import json

import datasets


logger = datasets.logging.get_logger(__name__)
_URL = "https://huggingface.co/datasets/sagnikrayc/snli-bt/resolve/main"
_URLS = {
    "train": f"{_URL}/train.jsonl",
    "validation": f"{_URL}/validation.jsonl",
    "test": f"{_URL}/test.jsonl",
}


class SnliBTConfig(datasets.BuilderConfig):
    def __init__(self, **kwargs):
        super(SnliBTConfig, self).__init__(**kwargs)


class SnliCF(datasets.GeneratorBasedBuilder):
    """SQUAD: The Stanford Question Answering Dataset. Version 1.1."""

    BUILDER_CONFIGS = [
        SnliBTConfig(
            name="plain_text",
            version=datasets.Version("1.0.0", ""),
            description="Plain text",
        ),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description="NA",
            features=datasets.Features(
                {
                    "idx": datasets.Value("string"),
                    "premise": datasets.Value("string"),
                    "hypothesis": datasets.Value("string"),
                    "label": datasets.Value("string"),
                    "_type": datasets.Value("string"),
                }
            ),
            # No default supervised_keys (as we have to pass both question
            # and context as input).
            supervised_keys=None
        )

    def _split_generators(self, dl_manager):
        downloaded_files = dl_manager.download_and_extract(_URLS)

        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["validation"]}
            ),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
        ]

    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 rf:
            for idx, line in enumerate(rf):
                if line:
                    _line = json.loads(line)
                    yield idx, {
                        "premise": _line["premise"],
                        "hypothesis": _line["hypothesis"],
                        "idx": _line["idx"],
                        "_type": _line["_type"],
                        "label": _line["label"]
                    }