"""
Batch Migration Script for Sample Library

Scans the libreria/reggaeton/ directory, analyzes all audio files,
and stores metadata in SQLite database with progress tracking.

Usage:
    python migrate_library.py                    # Run migration with defaults
    python migrate_library.py --force            # Force re-analyze all samples
    python migrate_library.py --dry-run          # Scan only, don't save to DB
    python migrate_library.py --status             # Show current DB statistics

"""
import os
import sys
import sqlite3
import argparse
from pathlib import Path
from dataclasses import dataclass, asdict
from typing import List, Dict, Optional, Any, Tuple
from datetime import datetime

# Audio analysis libraries (optional)
try:
    import numpy as np
    import librosa
    import librosa.feature
    LIBROSA_AVAILABLE = True
except ImportError:
    LIBROSA_AVAILABLE = False
    np = None

try:
    import wave
    import struct
    WAVE_AVAILABLE = True
except ImportError:
    WAVE_AVAILABLE = False


# Constants
DEFAULT_LIBRARY_PATH = Path(
    r"C:\ProgramData\Ableton\Live 12 Suite\Resources\MIDI Remote Scripts\libreria\reggaeton"
)
DEFAULT_DB_PATH = Path(
    r"C:\ProgramData\Ableton\Live 12 Suite\Resources\MIDI Remote Scripts\AbletonMCP_AI\mcp_server\data\samples.db"
)
SUPPORTED_EXTENSIONS = {'.wav', '.aif', '.aiff', '.mp3', '.flac'}

# Role mapping for categorization
ROLE_MAPPING = {
    'kick': 'kick',
    'snare': 'snare',
    'bass': 'bass',
    'fx': 'fx',
    'drumloops': 'drum_loop',
    'drumloop': 'drum_loop',
    'hi-hat': 'hat_closed',
    'hihat': 'hat_closed',
    'hat': 'hat_closed',
    'oneshots': 'oneshot',
    'oneshot': 'oneshot',
    'perc loop': 'perc_loop',
    'perc_loop': 'perc_loop',
    'reggaeton 3': 'synth',
    'sentimientolatino2025': 'multi',
    'sounds presets': 'preset',
    'extra': 'extra',
    'flp': 'project',
}


@dataclass
class SampleFeatures:
    """Complete feature set for a sample."""
    # File info
    path: str
    name: str
    pack: str
    role: str
    
    # Audio properties
    duration: float = 0.0
    sample_rate: int = 44100
    channels: int = 1
    
    # Musical properties
    bpm: float = 0.0
    key: str = ""
    
    # Spectral features
    rms: float = 0.0
    spectral_centroid: float = 0.0
    spectral_rolloff: float = 0.0
    zero_crossing_rate: float = 0.0
    
    # Advanced features
    mfccs: str = ""  # JSON string of list
    onset_strength: float = 0.0
    
    # Analysis metadata
    analysis_type: str = "partial"  # "full" or "partial"
    analyzed_at: str = ""
    file_size: int = 0
    file_modified: float = 0.0


def scan_library(library_path: Path) -> List[Path]:
    """
    Scan library directory for all audio files.
    
    Args:
        library_path: Root directory to scan
        
    Returns:
        List of paths to audio files
    """
    samples = []
    
    if not library_path.exists():
        print(f"[ERROR] Library path not found: {library_path}")
        return samples
    
    for ext in SUPPORTED_EXTENSIONS:
        samples.extend(library_path.rglob(f"*{ext}"))
        samples.extend(library_path.rglob(f"*{ext.upper()}"))
    
