""" TweetTopic Dataset """
import json
from itertools import chain
import datasets

logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """[TweetTopic](TBA)"""

_VERSION = "1.0.1"
_CITATION = """
TBA
"""
_HOME_PAGE = "https://cardiffnlp.github.io"
_LABEL_TYPE = "multi"
_NAME = f"tweet_topic_{_LABEL_TYPE}"
_URL = f'https://huggingface.co/datasets/cardiffnlp/{_NAME}/raw/main/dataset'
_URLS = {
    str(datasets.Split.TEST): [f'{_URL}/split_temporal/test_2021.{_LABEL_TYPE}.json'],
    str(datasets.Split.TRAIN): [f'{_URL}/split_temporal/train_2021.{_LABEL_TYPE}.json'],
    str(datasets.Split.VALIDATION): [f'{_URL}/split_temporal/validation_2021.{_LABEL_TYPE}.json'],
    f"temporal_2020_{str(datasets.Split.TEST)}": [f'{_URL}/split_temporal/test_2020.{_LABEL_TYPE}.json'],
    f"temporal_2021_{str(datasets.Split.TEST)}": [f'{_URL}/split_temporal/test_2021.{_LABEL_TYPE}.json'],
    f"temporal_2020_{str(datasets.Split.TRAIN)}": [f'{_URL}/split_temporal/train_2020.{_LABEL_TYPE}.json'],
    f"temporal_2021_{str(datasets.Split.TRAIN)}": [f'{_URL}/split_temporal/train_2021.{_LABEL_TYPE}.json'],
    f"temporal_2020_{str(datasets.Split.VALIDATION)}": [f'{_URL}/split_temporal/validation_2020.{_LABEL_TYPE}.json'],
    f"temporal_2021_{str(datasets.Split.VALIDATION)}": [f'{_URL}/split_temporal/validation_2021.{_LABEL_TYPE}.json'],
    f"random_{str(datasets.Split.TRAIN)}": [f'{_URL}/split_random/train_random.{_LABEL_TYPE}.json'],
    f"random_{str(datasets.Split.VALIDATION)}": [f'{_URL}/split_random/validation_random.{_LABEL_TYPE}.json'],
    f"coling2022_random_{str(datasets.Split.TEST)}": [f'{_URL}/split_coling2022_random/test_random.{_LABEL_TYPE}.json'],
    f"coling2022_random_{str(datasets.Split.TRAIN)}": [f'{_URL}/split_coling2022_random/train_random.{_LABEL_TYPE}.json'],
    f"coling2022_temporal_{str(datasets.Split.TEST)}": [f'{_URL}/split_coling2022_temporal/test_2021.{_LABEL_TYPE}.json'],
    f"coling2022_temporal_{str(datasets.Split.TRAIN)}": [f'{_URL}/split_coling2022_temporal/train_2020.{_LABEL_TYPE}.json'],
}


class TweetTopicSingleConfig(datasets.BuilderConfig):
    """BuilderConfig"""

    def __init__(self, **kwargs):
        """BuilderConfig.

        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(TweetTopicSingleConfig, self).__init__(**kwargs)


class TweetTopicSingle(datasets.GeneratorBasedBuilder):
    """Dataset."""

    BUILDER_CONFIGS = [
        TweetTopicSingleConfig(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION),
    ]

    def _split_generators(self, dl_manager):
        downloaded_file = dl_manager.download_and_extract(_URLS)
        return [datasets.SplitGenerator(name=i, gen_kwargs={"filepaths": downloaded_file[i]}) for i in _URLS.keys()]

    def _generate_examples(self, filepaths):
        _key = 0
        for filepath in filepaths:
            logger.info(f"generating examples from = {filepath}")
            with open(filepath, encoding="utf-8") as f:
                _list = [i for i in f.read().split('\n') if len(i) > 0]
                for i in _list:
                    data = json.loads(i)
                    yield _key, data
                    _key += 1

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": datasets.Value("string"),
                    "date": datasets.Value("string"),
                    "label": datasets.Value("int32"),
                    "label_name": datasets.Value("string"),
                    "id": datasets.Value("string")
                }
            ),
            supervised_keys=None,
            homepage=_HOME_PAGE,
            citation=_CITATION,
        )