import json
import datasets


logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """[SemEVAL 2012 task 2: Relational Similarity](https://aclanthology.org/S12-1047/)"""
_NAME = "semeval2012_relational_similarity_v5"
_VERSION = "1.1.0"
_CITATION = """
@inproceedings{jurgens-etal-2012-semeval,
    title = "{S}em{E}val-2012 Task 2: Measuring Degrees of Relational Similarity",
    author = "Jurgens, David  and
      Mohammad, Saif  and
      Turney, Peter  and
      Holyoak, Keith",
    booktitle = "*{SEM} 2012: The First Joint Conference on Lexical and Computational Semantics {--} Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation ({S}em{E}val 2012)",
    month = "7-8 " # jun,
    year = "2012",
    address = "Montr{\'e}al, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/S12-1047",
    pages = "356--364",
}
"""

_HOME_PAGE = "https://github.com/asahi417/relbert"
_URL = f'https://huggingface.co/datasets/relbert/{_NAME}/raw/main/dataset'
_URLS = {
    str(datasets.Split.TRAIN): ["https://huggingface.co/datasets/relbert/semeval2012_relational_similarity_v5/resolve/main/dataset/train.jsonl"],
    str(datasets.Split.VALIDATION): [f'{_URL}/valid.jsonl'],
}


class SemEVAL2012RelationalSimilarityV5Config(datasets.BuilderConfig):
    """BuilderConfig"""

    def __init__(self, **kwargs):
        """BuilderConfig.
        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(SemEVAL2012RelationalSimilarityV5Config, self).__init__(**kwargs)


class SemEVAL2012RelationalSimilarityV5(datasets.GeneratorBasedBuilder):
    """Dataset."""

    BUILDER_CONFIGS = [
        SemEVAL2012RelationalSimilarityV5Config(
            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[str(i)]})
                for i in [datasets.Split.TRAIN, datasets.Split.VALIDATION]]

    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(
                {
                    "level": datasets.Value("string"),
                    "relation_type": datasets.Value("string"),
                    "positives": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
                    "negatives": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
                }
            ),
            supervised_keys=None,
            homepage=_HOME_PAGE,
            citation=_CITATION,
        )