import os
import datasets
from huggingface_hub import HfApi
from datasets import DownloadManager, DatasetInfo
from datasets.data_files import DataFilesDict

_EXTENSION = [".png", ".jpg", ".jpeg", ".webp", ".bmp"]
_NAME = "nyanko7/danbooru2023"
_REVISION = "main"


class DanbooruDataset(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        # add number before name for sorting
        datasets.BuilderConfig(name="full"),
    ]

    def _info(self) -> DatasetInfo:
        features = {
            "image": datasets.Image(),
            "post_id": datasets.Value("int64")
        }
        info = datasets.DatasetInfo(
            features=datasets.Features(features),
            supervised_keys=None,
            citation="",
        )
        return info

    def _split_generators(self, dl_manager: DownloadManager):
        hfh_dataset_info = HfApi().dataset_info(_NAME, revision=_REVISION, timeout=100.0)
        data_files = DataFilesDict.from_hf_repo(
            {datasets.Split.TRAIN: ["**"]},
            dataset_info=hfh_dataset_info,
            allowed_extensions=["tar", ".tar"],
        )
        gs = []
        for split, files in data_files.items():
            downloaded_files = dl_manager.download_and_extract(files)
            gs.append(datasets.SplitGenerator(name=split, gen_kwargs={"filepath": downloaded_files}))
        return gs

    def _generate_examples(self, filepath):
        for path in filepath:
            all_fnames = {os.path.relpath(os.path.join(root, fname), start=path) for root, _dirs, files in os.walk(path) for fname in files}
            image_fnames = sorted([fname for fname in all_fnames if os.path.splitext(fname)[1].lower() in _EXTENSION], reverse=True)
            for image_fname in image_fnames:
                image_path = os.path.join(path, image_fname)
                post_id = int(os.path.splitext(os.path.basename(image_fname))[0])
                yield image_fname, {"post_id": post_id}