    # Remove duplicates and sort
    seen = set()
    unique_samples = []
    for s in samples:
        resolved = s.resolve()
        if resolved not in seen:
            seen.add(resolved)
            unique_samples.append(s)
    
    return sorted(unique_samples)


def detect_role(file_path: Path) -> str:
    """Detect sample role based on folder and filename."""
    path_parts = [p.lower() for p in file_path.parts]
    filename = file_path.name.lower()
    
    for part in path_parts:
        clean_part = part.replace(' ', '_').replace('-', '_').replace('(', '').replace(')', '')
        
        if part in ROLE_MAPPING:
            return ROLE_MAPPING[part]
        if clean_part in ROLE_MAPPING:
            return ROLE_MAPPING[clean_part]
        
        for key, role in ROLE_MAPPING.items():
            if key in part or key in clean_part:
                return role
    
    # Check filename
    if 'kick' in filename:
        return 'kick'
    if 'snare' in filename:
        return 'snare'
    if 'clap' in filename:
        return 'clap'
    if 'hat' in filename or 'hihat' in filename:
        return 'hat_closed'
    if 'bass' in filename:
        return 'bass'
    if 'fx' in filename:
        return 'fx'
    if 'perc' in filename:
        return 'perc'
    
    return 'unknown'


def get_pack_name(file_path: Path, library_path: Path) -> str:
    """Get the pack/folder name relative to library root."""
    try:
        rel_path = file_path.relative_to(library_path)
        return rel_path.parts[0] if rel_path.parts else 'root'
    except ValueError:
        return file_path.parent.name or 'unknown'


def analyze_sample_librosa(sample_path: Path) -> Optional[Dict[str, Any]]:
    """
    Analyze sample using librosa (full analysis).
    
    Args:
        sample_path: Path to audio file
        
    Returns:
        Dictionary with audio features or None on error
    """
    if not LIBROSA_AVAILABLE:
        return None
    
    try:
        # Load audio
        y, sr = librosa.load(str(sample_path), sr=None, mono=True)
        
        # Duration
        duration = librosa.get_duration(y=y, sr=sr)
        
        # RMS (energy)
        rms = float(np.mean(librosa.feature.rms(y=y)))
        rms_db = 20 * np.log10(rms + 1e-10)
        
        # Spectral features
        spectral_centroid = float(np.mean(librosa.feature.spectral_centroid(y=y, sr=sr)))
        spectral_rolloff = float(np.mean(librosa.feature.spectral_rolloff(y=y, sr=sr)))
        zcr = float(np.mean(librosa.feature.zero_crossing_rate(y)))
        
        # MFCCs
        mfccs = librosa.feature.mfcc(y=y, sr=sr, n_mfcc=13)
        mfccs_mean = [float(np.mean(coef)) for coef in mfccs]
        
        # Onset strength
        onset_env = librosa.onset.onset_strength(y=y, sr=sr)
        onset_strength = float(np.mean(onset_env))
        
        # BPM detection
        try:
            tempo, _ = librosa.beat.beat_track(y=y, sr=sr)
            bpm = float(tempo) if isinstance(tempo, (int, float, np.number)) else float(tempo[0])
        except:
            bpm = 0.0
        
        # Key detection
        try:
            chromagram = librosa.feature.chroma_cqt(y=y, sr=sr)
            chroma_avg = np.sum(chromagram, axis=1)
            notes = ['C', 'C#', 'D', 'D#', 'E', 'F', 'F#', 'G', 'G#', 'A', 'A#', 'B']
            key_index = np.argmax(chroma_avg)
            key = notes[key_index]
            
            # Detect minor
            minor_third_idx = (key_index + 3) % 12
            if chroma_avg[minor_third_idx] > chroma_avg[(key_index + 4) % 12]:
                key += 'm'
        except:
            key = ""
        
        # Detect original channels
        try:
            y_orig, _ = librosa.load(str(sample_path), sr=None, mono=False)
            channels = y_orig.shape[0] if len(y_orig.shape) > 1 else 1
        except:
            channels = 1
        
        return {
            "rms": round(rms_db, 2),
            "spectral_centroid": round(spectral_centroid, 2),
            "spectral_rolloff": round(spectral_rolloff, 2),
            "zero_crossing_rate": round(zcr, 4),
            "mfccs": mfccs_mean,
            "onset_strength": round(onset_strength, 4),
            "duration": round(duration, 3),
            "sample_rate": sr,
            "channels": channels,
            "bpm": round(bpm, 1) if bpm > 0 else 0,
            "key": key,
            "analysis_type": "full"
        }
        
    except Exception as e:
        print(f"  [WARN] Librosa analysis failed for {sample_path.name}: {e}")
        return None


def analyze_sample_wave(sample_path: Path) -> Optional[Dict[str, Any]]:
    """
    Analyze sample using wave module (basic info for WAV files).
    
