glazing.cli.convert

Convert command implementation.

convert

CLI commands for converting datasets to JSON Lines format.

This module provides commands for converting linguistic datasets from their native formats (XML, database) to JSON Lines format for efficient processing.

Commands

convert dataset Convert a specific dataset or all datasets to JSON Lines. convert list List available datasets for conversion. convert info Get information about a dataset's conversion process.

CLASS	DESCRIPTION
DatasetInfoDict	Type for dataset information.

FUNCTION	DESCRIPTION
convert	Convert linguistic datasets to JSON Lines format.
convert_dataset_cmd	Convert a dataset to JSON Lines format.
convert_framenet	Convert FrameNet XML frames to JSON Lines with lexical units.
convert_propbank	Convert PropBank XML framesets to JSON Lines.
convert_verbnet	Convert VerbNet XML files to JSON Lines.
convert_wordnet	Convert WordNet database to JSON Lines.
dataset_info_cmd	Get information about a dataset's conversion process.
list_datasets	List available datasets for conversion.

Classes

DatasetInfoDict

Bases: TypedDict

Type for dataset information.

Functions

convert() -> None

Convert linguistic datasets to JSON Lines format.

Source code in src/glazing/cli/convert.py

@click.group()
def convert() -> None:
    """Convert linguistic datasets to JSON Lines format."""

convert_dataset_cmd(dataset: DatasetName, input_dir: str | Path, output_dir: str | Path, verbose: bool) -> None

Convert a dataset to JSON Lines format.

Examples:

Convert VerbNet: $ glazing convert dataset --dataset verbnet \ --input-dir vn3.4/verbnet3.4 --output-dir output/

Convert all datasets: $ glazing convert dataset --dataset all --input-dir data/ --output-dir output/

Source code in src/glazing/cli/convert.py

@convert.command(name="dataset")
@click.option(
    "--dataset",
    type=click.Choice(["verbnet", "propbank", "wordnet", "framenet", "all"]),
    required=True,
    help="Dataset to convert.",
)
@click.option(
    "--input-dir",
    type=click.Path(exists=True, file_okay=False, dir_okay=True),
    required=True,
    help="Input directory containing dataset files.",
)
@click.option(
    "--output-dir",
    type=click.Path(file_okay=False, dir_okay=True),
    required=True,
    help="Output directory for JSON Lines files.",
)
@click.option(
    "--verbose",
    "-v",
    is_flag=True,
    help="Show verbose output.",
)
def convert_dataset_cmd(
    dataset: DatasetName, input_dir: str | Path, output_dir: str | Path, verbose: bool
) -> None:
    """Convert a dataset to JSON Lines format.

    Examples
    --------
    Convert VerbNet:
        $ glazing convert dataset --dataset verbnet \\
            --input-dir vn3.4/verbnet3.4 --output-dir output/

    Convert all datasets:
        $ glazing convert dataset --dataset all --input-dir data/ --output-dir output/
    """
    try:
        # Ensure Path objects
        input_dir = Path(input_dir)
        output_dir = Path(output_dir)

        # Create output directory if it doesn't exist
        output_dir.mkdir(parents=True, exist_ok=True)

        if dataset == "all":
            datasets_to_convert = ["verbnet", "propbank", "wordnet", "framenet"]
        else:
            datasets_to_convert = [dataset]

        for ds in datasets_to_convert:
            _convert_single_dataset(ds, input_dir, output_dir, verbose)

        console.print("\n[bold green]✓ Conversion complete![/bold green]")

    except FileNotFoundError as e:
        console.print(f"[red]✗ Input directory not found: {e}[/red]")
        sys.exit(1)
    except PermissionError as e:
        console.print(f"[red]✗ Permission denied: {e}[/red]")
        sys.exit(1)
    except (ValueError, TypeError, RuntimeError) as e:
        console.print(f"[red]✗ Conversion failed: {e}[/red]")
        if verbose:
            traceback.print_exc()
        sys.exit(1)

convert_framenet(input_dir: Path, output_dir: Path, verbose: bool = False) -> None

Convert FrameNet XML frames to JSON Lines with lexical units.

