"""
Database schema for Dynamic Highscores system.

This module defines the SQLite database schema for the Dynamic Highscores system,
which integrates benchmark selection, model evaluation, and leaderboard functionality.
"""

import sqlite3
import os
import json
import threading
from datetime import datetime, timedelta
import pandas as pd

class ThreadLocalDB:
    """Thread-local database connection manager."""
    
    _thread_local = threading.local()
    
    def __init__(self, db_path):
        """Initialize with database path."""
        self.db_path = db_path
    
    def get_connection(self):
        """Get a thread-local database connection."""
        if not hasattr(self._thread_local, 'conn') or self._thread_local.conn is None:
            self._thread_local.conn = sqlite3.connect(self.db_path)
            self._thread_local.conn.row_factory = sqlite3.Row
        return self._thread_local.conn
    
    def get_cursor(self):
        """Get a cursor from the thread-local connection."""
        conn = self.get_connection()
        if not hasattr(self._thread_local, 'cursor') or self._thread_local.cursor is None:
            self._thread_local.cursor = conn.cursor()
        return self._thread_local.cursor
    
    def close(self):
        """Close the thread-local connection if it exists."""
        if hasattr(self._thread_local, 'conn') and self._thread_local.conn is not None:
            if hasattr(self._thread_local, 'cursor') and self._thread_local.cursor is not None:
                self._thread_local.cursor.close()
                self._thread_local.cursor = None
            self._thread_local.conn.close()
            self._thread_local.conn = None

class DynamicHighscoresDB:
    """Database manager for the Dynamic Highscores system."""
    
    def __init__(self, db_path="dynamic_highscores.db"):
        """Initialize the database connection and create tables if they don't exist."""
        self.db_path = db_path
        self.thread_local_db = ThreadLocalDB(db_path)
        self.create_tables()
    
    def get_conn(self):
        """Get the thread-local database connection."""
        return self.thread_local_db.get_connection()
    
    def get_cursor(self):
        """Get the thread-local database cursor."""
        return self.thread_local_db.get_cursor()
    
    def close(self):
        """Close the thread-local database connection."""
        self.thread_local_db.close()
    
    def create_tables(self):
        """Create all necessary tables if they don't exist."""
        cursor = self.get_cursor()
        conn = self.get_conn()
        
        # Users table - stores user information
        cursor.execute('''
        CREATE TABLE IF NOT EXISTS users (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            username TEXT UNIQUE NOT NULL,
            hf_user_id TEXT UNIQUE NOT NULL,
            is_admin BOOLEAN DEFAULT 0,
            last_submission_date TEXT,
            created_at TEXT DEFAULT CURRENT_TIMESTAMP
        )
        ''')
        
        # Benchmarks table - stores information about available benchmarks
        cursor.execute('''
        CREATE TABLE IF NOT EXISTS benchmarks (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            name TEXT NOT NULL,
            dataset_id TEXT NOT NULL,
            description TEXT,
            metrics TEXT,  -- JSON string of metrics
            created_at TEXT DEFAULT CURRENT_TIMESTAMP
        )
        ''')
        
        # Models table - stores information about submitted models
        cursor.execute('''
        CREATE TABLE IF NOT EXISTS models (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            name TEXT NOT NULL,
            hf_model_id TEXT NOT NULL,
            user_id INTEGER NOT NULL,
            tag TEXT NOT NULL,  -- One of: Merge, Agent, Reasoning, Coding, etc.
            parameters TEXT,  -- Number of parameters (can be NULL)
            description TEXT,
            created_at TEXT DEFAULT CURRENT_TIMESTAMP,
            FOREIGN KEY (user_id) REFERENCES users (id),
            UNIQUE (hf_model_id, user_id)
        )
        ''')
        
        # Evaluations table - stores evaluation results
        cursor.execute('''
        CREATE TABLE IF NOT EXISTS evaluations (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            model_id INTEGER NOT NULL,
            benchmark_id INTEGER NOT NULL,
            status TEXT NOT NULL,  -- pending, running, completed, failed
            results TEXT,  -- JSON string of results
            score REAL,  -- Overall score (can be NULL)
            submitted_at TEXT DEFAULT CURRENT_TIMESTAMP,
            started_at TEXT,
            completed_at TEXT,
            FOREIGN KEY (model_id) REFERENCES models (id),
            FOREIGN KEY (benchmark_id) REFERENCES benchmarks (id)
        )
        ''')
        
        # Queue table - stores evaluation queue
        cursor.execute('''
        CREATE TABLE IF NOT EXISTS queue (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            evaluation_id INTEGER NOT NULL,
            priority INTEGER DEFAULT 0,  -- Higher number = higher priority
            added_at TEXT DEFAULT CURRENT_TIMESTAMP,
            FOREIGN KEY (evaluation_id) REFERENCES evaluations (id)
        )
        ''')
        
        conn.commit()
    