    Args:
        sample_path: Path to audio file
        
    Returns:
        Dictionary with basic audio features or None on error
    """
    if not WAVE_AVAILABLE:
        return None
    
    try:
        # Only works for WAV files
        if sample_path.suffix.lower() != '.wav':
            return None
        
        with wave.open(str(sample_path), 'rb') as wav_file:
            channels = wav_file.getnchannels()
            sample_rate = wav_file.getframerate()
            sample_width = wav_file.getsampwidth()
            n_frames = wav_file.getnframes()
            
            duration = n_frames / sample_rate
            
            # Try to calculate RMS from samples
            rms_db = 0.0
            try:
                # Read a portion of the file for RMS calculation
                frames_to_read = min(n_frames, int(sample_rate * 1))  # Max 1 second
                raw_data = wav_file.readframes(frames_to_read)
                
                if sample_width == 1:
                    fmt = f"{len(raw_data)}B"
                    samples = struct.unpack(fmt, raw_data)
                    samples = [(s - 128) / 128.0 for s in samples]
                elif sample_width == 2:
                    fmt = f"{len(raw_data) // 2}h"
                    samples = struct.unpack(fmt, raw_data)
                    samples = [s / 32768.0 for s in samples]
                elif sample_width == 4:
                    fmt = f"{len(raw_data) // 4}i"
                    samples = struct.unpack(fmt, raw_data)
                    samples = [s / 2147483648.0 for s in samples]
                else:
                    samples = []
                
                if samples:
                    # Calculate RMS
                    if channels > 1:
                        # Interleaved channels - convert to mono
                        mono_samples = []
                        for i in range(0, len(samples) - channels + 1, channels):
                            mono_samples.append(sum(samples[i:i+channels]) / channels)
                        samples = mono_samples
                    
                    rms = (sum(s**2 for s in samples) / len(samples)) ** 0.5
                    rms_db = 20 * (rms + 1e-10).bit_length()  # Approximate
                    
            except Exception:
                pass
            
            return {
                "rms": round(rms_db, 2),
                "spectral_centroid": 0.0,
                "spectral_rolloff": 0.0,
                "zero_crossing_rate": 0.0,
                "mfccs": [],
                "onset_strength": 0.0,
                "duration": round(duration, 3),
                "sample_rate": sample_rate,
                "channels": channels,
                "bpm": 0,
                "key": "",
                "analysis_type": "partial"
            }
            
    except Exception as e:
        return None


def create_placeholder_metadata(sample_path: Path) -> Dict[str, Any]:
    """
    Create basic metadata without audio analysis (fallback).
    
    Args:
        sample_path: Path to audio file
        
    Returns:
        Dictionary with file info and placeholder audio features
    """
    # Try wave module first
    wave_data = analyze_sample_wave(sample_path)
    if wave_data:
        return wave_data
    
    # Ultimate fallback - just file info
    stat = sample_path.stat()
    
    return {
        "rms": 0.0,
        "spectral_centroid": 0.0,
        "spectral_rolloff": 0.0,
        "zero_crossing_rate": 0.0,
        "mfccs": [],
        "onset_strength": 0.0,
        "duration": 0.0,
        "sample_rate": 44100,
        "channels": 1,
        "bpm": 0,
        "key": "",
        "analysis_type": "partial"
    }


def analyze_sample(sample_path: Path, library_path: Path) -> Optional[SampleFeatures]:
    """
    Analyze a sample and return complete features.
    