PARAMETER	DESCRIPTION
input_dir	Directory containing FrameNet XML files (should have frame/ subdirectory). TYPE: Path
output_dir	Directory to write JSON Lines files to. TYPE: Path
verbose	Show verbose output. TYPE: bool DEFAULT: False

Source code in src/glazing/cli/convert.py

def convert_framenet(input_dir: Path, output_dir: Path, verbose: bool = False) -> None:
    """Convert FrameNet XML frames to JSON Lines with lexical units.

    Parameters
    ----------
    input_dir : Path
        Directory containing FrameNet XML files (should have frame/ subdirectory).
    output_dir : Path
        Directory to write JSON Lines files to.
    verbose : bool
        Show verbose output.
    """
    converter = FrameNetConverter()

    # FrameNet has frames in a subdirectory
    frames_dir = input_dir / "frame"
    if not frames_dir.exists():
        frames_dir = input_dir  # Fallback to input_dir if no frame/ subdirectory

    output_file = output_dir / "framenet.jsonl"

    with Progress(
        SpinnerColumn(),
        TextColumn("[progress.description]{task.description}"),
        BarColumn(),
        TextColumn("[progress.percentage]{task.percentage:>3.0f}%"),
        TimeElapsedColumn(),
        console=console,
    ) as progress:
        task = progress.add_task("Converting FrameNet frames and lexical units...", total=None)

        count = converter.convert_frames_directory(str(frames_dir), str(output_file))

        progress.update(task, completed=True)

    if verbose:
        console.print(f"[green]✓[/green] Converted {count} frames with lexical units")
        console.print(f"  Output: {output_file}")

convert_propbank(input_dir: Path, output_dir: Path, verbose: bool = False) -> None

Convert PropBank XML framesets to JSON Lines.

PARAMETER	DESCRIPTION
input_dir	Directory containing PropBank XML files. TYPE: Path
output_dir	Directory to write JSON Lines files to. TYPE: Path
verbose	Show verbose output. TYPE: bool DEFAULT: False

Source code in src/glazing/cli/convert.py

def convert_propbank(input_dir: Path, output_dir: Path, verbose: bool = False) -> None:
    """Convert PropBank XML framesets to JSON Lines.

    Parameters
    ----------
    input_dir : Path
        Directory containing PropBank XML files.
    output_dir : Path
        Directory to write JSON Lines files to.
    verbose : bool
        Show verbose output.
    """
    converter = PropBankConverter()
    output_file = output_dir / "propbank.jsonl"

    with Progress(
        SpinnerColumn(),
        TextColumn("[progress.description]{task.description}"),
        BarColumn(),
        TextColumn("[progress.percentage]{task.percentage:>3.0f}%"),
        TimeElapsedColumn(),
        console=console,
    ) as progress:
        task = progress.add_task("Converting PropBank files...", total=None)

        count = converter.convert_framesets_directory(str(input_dir), str(output_file))

        progress.update(task, completed=True)

    if verbose:
        console.print(f"[green]✓[/green] Converted {count} framesets")
        console.print(f"  Output: {output_file}")

convert_verbnet(input_dir: Path, output_dir: Path, verbose: bool = False) -> None

Convert VerbNet XML files to JSON Lines.

PARAMETER	DESCRIPTION
input_dir	Directory containing VerbNet XML files. TYPE: Path
output_dir	Directory to write JSON Lines files to. TYPE: Path
verbose	Show verbose output. TYPE: bool DEFAULT: False

Source code in src/glazing/cli/convert.py

def convert_verbnet(input_dir: Path, output_dir: Path, verbose: bool = False) -> None:
    """Convert VerbNet XML files to JSON Lines.

    Parameters
    ----------
    input_dir : Path
        Directory containing VerbNet XML files.
    output_dir : Path
        Directory to write JSON Lines files to.
    verbose : bool
        Show verbose output.
    """
    converter = VerbNetConverter()
    output_file = output_dir / "verbnet.jsonl"

    with Progress(
        SpinnerColumn(),
        TextColumn("[progress.description]{task.description}"),
        BarColumn(),
        TextColumn("[progress.percentage]{task.percentage:>3.0f}%"),
        TimeElapsedColumn(),
        console=console,
    ) as progress:
        task = progress.add_task("Converting VerbNet files...", total=None)

        count = converter.convert_verbnet_directory(str(input_dir), str(output_file))

        progress.update(task, completed=True)

    if verbose:
        console.print(f"[green]✓[/green] Converted {count} verb classes")
        console.print(f"  Output: {output_file}")

convert_wordnet(input_dir: Path, output_dir: Path, verbose: bool = False) -> None

Convert WordNet database to JSON Lines.

