# Loading script for the ReviewsFinder dataset.


import json
import csv

import datasets


logger = datasets.logging.get_logger(__name__)


_CITATION = """ """


_DESCRIPTION = """   """


_HOMEPAGE = """  """



_URL = "https://huggingface.co/datasets/projecte-aina/CaSET-catalan-stance-emotions-twitter/resolve/main/"
_FILE = "data.jsonl"


class CaSETConfig(datasets.BuilderConfig):
    """ Builder config for the CaSET dataset """

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


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


    BUILDER_CONFIGS = [
        CaSETConfig(
            name="CaSET",
            version=datasets.Version("1.0.0"),
            description="CaSET dataset",
        ),
    ]


    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {"id_original": datasets.Value("string"),
                 "id_answer": datasets.Value("string"),
                    "original_text": datasets.Value("string"),
                    "answer_text": datasets.Value("string"),
                    "topic": datasets.features.ClassLabel
                    (names=
                        ['aeroport',
                         'vaccines',
                         'lloguer',
                         'benidormfest',
                         'subrogada'
                        ]
                    ),
                 "dynamic_stance": datasets.features.ClassLabel
                 (names=
                  ['Agree', 'Disagree', 'Elaborate', 'Query', 'Neutral', 'Unrelated', 'NA'
                   ]
                  ),
                 "original_stance": datasets.features.ClassLabel
                 (names=
                  ['FAVOUR', 'AGAINST', 'NEUTRAL', 'NA'
                   ]
                  ),
                 "answer_stance": datasets.features.ClassLabel
                 (names=
                  ['FAVOUR', 'AGAINST', 'NEUTRAL', 'NA'
                   ]
                  ),
                 "original_emotion": datasets.Value("list"),
                 "answer_emotion": datasets.Value("list"),
                }
            ),
            homepage=_HOMEPAGE,
            citation=_CITATION,
        )

    def _generate_examples(self, filepath):
        """This function returns the examples in the raw (text) form."""
        logger.info("generating examples from = %s", filepath)
        with open(filepath, encoding="utf-8") as f:
            data = [json.loads(line) for line in f]
            for id_, pair in enumerate(data):
                    yield id_, {
                        "id_original": pair["id_original"],
                        "id_answer": pair["id_answer"],
                        "original_text":pair["original_text"],
                        "answer_text": pair["answer_text"],
                        "topic": pair["topic"],
                        "dynamic_stance": pair["dynamic_stance"],
                        "original_stance": pair["original_stance"],
                        "answer_stance": pair["answer_stance"],
                        "original_emotion": pair["original_emotion"],
                        "answer_emotion": pair["answer_emotion"],
                    }