import json
import csv
import datasets
_CITATION = """\\
@article{amirkhani2020farstail,
  title={FarsTail: A Persian Natural Language Inference Dataset},
  author={Hossein Amirkhani, Mohammad Azari Jafari, Azadeh Amirak, Zohreh Pourjafari, Soroush Faridan Jahromi, and Zeinab Kouhkan},
  journal={arXiv preprint arXiv:2009.08820},
  year={2020}
}
"""
_DESCRIPTION = """\\\\\\\\
A Persian Natural Language Inference Dataset
"""

_URL = "https://raw.githubusercontent.com/dml-qom/FarsTail/master/data/"
_URLS = {
    "train": _URL + "Train-word.csv",
    "test": _URL + "Test-word.csv",
    "validation": _URL + "Val-word.csv"
}
class FarsTailConfig(datasets.BuilderConfig):
    """BuilderConfig for FarsTail."""
    def __init__(self, **kwargs):
        """BuilderConfig for FarsTail.
        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(FarsTailConfig, self).__init__(**kwargs)
        
class FarsTail(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        FarsTailConfig(name="FarsTail", version=datasets.Version("1.0.0"), description="persian NLI dataset"),
    ]
    def _info(self):
        return datasets.DatasetInfo(
            # This is the description that will appear on the datasets page.
            description=_DESCRIPTION,
            # datasets.features.FeatureConnectors
            features=datasets.Features(
                {
                    "premise": datasets.Value("string"),
                    "hypothesis": datasets.Value("string"),
                    "label": datasets.Value("string")
                }
            ),
            supervised_keys=None,
            # Homepage of the dataset for documentation
            homepage="https://github.com/dml-qom/FarsTail",
            citation=_CITATION,
        )
        
    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        # dl_manager is a datasets.download.DownloadManager that can be used to
        # download and extract URLs
        urls_to_download = _URLS
        downloaded_files = dl_manager.download_and_extract(urls_to_download)
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["validation"]}),
        ]

    def _generate_examples(self, filepath):
        try:
            with open(filepath, encoding="utf-8") as f:
                reader = csv.DictReader(f, delimiter="\t")
                for idx, row in enumerate(reader):
                    yield idx, {
                        "premise": row["premise"],
                        "hypothesis": row["hypothesis"],
                        "label": row["label"],
                    }
        except Exception as e:
            print(e)