e-commerce": {
                "name_prefix": "Product",
                "description_length": 200,
                "price_range": (9.99, 999.99),
                "stock_range": (0, 10000)
            },
            "social": {
                "name_prefix": "User",
                "description_length": 140,
                "price_range": None,
                "stock_range": None
            },
            "blog": {
                "name_prefix": "Post",
                "description_length": 1000,
                "price_range": None,
                "stock_range": None
            },
            "default": {
                "name_prefix": "Record",
                "description_length": 100,
                "price_range": None,
                "stock_range": None
            }
        }
        return styles.get(style, styles["default"])
        
    def generate_record(self) -> Dict[str, Any]:
        """Generate a single record with realistic data"""
        import random
        import string
        
        config = self.config
        
        data = {
            "name": f"{config['name_prefix']}_{random.randint(1000, 9999)}",
            "description": "".join(random.choices(string.ascii_letters, k=config['description_length']))[:100]
        }
        
        if config['price_range']:
            data['price'] = round(random.uniform(*config['price_range']), 2)
            
        if config['stock_range']:
            data['stock'] = random.randint(*config['stock_range'])
            
        return data
        
    def generate_bulk(self, count: int) -> List[Dict[str, Any]]:
        """Generate multiple records"""
        records = [self.generate_record() for _ in range(count)]
        print(f"[BLUEPRINT] Generated {count} records for {self.model_class.__name__}")
        return records


# ============================================================================
# LIVE DASHBOARD - Real-time monitoring
# ============================================================================

class LiveDashboard:
    """Real-time ORM monitoring dashboard"""
    
    def __init__(self):
        self.metrics = {
            "total_queries": 0,
            "total_saves": 0,
            "total_deletes": 0,
            "cache_hits": 0,
            "cache_misses": 0,
            "query_times": []
        }
        self.start_time = datetime.now()
        
    def record_query(self, query_type: str, execution_time: float) -> None:
        """Record a query execution"""
        self.metrics["total_queries"] += 1
        self.metrics["query_times"].append(execution_time)
        
    def record_save(self) -> None:
        """Record a save operation"""
        self.metrics["total_saves"] += 1
        
    def record_delete(self) -> None:
        """Record a delete operation"""
        self.metrics["total_deletes"] += 1
        
    def record_cache_hit(self) -> None:
        """Record a cache hit"""
        self.metrics["cache_hits"] += 1
        
    def record_cache_miss(self) -> None:
        """Record a cache miss"""
        self.metrics["cache_misses"] += 1
        
    def get_status(self) -> Dict[str, Any]:
        """Get current dashboard status"""
        uptime = (datetime.now() - self.start_time).total_seconds()
        total_cache = self.metrics["cache_hits"] + self.metrics["cache_misses"]
        hit_rate = (self.metrics["cache_hits"] / total_cache * 100) if total_cache > 0 else 0
        
        avg_query_time = (sum(self.metrics["query_times"]) / len(self.metrics["query_times"]) * 1000 
                         if self.metrics["query_times"] else 0)
        
        return {
            "uptime_seconds": uptime,
            "total_queries": self.metrics["total_queries"],
            "total_saves": self.metrics["total_saves"],
            "total_deletes": self.metrics["total_deletes"],
            "cache_hits": self.metrics["cache_hits"],
            "cache_misses": self.metrics["cache_misses"],
            "cache_hit_rate": f"{hit_rate:.1f}%",
            "avg_query_time_ms": f"{avg_query_time:.2f}ms",
            "queries_per_second": f"{self.metrics['total_queries'] / uptime:.2f}" if uptime > 0 else "0"
        }
        
    def display_dashboard(self) -> None:
        """Display formatted dashboard"""
        status = self.get_status()
        print("\n" + "=" * 70)
        print("LIVE DASHBOARD")
        print("=" * 70)
        print(f"Uptime: {status['uptime_seconds']:.1f}s")
        print(f"Queries: {status['total_queries']} (avg {status['avg_query_time_ms']}ms)")
        print(f"Saves: {status['total_saves']} | Deletes: {status['total_deletes']}")
        print(f"Cache: {status['cache_hits']} hits, {status['cache_misses']} misses ({status['cache_hit_rate']})")
        print(f"Throughput: {status['queries_per_second']} queries/sec")
        print("=" * 70 + "\n")


# ============================================================================
# MODEL CONTRACTS - Advanced validation framework
# ============================================================================

class ModelContract:
    """Contract for model validation rules"""
    
    def __init__(self):
        self.rules: Dict[str, callable] = {}
        self.violations: List[str] = []
        
    def add_rule(self, name: str, validator: callable) -> None:
        """Add validation rule"""
        self.rules[name] = validator
        
    def validate(self, model_instance: Any) -> bool:
        """Validate model against all rules"""
        self.violations = []
        for rule_name, validator in self.rules.items():
            try:
                if not validator(model_instance):
                    self.violations.append(f"Rule '{rule_name}' violated")
            except Exception as e:
                self.violations.append(f"Rule '{rule_name}' error: {str(e)}")
                
        return len(self.violations) == 0
        
    def get_violations(self) -> List[str]:
        """Get validation violations"""
        return self.violations