    # User management methods
    def add_user(self, username, hf_user_id, is_admin=False):
        """Add a new user to the database."""
        cursor = self.get_cursor()
        conn = self.get_conn()
        
        try:
            cursor.execute(
                "INSERT INTO users (username, hf_user_id, is_admin) VALUES (?, ?, ?)",
                (username, hf_user_id, is_admin)
            )
            conn.commit()
            return cursor.lastrowid
        except sqlite3.IntegrityError:
            # User already exists
            cursor.execute(
                "SELECT id FROM users WHERE hf_user_id = ?",
                (hf_user_id,)
            )
            row = cursor.fetchone()
            return row[0] if row else None
    
    def get_user(self, hf_user_id):
        """Get user information by HuggingFace user ID."""
        cursor = self.get_cursor()
        
        cursor.execute(
            "SELECT * FROM users WHERE hf_user_id = ?",
            (hf_user_id,)
        )
        row = cursor.fetchone()
        return dict(row) if row else None
    
    def get_user_by_username(self, username):
        """Get user information by username."""
        cursor = self.get_cursor()
        
        cursor.execute(
            "SELECT * FROM users WHERE username = ?",
            (username,)
        )
        row = cursor.fetchone()
        return dict(row) if row else None
    
    def can_submit_today(self, user_id):
        """Check if a user can submit a benchmark evaluation today."""
        cursor = self.get_cursor()
        
        cursor.execute(
            "SELECT is_admin, last_submission_date FROM users WHERE id = ?",
            (user_id,)
        )
        result = cursor.fetchone()
        
        if not result:
            return False
        
        user_data = dict(result)
        
        # Admin can always submit
        if user_data['is_admin']:
            return True
        
        # If no previous submission, user can submit
        if not user_data['last_submission_date']:
            return True
        
        # Check if last submission was before today
        last_date = datetime.fromisoformat(user_data['last_submission_date'])
        today = datetime.now().replace(hour=0, minute=0, second=0, microsecond=0)
        
        return last_date < today
    
    def update_submission_date(self, user_id):
        """Update the last submission date for a user."""
        cursor = self.get_cursor()
        conn = self.get_conn()
        
        current_time = datetime.now().isoformat()
        cursor.execute(
            "UPDATE users SET last_submission_date = ? WHERE id = ?",
            (current_time, user_id)
        )
        conn.commit()
    
    # Benchmark management methods
    def add_benchmark(self, name, dataset_id, description="", metrics=None):
        """Add a new benchmark to the database."""
        cursor = self.get_cursor()
        conn = self.get_conn()
        
        if metrics is None:
            metrics = {}
        
        metrics_json = json.dumps(metrics)
        
        try:
            cursor.execute(
                "INSERT INTO benchmarks (name, dataset_id, description, metrics) VALUES (?, ?, ?, ?)",
                (name, dataset_id, description, metrics_json)
            )
            conn.commit()
            return cursor.lastrowid
        except sqlite3.IntegrityError:
            # Benchmark already exists with this dataset_id
            cursor.execute(
                "SELECT id FROM benchmarks WHERE dataset_id = ?",
                (dataset_id,)
            )
            row = cursor.fetchone()
            return row[0] if row else None
    
    def get_benchmarks(self):
        """Get all available benchmarks."""
        cursor = self.get_cursor()
        
        cursor.execute("SELECT * FROM benchmarks")
        benchmarks = [dict(row) for row in cursor.fetchall()]
        
        # Parse metrics JSON
        for benchmark in benchmarks:
            if benchmark['metrics']:
                benchmark['metrics'] = json.loads(benchmark['metrics'])
            else:
                benchmark['metrics'] = {}
        
        return benchmarks
    
    def get_benchmark(self, benchmark_id):
        """Get benchmark information by ID."""
        cursor = self.get_cursor()
        
        cursor.execute(
            "SELECT * FROM benchmarks WHERE id = ?",
            (benchmark_id,)
        )
        row = cursor.fetchone()
        benchmark = dict(row) if row else None
        
        if benchmark and benchmark['metrics']:
            benchmark['metrics'] = json.loads(benchmark['metrics'])
        
        return benchmark
    
    # Model management methods
    def add_model(self, name, hf_model_id, user_id, tag, parameters=None, description=""):
        """Add a new model to the database."""
        cursor = self.get_cursor()
        conn = self.get_conn()
        
        try:
            cursor.execute(
                "INSERT INTO models (name, hf_model_id, user_id, tag, parameters, description) VALUES (?, ?, ?, ?, ?, ?)",
                (name, hf_model_id, user_id, tag, parameters, description)
            )
            conn.commit()
            return cursor.lastrowid
        except sqlite3.IntegrityError:
            # Model already exists for this user
            cursor.execute(
                "SELECT id FROM models WHERE hf_model_id = ? AND user_id = ?",
                (hf_model_id, user_id)
            )
            row = cursor.fetchone()
            return row[0] if row else None
    
    def get_models(self, tag=None):
        """Get all models, optionally filtered by tag."""
        cursor = self.get_cursor()
        
        if tag and tag.lower() != "all":
            cursor.execute(
                "SELECT * FROM models WHERE tag = ?",
                (tag,)
            )
        else:
            cursor.execute("SELECT * FROM models")
        
        return [dict(row) for row in cursor.fetchall()]
    
    def get_model(self, model_id):
        """Get model information by ID."""
        cursor = self.get_cursor()
        
        cursor.execute(
            "SELECT * FROM models WHERE id = ?",
            (model_id,)
        )
        row = cursor.fetchone()
        return dict(row) if row else None
    
