"""
Copyright 2025-present Rhythm World Team

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""

from os import listdir
from pathlib import Path
import datasets
import shutil
import typer


DISALLOWED_METADATA = set(
    [
        "ChartConverter",
        "ChartConvertTool",
        "ChartConvertToolVersion",
        "smsg",
    ]
)


def parse_chart(chart: str) -> tuple[str, dict[str, str]]:
    """Extract metadata from chart string, ignoring disallowed keys.

    Returns (filtered_chart, metadata_dict)."""
    chart_lines = []
    meta: dict[str, str] = {}
    prev_blank = False
    for line in chart.split("\n"):
        if line.startswith("&"):
            key, value = line[1:].split("=", 1)
            if key in DISALLOWED_METADATA:
                continue
            else:
                meta[key] = value
        else:
            # Filter out consecutive newlines & blank lines
            if not line.strip():
                if not prev_blank:
                    chart_lines.append("")
                prev_blank = True
            else:
                chart_lines.append(line)
                prev_blank = False
    return ("\n".join(chart_lines), meta)


def count_subdirs(source_path: Path):
    result: dict[str, int] = {}
    for entry in listdir(source_path):
        first_level = source_path / entry
        if not first_level.is_dir():
            continue
        count = 0
        for sub in listdir(first_level):
            if (first_level / sub).is_dir():
                count += 1
        result[entry] = count
    return result


def collect_all_rows(source_path: Path):
    for entry in listdir(source_path):
        first_level = source_path / entry
        if not first_level.is_dir():
            continue
        for subentry in listdir(first_level):
            p = first_level / subentry
            with open(p / "maidata.txt", encoding="utf-8") as f:
                chart = f.read()
            chart, meta = parse_chart(chart)
            yield {
                "id": int(subentry.split("_")[0]),
                "name": meta.get("title", "").replace("[DX]", "").replace("[SD]", ""),
                "type": "DX" if subentry.endswith("_DX") else "STD",
                "music": str(p / "track.mp3"),
                "chart": chart,
            }


def main(
    source_path: Path = typer.Argument(
        ..., help="Source directory, see README.md for details"
    ),
    output_path: Path = typer.Argument(..., help="Output directory for dataset"),
    clear: bool = typer.Option(
        False, "--clear", help="Clear output directory if not empty"
    ),
):
    if output_path.exists() and any(output_path.iterdir()):
        if not clear:
            typer.echo("Error: Output directory is not empty.")
            raise typer.Exit(code=1)
        else:
            for item in output_path.iterdir():
                if item.is_dir():
                    shutil.rmtree(item)
                else:
                    item.unlink()
    output_path.mkdir(parents=True, exist_ok=True)

    features = datasets.Features(
        {
            "id": datasets.Value("int32"),
            "name": datasets.Value("string"),
            "type": datasets.ClassLabel(names=["STD", "DX"]),
            "music": datasets.Audio(),
            "chart": datasets.Value("string"),
        }
    )

    rows = [i for i in collect_all_rows(source_path)]
    dataset = datasets.Dataset.from_list(
        rows,
        features=features,
        info=datasets.DatasetInfo(
            description="Dataset of Maimai charts & music, in 3simai format.",
            homepage="https://huggingface.co/datasets/rhythm-world/maimai-charts-dataset",
            version="1.0.0",
            license="odc-by",
        ),
    )
    dataset.save_to_disk(output_path)


app = typer.Typer()
app.command()(main)

if __name__ == "__main__":
    app()