import datasets
import json
import numpy
import tarfile
import io
from io import BytesIO

CHUNK_COUNT = 330

_FEATURES = datasets.Features(
    {
        "mbid": datasets.Value("string"),
        "title": datasets.Value("string"),
        "artists": datasets.Value("string"),
        "isrc": datasets.Value("string"),
        "length": datasets.Value("string"),
        "date": datasets.Value("string"),
        "ytid": datasets.Value("string"),
    }
)

class MusicBrainzLoaderStream(datasets.GeneratorBasedBuilder):
    """MusicBrainz Dataset"""

    def _info(self):
        return datasets.DatasetInfo(
            description="MusicBrainz Dataset",
            features=_FEATURES,
            homepage="None",
            citation="None",
            license="None"
        )

    def _split_generators(self, dl_manager):
        # Load the chunk list.
        _CHUNK_LIST = [x for x in range(CHUNK_COUNT)]

        # Create a list to hold the downloaded chunks.
        _list = []

        # Download each chunk file.
        for chunk in _CHUNK_LIST:
           _list.append(dl_manager.download(f"data/{chunk+1}.jsonl"))

        # Return the list of downloaded chunks.
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "chunks": _list,
                },
            ),
        ]
    
    def _generate_examples(self, chunks):
        """Generate images and labels for splits."""
        for chunk in chunks:
            with open(chunk, mode='r') as infile:
                for line in infile:
                    mbid, title, artists, isrc, length, date, ytid = json.loads(line)
                    yield mbid, {
                        "mbid": mbid,
                        "title": title,
                        "artists": json.dumps(artists),
                        "isrc": json.dumps(isrc),
                        "length": length,
                        "date": date,
                        "ytid": ytid
                    }