# Example contract rules
def create_user_contract() -> ModelContract:
    """Create contract for User model"""
    contract = ModelContract()
    
    contract.add_rule(
        "email_format",
        lambda u: "@" in u.email if hasattr(u, 'email') else True
    )
    
    contract.add_rule(
        "name_not_empty",
        lambda u: len(u.name) > 0 if hasattr(u, 'name') else False
    )
    
    contract.add_rule(
        "age_valid",
        lambda u: 0 <= u.age <= 150 if hasattr(u, 'age') else True
    )
    
    return contract


# ============================================================================
# QUANTUM QUERIES - Multi-timeline analytics
# ============================================================================

class QuantumQuery:
    """Execute queries across multiple timelines/states"""
    
    def __init__(self, db_connection):
        self.db = db_connection
        self.timelines: Dict[str, Any] = {}
        self.current_timeline = "main"
        
    def create_timeline(self, name: str) -> None:
        """Create alternative timeline for analysis"""
        self.timelines[name] = {
            "created_at": datetime.now(),
            "records": [],
            "queries": []
        }
        print(f"[QUANTUM] Timeline created: {name}")
        
    def switch_timeline(self, name: str) -> None:
        """Switch to different timeline"""
        if name not in self.timelines:
            raise ValueError(f"Timeline not found: {name}")
        self.current_timeline = name
        print(f"[QUANTUM] Switched to timeline: {name}")
        
    def execute_on_timeline(self, query_type: str, params: Dict[str, Any]) -> List[Any]:
        """Execute query on current timeline"""
        timeline = self.timelines[self.current_timeline]
        timeline["queries"].append({
            "type": query_type,
            "params": params,
            "timestamp": datetime.now()
        })
        return []
        
    def compare_timelines(self, timeline1: str, timeline2: str) -> Dict[str, Any]:
        """Compare results across timelines"""
        if timeline1 not in self.timelines or timeline2 not in self.timelines:
            raise ValueError("One or both timelines not found")
            
        t1_queries = len(self.timelines[timeline1]["queries"])
        t2_queries = len(self.timelines[timeline2]["queries"])
        
        return {
            "timeline1": {
                "name": timeline1,
                "queries": t1_queries
            },
            "timeline2": {
                "name": timeline2,
                "queries": t2_queries
            },
            "difference": abs(t1_queries - t2_queries)
        }


# ============================================================================
# COMPREHENSIVE DEMO
# ============================================================================

def demo_advanced_features():
    """Demonstrate all advanced features"""
    
    print("\n" + "=" * 70)
    print("ADVANCED FEATURES DEMONSTRATION")
    print("=" * 70)
    
    # 1. Query Replay Demo
    print("\n1. QUERY REPLAY")
    print("-" * 70)
    replay = QueryReplay()
    replay.start_recording("user_signup_flow")
    
    replay.record_operation("CREATE_USER", {"email": "john@example.com"})
    replay.record_operation("CREATE_PROFILE", {"user_id": 1})
    replay.record_operation("SEND_EMAIL", {"email": "john@example.com"})
    
    replay.stop_recording()
    replay.replay_session("user_signup_flow")
    stats = replay.get_session_stats("user_signup_flow")
    print(f"Session stats: {stats}")
    
    # 2. Model Blueprints Demo
    print("\n2. MODEL BLUEPRINTS")
    print("-" * 70)
    
    class Product:
        pass
    
    blueprint = ModelBlueprint(Product, style="e-commerce")
    records = blueprint.generate_bulk(5)
    for record in records:
        print(f"Generated: {record['name']} - Price: {record.get('price', 'N/A')}")
    
    # 3. Live Dashboard Demo
    print("\n3. LIVE DASHBOARD")
    print("-" * 70)
    dashboard = LiveDashboard()
    
    # Simulate operations
    for i in range(10):
        dashboard.record_query("SELECT", 0.05 + (i * 0.001))
        dashboard.record_cache_hit() if i % 2 == 0 else dashboard.record_cache_miss()
        dashboard.record_save()
    
    dashboard.display_dashboard()
    
    # 4. Model Contracts Demo
    print("\n4. MODEL CONTRACTS")
    print("-" * 70)
    
    class User:
        def __init__(self, name: str, email: str, age: int):
            self.name = name
            self.email = email
            self.age = age
    
    contract = create_user_contract()
    
    valid_user = User("John", "john@example.com", 25)
    if contract.validate(valid_user):
        print(f"[OK] Valid user: {valid_user.name}")
    else:
        print(f"[FAIL] Invalid user: {contract.get_violations()}")
    
    invalid_user = User("", "invalid", 200)
    if contract.validate(invalid_user):
        print(f"[OK] Valid user: {invalid_user.name}")
    else:
        print(f"[FAIL] Invalid user violations:")
        for v in contract.get_violations():
            print(f"  - {v}")
    
    # 5. Quantum Queries Demo
    print("\n5. QUANTUM QUERIES")
    print("-" * 70)
    
    class MockDB:
        pass
    
    quantum = QuantumQuery(MockDB())
    quantum.create_timeline("scenario_a")
    quantum.create_timeline("scenario_b")
    
    quantum.switch_timeline("scenario_a")
    quantum.execute_on_timeline("SELECT", {"table": "users", "limit": 10})
    quantum.execute_on_timeline("SELECT", {"table": "posts", "limit": 20})
    
    quantum.switch_timeline("scenario_b")
    quantum.execute_on_timeline("SELECT", {"table": "users", "limit": 5})
    
    comparison = quantum.compare_timelines("scenario_a", "scenario_b")
    print(f"Scenario A: {comparison['timeline1']['queries']} queries")
    print(f"Scenario B: {comparison['timeline2']['queries']} queries")
    print(f"Difference: {comparison['difference']} queries")
    
    print("\n" + "=" * 70)
    print("ADVANCED FEATURES DEMO COMPLETE")
    print("=" * 70 + "\n")


if __name__ == "__main__":
    demo_advanced_features()
