import json
import datasets

logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """[ConceptNet5](https://ojs.aaai.org/index.php/AAAI/article/view/11164)"""
_NAME = "conceptnet"
_VERSION = "1.0.0"
_CITATION = """
@inproceedings{speer2017conceptnet,
  title={Conceptnet 5.5: An open multilingual graph of general knowledge},
  author={Speer, Robyn and Chin, Joshua and Havasi, Catherine},
  booktitle={Thirty-first AAAI conference on artificial intelligence},
  year={2017}
}
"""

_HOME_PAGE = "https://github.com/asahi417/relbert"
_URL = f'https://huggingface.co/datasets/relbert/{_NAME}/raw/main/dataset'
_URLS = {
    # str(datasets.Split.TRAIN): [f'{_URL}/train.jsonl'],
    # str(datasets.Split.VALIDATION): [f'{_URL}/valid.jsonl'],
    str(datasets.Split.TRAIN): [f'{_URL}/train{i:02d}.jsonl' for i in range(33)],
    str(datasets.Split.VALIDATION): [f'{_URL}/valid{i:02d}.jsonl' for i in range(25)],
}


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

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


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

    BUILDER_CONFIGS = [
        ConceptNetHighConfidenceConfig(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(
                {
                    "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,
        )