    Tries librosa first, falls back to wave module, then placeholder.
    
    Args:
        sample_path: Path to audio file
        library_path: Root library path for pack detection
        
    Returns:
        SampleFeatures object or None on error
    """
    # Get file info
    stat = sample_path.stat()
    
    # Detect role and pack
    role = detect_role(sample_path)
    pack = get_pack_name(sample_path, library_path)
    
    # Try analysis methods in order of preference
    audio_features = None
    
    if LIBROSA_AVAILABLE:
        audio_features = analyze_sample_librosa(sample_path)
    
    if audio_features is None:
        audio_features = create_placeholder_metadata(sample_path)
    
    if audio_features is None:
        return None
    
    # Build SampleFeatures
    return SampleFeatures(
        path=str(sample_path.resolve()),
        name=sample_path.name,
        pack=pack,
        role=role,
        duration=audio_features.get("duration", 0.0),
        sample_rate=audio_features.get("sample_rate", 44100),
        channels=audio_features.get("channels", 1),
        bpm=audio_features.get("bpm", 0.0),
        key=audio_features.get("key", ""),
        rms=audio_features.get("rms", 0.0),
        spectral_centroid=audio_features.get("spectral_centroid", 0.0),
        spectral_rolloff=audio_features.get("spectral_rolloff", 0.0),
        zero_crossing_rate=audio_features.get("zero_crossing_rate", 0.0),
        mfccs=str(audio_features.get("mfccs", [])),
        onset_strength=audio_features.get("onset_strength", 0.0),
        analysis_type=audio_features.get("analysis_type", "partial"),
        analyzed_at=datetime.now().isoformat(),
        file_size=stat.st_size,
        file_modified=stat.st_mtime
    )


def init_database(db_path: Path) -> sqlite3.Connection:
    """
    Initialize SQLite database with schema.
    
    Args:
        db_path: Path to database file
        
    Returns:
        Database connection
    """
    # Ensure directory exists
    db_path.parent.mkdir(parents=True, exist_ok=True)
    
    conn = sqlite3.connect(str(db_path))
    cursor = conn.cursor()
    
    # Create samples table
    cursor.execute("""
        CREATE TABLE IF NOT EXISTS samples (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            path TEXT UNIQUE NOT NULL,
            name TEXT NOT NULL,
            pack TEXT,
            role TEXT,
            duration REAL DEFAULT 0.0,
            sample_rate INTEGER DEFAULT 44100,
            channels INTEGER DEFAULT 1,
            bpm REAL DEFAULT 0.0,
            key TEXT,
            rms REAL DEFAULT 0.0,
            spectral_centroid REAL DEFAULT 0.0,
            spectral_rolloff REAL DEFAULT 0.0,
            zero_crossing_rate REAL DEFAULT 0.0,
            mfccs TEXT,
            onset_strength REAL DEFAULT 0.0,
            analysis_type TEXT DEFAULT 'partial',
            analyzed_at TEXT,
            file_size INTEGER DEFAULT 0,
            file_modified REAL DEFAULT 0.0,
            created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
        )
    """)
    
    # Create indexes
    cursor.execute("CREATE INDEX IF NOT EXISTS idx_role ON samples(role)")
    cursor.execute("CREATE INDEX IF NOT EXISTS idx_pack ON samples(pack)")
    cursor.execute("CREATE INDEX IF NOT EXISTS idx_key ON samples(key)")
    cursor.execute("CREATE INDEX IF NOT EXISTS idx_bpm ON samples(bpm)")
    cursor.execute("CREATE INDEX IF NOT EXISTS idx_analysis ON samples(analysis_type)")
    
    # Create migration log table
    cursor.execute("""
        CREATE TABLE IF NOT EXISTS migration_log (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            started_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
            completed_at TIMESTAMP,
            total_samples INTEGER DEFAULT 0,
            analyzed_full INTEGER DEFAULT 0,
            analyzed_partial INTEGER DEFAULT 0,
            errors INTEGER DEFAULT 0,
            duration_seconds REAL DEFAULT 0.0
        )
    """)
    
    conn.commit()
    return conn


def sample_exists(conn: sqlite3.Connection, sample_path: str) -> bool:
    """Check if a sample already exists in database."""
    cursor = conn.cursor()
    cursor.execute("SELECT 1 FROM samples WHERE path = ?", (sample_path,))
    return cursor.fetchone() is not None


def save_sample(conn: sqlite3.Connection, features: SampleFeatures) -> bool:
    """
    Save or update sample features in database.
    
