"""
LeRobotLab Tools - Convert Module

Handles conversion of robot datasets to different formats (HDF5, Zarr, Parquet).
"""

import os
from pathlib import Path
from typing import Dict, Any, Optional, List

import click


def convert_datasets(
    selection_data: Dict[str, Any],
    output_path: str,
    input_path: Optional[str] = None,
    format: str = 'hdf5',
    verbose: bool = False
) -> None:
    try:
        # Create output directory if it doesn't exist
        output_dir = Path(output_path)
        output_dir.mkdir(parents=True, exist_ok=True)
        
        if verbose:
            click.echo(f"Created output directory: {output_dir.absolute()}")
        
        # Handle input path
        if input_path is None:
            if verbose:
                click.echo("No input path provided - datasets will be downloaded first")
            # Here would trigger download process
            input_dir = output_dir / "temp_downloads"
            click.echo("Downloading datasets for conversion...")
            # Would call download function here
        else:
            input_dir = Path(input_path)
            if not input_dir.exists():
                raise click.ClickException(f"Input directory does not exist: {input_path}")
        
        # Get datasets from selection
        datasets = selection_data.get('datasets', [])
        
        if verbose:
            metadata = selection_data.get('metadata', {})
            click.echo(f"Converting {len(datasets)} datasets to {format.upper()} format...")
            if 'total_episodes' in metadata:
                click.echo(f"Total episodes to convert: {metadata['total_episodes']}")
        
        # Process each dataset
        for i, dataset in enumerate(datasets, 1):
            repo_id = dataset['repo_id']
            selected_videos = dataset['selected_videos']
            
            if verbose:
                click.echo(f"\n[{i}/{len(datasets)}] Converting dataset: {repo_id}")
                click.echo(f"Selected videos: {', '.join(selected_videos)}")
            
            # Placeholder implementation - echo conversion actions
            click.echo(f"Converting dataset: {repo_id}")
            
            # Create output file path
            output_file = _get_output_filename(repo_id, format, output_dir)
            click.echo(f"  Output file: {output_file}")
            
            for video in selected_videos:
                click.echo(f"  - Converting video stream: {video}")
                # Conversion logic based on format
                if format == 'droid':
                    _convert_to_droid(video, repo_id, input_dir, output_file, verbose)
                elif format == 'vjepa2-ac':
                    _convert_to_vjepa2_ac(video, repo_id, input_dir, output_file, verbose)
                else:
                    raise click.ClickException(f"Unsupported format: {format}")
            
            if verbose:
                click.echo(f"  -> Dataset {repo_id} converted successfully")
        
        click.echo(f"\nAll {len(datasets)} datasets converted to {format.upper()} format")
        click.echo(f"Output directory: {output_dir.absolute()}")
        
        # Clean up temporary downloads if they were created
        if input_path is None and input_dir.name == "temp_downloads":
            if verbose:
                click.echo("Cleaning up temporary download files...")
        
    except Exception as e:
        raise click.ClickException(f"Conversion failed: {e}")


def validate_output_path(output_path: str) -> Path:
    try:
        path = Path(output_path)
        
        # Check if parent directory is writable
        parent = path.parent
        if not parent.exists():
            raise click.ClickException(f"Parent directory does not exist: {parent}")
        
        if not os.access(parent, os.W_OK):
            raise click.ClickException(f"No write permission for directory: {parent}")
        
        return path
        
    except Exception as e:
        if isinstance(e, click.ClickException):
            raise
        raise click.ClickException(f"Invalid output path: {e}")


def validate_input_path(input_path: str) -> Path:
    try:
        path = Path(input_path)
        
        if not path.exists():
            raise click.ClickException(f"Input directory does not exist: {input_path}")
        
        if not path.is_dir():
            raise click.ClickException(f"Input path is not a directory: {input_path}")
        
        if not os.access(path, os.R_OK):
            raise click.ClickException(f"No read permission for directory: {input_path}")
        
        return path
        
    except Exception as e:
        if isinstance(e, click.ClickException):
            raise
        raise click.ClickException(f"Invalid input path: {e}")


def get_supported_formats() -> List[str]:
    return ['droid', 'vjepa2-ac']


def validate_format(format: str) -> str:
    format_lower = format.lower()
    supported = get_supported_formats()
    
    if format_lower not in supported:
        raise click.ClickException(
            f"Unsupported format '{format}'. Supported formats: {', '.join(supported)}"
        )
    
    return format_lower


def _get_output_filename(repo_id: str, format: str, output_dir: Path) -> Path:
    # Clean repo_id for filename (replace slashes with underscores)
    clean_repo_id = repo_id.replace('/', '_').replace('\\', '_')
    
    # Add appropriate extension
    extensions = {
        'droid': '.droid',
        'vjepa2-ac': '.vjepa2'
    }
    
    extension = extensions.get(format, f'.{format}')
    filename = f"{clean_repo_id}{extension}"
    
    return output_dir / filename


def estimate_conversion_time(selection_data: Dict[str, Any]) -> Optional[str]:
    metadata = selection_data.get('metadata', {})
    total_frames = metadata.get('total_frames')
    
    if total_frames:
        # Rough estimate: assume ~1000 frames per second processing
        estimated_seconds = total_frames / 1000
        
        if estimated_seconds < 60:
            return f"~{estimated_seconds:.0f} seconds"
        elif estimated_seconds < 3600:
            return f"~{estimated_seconds / 60:.1f} minutes"
        else:
            return f"~{estimated_seconds / 3600:.1f} hours"
    
    return None


def _convert_to_droid(video_stream: str, repo_id: str, input_dir: Path, output_file: Path, verbose: bool = False) -> None:
    """
    Placeholder function for converting video streams to DROID format.
    
    Args:
        video_stream: Name of the video stream to convert (e.g., 'observation.images.front')
        repo_id: Repository ID of the dataset
        input_dir: Directory containing the input dataset
        output_file: Path where the converted file should be saved
        verbose: Whether to enable verbose logging
    """
    if verbose:
        click.echo(f"    Converting {video_stream} to DROID format...")
        click.echo(f"    Input: {input_dir}")
        click.echo(f"    Output: {output_file}")
    
    # TODO: Implement DROID conversion logic
    # This would include:
    # - Loading robot trajectory data
    # - Converting to DROID's action space representation
    # - Handling observation encoding for DROID's visual processing
    # - Saving in DROID-compatible format
    pass


def _convert_to_vjepa2_ac(video_stream: str, repo_id: str, input_dir: Path, output_file: Path, verbose: bool = False) -> None:
    """
    Placeholder function for converting video streams to V-JEPA2-AC format.
    
    Args:
        video_stream: Name of the video stream to convert (e.g., 'observation.images.front')
        repo_id: Repository ID of the dataset
        input_dir: Directory containing the input dataset
        output_file: Path where the converted file should be saved
        verbose: Whether to enable verbose logging
    """
    if verbose:
        click.echo(f"    Converting {video_stream} to V-JEPA2-AC format...")
        click.echo(f"    Input: {input_dir}")
        click.echo(f"    Output: {output_file}")
    
    # TODO: Implement V-JEPA2-AC conversion logic
    # This would include:
    # - Processing video frames for V-JEPA2's visual encoder
    # - Converting action sequences for actor-critic training
    # - Handling temporal sequences and masking strategies
    # - Saving in V-JEPA2-AC training format
    pass 