PARAMETER	DESCRIPTION
input_dir	Directory containing WordNet database files. TYPE: Path
output_dir	Directory to write JSON Lines files to. TYPE: Path
verbose	Show verbose output. TYPE: bool DEFAULT: False

Source code in src/glazing/cli/convert.py

def convert_wordnet(input_dir: Path, output_dir: Path, verbose: bool = False) -> None:
    """Convert WordNet database to JSON Lines.

    Parameters
    ----------
    input_dir : Path
        Directory containing WordNet database files.
    output_dir : Path
        Directory to write JSON Lines files to.
    verbose : bool
        Show verbose output.
    """
    converter = WordNetConverter()

    with Progress(
        SpinnerColumn(),
        TextColumn("[progress.description]{task.description}"),
        BarColumn(),
        TextColumn("[progress.percentage]{task.percentage:>3.0f}%"),
        TimeElapsedColumn(),
        console=console,
    ) as progress:
        task = progress.add_task("Converting WordNet database...", total=None)

        output_file = output_dir / "wordnet.jsonl"
        stats = converter.convert_wordnet_database(str(input_dir), str(output_file))

        progress.update(task, completed=True)

    if verbose:
        console.print("[green]✓[/green] Converted WordNet database")
        for key, count in stats.items():
            console.print(f"  {key}: {count} entries")

dataset_info_cmd(dataset: str) -> None

Get information about a dataset's conversion process.

Source code in src/glazing/cli/convert.py

@convert.command(name="info")
@click.option(
    "--dataset",
    type=click.Choice(["verbnet", "propbank", "wordnet", "framenet"]),
    required=True,
    help="Dataset to get information about.",
)
def dataset_info_cmd(dataset: str) -> None:
    """Get information about a dataset's conversion process."""
    info = DATASET_INFO[dataset]

    console.print(f"\n[bold cyan]{info['name']} Conversion Information[/bold cyan]")
    console.print(f"[white]Description:[/white] {info['description']}")
    console.print(f"[white]Input Format:[/white] {info['input_format']}")
    console.print("[white]Output Files:[/white]")
    for output_file in info["output_files"]:
        console.print(f"  • {output_file}")

    converter_class = info.get("converter")
    if converter_class:
        console.print(f"\n[white]Converter Class:[/white] {converter_class.__name__}")

    # Add dataset-specific notes
    if dataset == "verbnet":
        console.print("\n[yellow]Notes:[/yellow]")
        console.print("• Converts VerbNet 3.4 XML files")
        console.print("• Preserves verb class hierarchy")
        console.print("• Includes thematic roles and selectional restrictions")
    elif dataset == "propbank":
        console.print("\n[yellow]Notes:[/yellow]")
        console.print("• Converts PropBank framesets")
        console.print("• Preserves argument structure and examples")
        console.print("• Includes cross-references to VerbNet")
    elif dataset == "wordnet":
        console.print("\n[yellow]Notes:[/yellow]")
        console.print("• Converts WordNet 3.1 database files")
        console.print("• Creates separate files for each POS")
        console.print("• Includes synsets, indices, and exceptions")
    elif dataset == "framenet":
        console.print("\n[yellow]Notes:[/yellow]")
        console.print("• Converts FrameNet 1.7 XML frames")
        console.print("• Preserves frame elements and relations")
        console.print("• Includes lexical units and examples")

list_datasets() -> None

List available datasets for conversion.

Source code in src/glazing/cli/convert.py

@convert.command(name="list")
def list_datasets() -> None:
    """List available datasets for conversion."""
    table = Table(title="Available Datasets for Conversion")
    table.add_column("Dataset", style="cyan", no_wrap=True)
    table.add_column("Description", style="white")
    table.add_column("Input Format", style="yellow")

    for key, info in DATASET_INFO.items():
        if key != "all":  # Skip 'all' in the listing
            table.add_row(info["name"], info["description"], info["input_format"])

    console.print(table)