    Args:
        conn: Database connection
        features: SampleFeatures to save
        
    Returns:
        True on success
    """
    cursor = conn.cursor()
    
    data = asdict(features)
    
    cursor.execute("""
        INSERT OR REPLACE INTO samples (
            path, name, pack, role, duration, sample_rate, channels,
            bpm, key, rms, spectral_centroid, spectral_rolloff,
            zero_crossing_rate, mfccs, onset_strength, analysis_type,
            analyzed_at, file_size, file_modified
        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
    """, (
        data['path'], data['name'], data['pack'], data['role'],
        data['duration'], data['sample_rate'], data['channels'],
        data['bpm'], data['key'], data['rms'], data['spectral_centroid'],
        data['spectral_rolloff'], data['zero_crossing_rate'], data['mfccs'],
        data['onset_strength'], data['analysis_type'], data['analyzed_at'],
        data['file_size'], data['file_modified']
    ))
    
    conn.commit()
    return True


def migrate_library(
    library_path: Path,
    db_path: Path,
    force_reanalyze: bool = False,
    dry_run: bool = False
) -> Dict[str, Any]:
    """
    Migrate all samples from library to SQLite database.
    
    Args:
        library_path: Path to sample library
        db_path: Path to SQLite database
        force_reanalyze: Re-analyze samples even if already in DB
        dry_run: Scan only, don't save to database
        
    Returns:
        Migration statistics
    """
    start_time = datetime.now()
    
    # Scan for samples
    print(f"[MIGRATE] Scanning library: {library_path}")
    samples = scan_library(library_path)
    total = len(samples)
    
    if total == 0:
        print("[MIGRATE] No samples found!")
        return {"total": 0, "analyzed": 0, "errors": 0, "skipped": 0}
    
    print(f"[MIGRATE] Found {total} samples")
    
    if dry_run:
        print("[MIGRATE] Dry run - not saving to database")
        for i, sample in enumerate(samples, 1):
            print(f"  {i}/{total}: {sample.name}")
        return {"total": total, "dry_run": True}
    
    # Initialize database
    conn = init_database(db_path)
    
    # Start migration log
    cursor = conn.cursor()
    cursor.execute("INSERT INTO migration_log (started_at) VALUES (CURRENT_TIMESTAMP)")
    migration_id = cursor.lastrowid
    conn.commit()
    
    # Process samples
    analyzed_full = 0
    analyzed_partial = 0
    errors = 0
    skipped = 0
    
    for i, sample_path in enumerate(samples, 1):
        abs_path = str(sample_path.resolve())
        
        # Check if already analyzed
        if not force_reanalyze and sample_exists(conn, abs_path):
            skipped += 1
            print(f"\r[MIGRATE] {i}/{total}: {sample_path.name} (skipped - already in DB)", end="")
            continue
        
        print(f"\r[MIGRATE] {i}/{total}: {sample_path.name}", end="")
        sys.stdout.flush()
        
        try:
            features = analyze_sample(sample_path, library_path)
            
            if features:
                save_sample(conn, features)
                
                if features.analysis_type == "full":
                    analyzed_full += 1
                else:
                    analyzed_partial += 1
            else:
                errors += 1
                print(f"\n  [ERROR] Failed to analyze: {sample_path.name}")
                
        except Exception as e:
            errors += 1
            print(f"\n  [ERROR] Exception analyzing {sample_path.name}: {e}")
    
