import os
import datasets
from huggingface_hub import HfFileSystem
from typing import List

logger = datasets.logging.get_logger(name=__name__)
fs = HfFileSystem()

_CITATION = """
"""

_DESCRIPTION = """
    This dataset contain file about datetime date. 
    It's created with purpose is practice loading dataset from hugging face hub.
"""


_HOMEPAGE = """
"""

_REPO = "datasets/nguyenminh4099/date-data"
_BRANCH = "main"
_REPO_BRANCH = f"{_REPO}@{_BRANCH}"

_REPO_URL = f"https://huggingface.co/{_REPO_PATH}/resolve/{_BRANCH}"
_URL = os.path.join(_REPO_URL, "data", "{filename}.zip")

_CONFIGS = ['all']
_CONFIGS.extend(
    os.path.basename(file)[:-4]
    for file in fs.listdir(_REPO_BRANCH + "data", detail=False)
    if file.endswith('.zip')
)

class DateDataConfig(datasets.BuilderConfig):
    def __init__(
        self,
        name: str,
        **kwargs,        
    ):
        super(DateDataConfig, self).__init__(
            name=name,
            version=datasets.Version("1.0.0"),
            description=_DESCRIPTION,
        )

class DateDate(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [DateDataConfig(name=name) for name in _CONFIGS]
    DEFAULT_CONFIG_NAME = 'all'

    def info(self) -> datasets.DatasetInfo:
        features = datasets.Features({
            "id": datasets.Value('string'),
            "dow": datasets.Value('string'),
            "month": datasets.Value('string'),
            "dom": datasets.Value('string'),
            "hour": datasets.Value('int'),
            "min": datasets.Value('int'),
            "second": datasets.Value('int'),
            "timezone": datasets.Value('string'),
            "year": datasets.Value('int'),
            "file_path": datasets.Value('string'),
        })

        return datasets.DatasetInfo(
            features=features,
            description=_DESCRIPTION,
            citation=_CITATION,
            homepage=_HOMEPAGE,
        )

    def _split_generators(
        self,
        dl_manager: datasets.DownloadManager,
    ) -> List[datasets.SplitGenerator]:
        config_names = _CONFIGS[1:] if self.config.name == 'all' else [self.config.name]

        data_dirs = dl_manager.download_and_extract(
            [_URL.format(filename=zipfile) for zipfile in config_names]
        )

        return datasets.SplitGenerator(
            name=datasets.Split.TRAIN,
            gen_kwargs={
                "data_dirs": data_dirs,
            }
        )


    def _generate_examples(
        self,
        data_dirs: List[str],
    ) -> dict:
        for data_dir in data_dirs:
            print(data_dir)
            yield self._extract_datetime("Wed Oct 16 11:08:00 +07 2024").update((('id','123'),('file_path',"null")))
            

    def _read_txt(
        self,
        file_name: str,
    ) -> str:
        with open(file=file_name, mode='r') as f:
            return self._extract_datetime(f.read())

    
    def _extract_datetime(
        self,
        datetime_string: str,
    ) -> dict:
        datetime_string = datetime_string.strip("./ ")
        components = datetime_string.split(' ')

        return {
            "dow": components[0],
            "month": components[1],
            "dom": components[2],
            "hour": components[3],
            "min": components[4],
            "second": components[5],
            "timezone": components[6],
            "year": components[7],
        }