import csv
import datasets

_CITATION = """
@InProceedings{--,
  author = {---},
  title = {---},
  booktitle = {---},
  year = 2021,
  address = "---"
}
"""

_DESCRIPTION = """\
The Norwegian Parliament Speeches is a collection of text passages from
1998 to 2016 and pronounced at the Norwegian Parliament (Storting) by members
of the two major parties: Fremskrittspartiet and Sosialistisk Venstreparti.
"""

_HOMEPAGE = "https://github.com/NBAiLab/notram/"

_BASE_URL = "https://huggingface.co/datasets/NbAiLab/norwegian_parliament/raw/main/data/"
_URLS = {
    "train": f"{_BASE_URL}train.tsv",
    "dev": f"{_BASE_URL}dev.tsv",
    "test": f"{_BASE_URL}test.tsv",
}

class NorwegianParliament(datasets.GeneratorBasedBuilder):
    """Norwegian Parliament Speeches (1998, 2016)"""

    VERSION = datasets.Version("1.0.0")

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": datasets.Value("string"),
                    "label": datasets.ClassLabel(names=["Fremskrittspartiet", "Sosialistisk Venstreparti"]),
                }
            ),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        downloaded_files = dl_manager.download(_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["dev"]}),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
        ]

    def _generate_examples(self, filepath):
        with open(filepath, encoding="utf-8") as file:
            reader = csv.reader(file, delimiter="\t")
            #next(reader)  # Skip the header
            for idx, row in enumerate(reader):
                label, text = row
                yield idx, {
                    "text": text,
                    "label": label,
                }