import datasets

_CITATION = """\
@InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2021}
}
"""

_DESCRIPTION = """\
This is a dataset put together to pretrain a language model in Dhivehi, the language of Maldives.
"""
_HOMEPAGE = "https://huggingface.co/datasets/ashraq/dhivehi-corpus"

_LICENSE = ""

TRAIN_URL = "train.txt"


class DhivehiCorpus(datasets.GeneratorBasedBuilder):
    VERSION = datasets.Version("1.1.0")

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": datasets.Value("string"),
                },
            ),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        train_path = dl_manager.download_and_extract(TRAIN_URL)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": train_path,
                    "split": "train",
                },
            ),
        ]

    def _generate_examples(self, filepath, split):
        with open(filepath, encoding="utf8") as f:
            id_ = 0
            for line in f:
                yield id_, {"text": line.strip()}
                id_ += 1