# Evaluation management methods
    def add_evaluation(self, model_id, benchmark_id, priority=0):
        """Add a new evaluation to the database and queue."""
        cursor = self.get_cursor()
        conn = self.get_conn()
        
        # First, add the evaluation
        cursor.execute(
            "INSERT INTO evaluations (model_id, benchmark_id, status) VALUES (?, ?, 'pending')",
            (model_id, benchmark_id)
        )
        evaluation_id = cursor.lastrowid
        
        # Then, add it to the queue
        cursor.execute(
            "INSERT INTO queue (evaluation_id, priority) VALUES (?, ?)",
            (evaluation_id, priority)
        )
        
        conn.commit()
        return evaluation_id
    
    def update_evaluation_status(self, evaluation_id, status, results=None, score=None):
        """Update the status of an evaluation."""
        cursor = self.get_cursor()
        conn = self.get_conn()
        
        params = [status, evaluation_id]
        sql = "UPDATE evaluations SET status = ?"
        
        if results is not None:
            sql += ", results = ?"
            params.insert(1, json.dumps(results))
        
        if score is not None:
            sql += ", score = ?"
            params.insert(1 if results is None else 2, score)
        
        if status in ['completed', 'failed']:
            sql += ", completed_at = datetime('now')"
        elif status == 'running':
            sql += ", started_at = datetime('now')"
        
        sql += " WHERE id = ?"
        
        cursor.execute(sql, params)
        conn.commit()
    
    def get_next_in_queue(self):
        """Get the next evaluation in the queue."""
        cursor = self.get_cursor()
        
        cursor.execute("""
            SELECT q.*, e.id as evaluation_id, e.model_id, e.benchmark_id, e.status
            FROM queue q
            JOIN evaluations e ON q.evaluation_id = e.id
            WHERE e.status = 'pending'
            ORDER BY q.priority DESC, q.added_at ASC
            LIMIT 1
        """)
        
        row = cursor.fetchone()
        return dict(row) if row else None
    
    def get_evaluation_results(self, model_id=None, benchmark_id=None, tag=None, status=None, limit=None):
        """Get evaluation results, optionally filtered by model, benchmark, tag, or status."""
        cursor = self.get_cursor()
        
        sql = """
            SELECT e.id, e.model_id, e.benchmark_id, e.status, e.results, e.score, 
                   e.submitted_at, e.started_at, e.completed_at, m.name as model_name, m.tag, 
                   b.name as benchmark_name
            FROM evaluations e
            JOIN models m ON e.model_id = m.id
            JOIN benchmarks b ON e.benchmark_id = b.id
            WHERE 1=1
        """
        
        params = []
        
        if status:
            sql += " AND e.status = ?"
            params.append(status)
        
        if model_id:
            sql += " AND e.model_id = ?"
            params.append(model_id)
        
        if benchmark_id and benchmark_id != "all" and benchmark_id.lower() != "all":
            sql += " AND e.benchmark_id = ?"
            params.append(benchmark_id)
        
        if tag and tag.lower() != "all":
            sql += " AND m.tag = ?"
            params.append(tag)
        
        sql += " ORDER BY e.submitted_at DESC"
        
        if limit:
            sql += " LIMIT ?"
            params.append(limit)
        
        cursor.execute(sql, params)
        results = [dict(row) for row in cursor.fetchall()]
        
        # Parse results JSON
        for result in results:
            if result['results']:
                try:
                    result['results'] = json.loads(result['results'])
                except:
                    result['results'] = {}
        
        return results
    
    def get_leaderboard_df(self, tag=None, benchmark_id=None):
        """Get a pandas DataFrame of the leaderboard, optionally filtered by tag and benchmark."""
        results = self.get_evaluation_results(tag=tag, benchmark_id=benchmark_id, status="completed")
        
        if not results:
            return pd.DataFrame()
        
        # Create a list of dictionaries for the DataFrame
        leaderboard_data = []
        
        for result in results:
            entry = {
                'model_name': result['model_name'],
                'tag': result['tag'],
                'benchmark_name': result['benchmark_name'],
                'score': result['score'],
                'completed_at': result['completed_at']
            }
            
            # Add any additional metrics from results
            if result['results'] and isinstance(result['results'], dict):
                for key, value in result['results'].items():
                    if isinstance(value, (int, float)) and key not in entry:
                        entry[key] = value
            
            leaderboard_data.append(entry)
        
        # Convert to DataFrame
        df = pd.DataFrame(leaderboard_data)
        
        # Sort by score (descending)
        if not df.empty and 'score' in df.columns:
            df = df.sort_values('score', ascending=False)
        
        return df