    print()  # New line after progress
    
    # Update migration log
    duration = (datetime.now() - start_time).total_seconds()
    cursor.execute("""
        UPDATE migration_log 
        SET completed_at = CURRENT_TIMESTAMP,
            total_samples = ?,
            analyzed_full = ?,
            analyzed_partial = ?,
            errors = ?,
            duration_seconds = ?
        WHERE id = ?
    """, (total, analyzed_full, analyzed_partial, errors, duration, migration_id))
    conn.commit()
    conn.close()
    
    return {
        "total": total,
        "analyzed_full": analyzed_full,
        "analyzed_partial": analyzed_partial,
        "errors": errors,
        "skipped": skipped,
        "duration_seconds": duration,
        "db_path": str(db_path)
    }


def get_migration_status(db_path: Path) -> Dict[str, Any]:
    """
    Get current database statistics.
    
    Args:
        db_path: Path to SQLite database
        
    Returns:
        Statistics dictionary
    """
    if not db_path.exists():
        return {"error": "Database not found", "db_path": str(db_path)}
    
    conn = sqlite3.connect(str(db_path))
    cursor = conn.cursor()
    
    # Total samples
    cursor.execute("SELECT COUNT(*) FROM samples")
    total = cursor.fetchone()[0]
    
    # By role
    cursor.execute("SELECT role, COUNT(*) FROM samples GROUP BY role")
    by_role = {row[0]: row[1] for row in cursor.fetchall()}
    
    # By analysis type
    cursor.execute("SELECT analysis_type, COUNT(*) FROM samples GROUP BY analysis_type")
    by_analysis = {row[0]: row[1] for row in cursor.fetchall()}
    
    # By pack
    cursor.execute("SELECT pack, COUNT(*) FROM samples GROUP BY pack")
    by_pack = {row[0]: row[1] for row in cursor.fetchall()}
    
    # Averages
    cursor.execute("""
        SELECT 
            AVG(duration),
            AVG(bpm),
            AVG(rms),
            AVG(spectral_centroid)
        FROM samples
    """)
    avg_row = cursor.fetchone()
    
    # Last migration
    cursor.execute("""
        SELECT started_at, completed_at, total_samples, errors, duration_seconds
        FROM migration_log
        ORDER BY id DESC
        LIMIT 1
    """)
    last_migration = cursor.fetchone()
    
    conn.close()
    
    return {
        "total_samples": total,
        "by_role": by_role,
        "by_analysis_type": by_analysis,
        "by_pack": by_pack,
        "averages": {
            "duration": round(avg_row[0], 3) if avg_row[0] else 0,
            "bpm": round(avg_row[1], 1) if avg_row[1] else 0,
            "rms": round(avg_row[2], 2) if avg_row[2] else 0,
            "spectral_centroid": round(avg_row[3], 2) if avg_row[3] else 0,
        },
        "last_migration": {
            "started": last_migration[0] if last_migration else None,
            "completed": last_migration[1] if last_migration else None,
            "total_samples": last_migration[2] if last_migration else 0,
            "errors": last_migration[3] if last_migration else 0,
            "duration_seconds": last_migration[4] if last_migration else 0,
        } if last_migration else None,
        "db_path": str(db_path),
        "db_size_mb": round(db_path.stat().st_size / (1024 * 1024), 2)
    }


def print_report(stats: Dict[str, Any]):
    """Print formatted migration report."""
    print("\n" + "=" * 60)
    print("MIGRATION REPORT")
    print("=" * 60)
    
    if "error" in stats:
        print(f"Error: {stats['error']}")
        return
    
    print(f"\nTotal samples: {stats['total']}")
    
    if stats.get('dry_run'):
        print("Mode: Dry run (no changes saved)")
        return
    
    print(f"Full analysis: {stats.get('analyzed_full', 0)}")
    print(f"Partial analysis: {stats.get('analyzed_partial', 0)}")
    print(f"Skipped (already in DB): {stats.get('skipped', 0)}")
    print(f"Errors: {stats.get('errors', 0)}")
    print(f"Duration: {stats.get('duration_seconds', 0):.1f} seconds")
    print(f"Database: {stats.get('db_path', 'N/A')}")
    
    print("\n" + "=" * 60)


def print_status(status: Dict[str, Any]):
    """Print database status report."""
    print("\n" + "=" * 60)
    print("DATABASE STATUS")
    print("=" * 60)
    
    if "error" in status:
        print(f"Error: {status['error']}")
        return
    
    print(f"\nTotal samples: {status['total_samples']}")
    print(f"Database size: {status['db_size_mb']} MB")
    print(f"Database path: {status['db_path']}")
    
    print("\nBy Role:")
    for role, count in sorted(status['by_role'].items()):
        print(f"  {role}: {count}")
    
    print("\nBy Analysis Type:")
    for atype, count in status['by_analysis_type'].items():
        print(f"  {atype}: {count}")
    
    print("\nAverages:")
    avg = status['averages']
    print(f"  Duration: {avg['duration']}s")
    print(f"  BPM: {avg['bpm']}")
    print(f"  RMS: {avg['rms']} dB")
    print(f"  Spectral Centroid: {avg['spectral_centroid']} Hz")
    
    if status.get('last_migration'):
        lm = status['last_migration']
        print(f"\nLast Migration:")
        print(f"  Started: {lm['started']}")
        print(f"  Completed: {lm['completed']}")
        print(f"  Samples: {lm['total_samples']}")
        print(f"  Errors: {lm['errors']}")
        print(f"  Duration: {lm['duration_seconds']:.1f}s")
    
    print("\n" + "=" * 60)


def main():
    """Command-line interface for migration script."""
    parser = argparse.ArgumentParser(
        description="Migrate sample library to SQLite database",
        formatter_class=argparse.RawDescriptionHelpFormatter,
        epilog="""
Examples:
    python migrate_library.py                    # Run migration
    python migrate_library.py --force            # Force re-analyze all
    python migrate_library.py --dry-run          # Scan only
    python migrate_library.py --status           # Show database stats
        """
    )
    
    parser.add_argument(
        "--library",
        type=str,
        default=str(DEFAULT_LIBRARY_PATH),
        help=f"Path to sample library (default: {DEFAULT_LIBRARY_PATH})"
    )
    
    parser.add_argument(
        "--db",
        type=str,
        default=str(DEFAULT_DB_PATH),
        help=f"Path to SQLite database (default: {DEFAULT_DB_PATH})"
    )
    
    parser.add_argument(
        "--force",
        action="store_true",
        help="Force re-analysis of all samples"
    )
    
    parser.add_argument(
        "--dry-run",
        action="store_true",
        help="Scan only, don't save to database"
    )
    
    parser.add_argument(
        "--status",
        action="store_true",
        help="Show database status and exit"
    )
    
    parser.add_argument(
        "--reset",
        action="store_true",
        help="Delete database and start fresh"
    )
    
    args = parser.parse_args()
    
    library_path = Path(args.library)
    db_path = Path(args.db)
    
    # Handle reset
    if args.reset:
        if db_path.exists():
            print(f"[RESET] Deleting database: {db_path}")
            db_path.unlink()
        else:
            print("[RESET] Database does not exist")
    
    # Show status
    if args.status:
        status = get_migration_status(db_path)
        print_status(status)
        return
    
    # Run migration
    print(f"[MIGRATE] Library: {library_path}")
    print(f"[MIGRATE] Database: {db_path}")
    print(f"[MIGRATE] Librosa available: {LIBROSA_AVAILABLE}")
    
    stats = migrate_library(
        library_path=library_path,
        db_path=db_path,
        force_reanalyze=args.force,
        dry_run=args.dry_run
    )
    
    print_report(stats)
    
    # Show final status
    if not args.dry_run:
        status = get_migration_status(db_path)
        print_status(status)


if __name__ == "__main__":
    main()