# Lint as: python3
"""20ng question classification dataset."""


import csv

import datasets
from datasets.tasks import TextClassification
import sys
csv.field_size_limit(sys.maxsize)

_DESCRIPTION = """
"""

_CITATION = """jigsaw_toxicity_pred"""

_TRAIN_DOWNLOAD_URL = "https://huggingface.co/datasets/vmalperovich/toxic_comments/raw/main/train.csv"
_TEST_DOWNLOAD_URL = "https://huggingface.co/datasets/vmalperovich/toxic_comments/raw/main/test.csv"
_VALID_DOWNLOAD_URL = "https://huggingface.co/datasets/vmalperovich/toxic_comments/raw/main/validation.csv"


CATEGORY_MAPPING = ['neutral', 'toxic', 'severe_toxic', 'obscene', 'threat', 'insult', 'identity_hate']

class NG(datasets.GeneratorBasedBuilder):
    """toxic_comments  classification dataset."""

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": datasets.Value("string"),
                    "label": datasets.Sequence(datasets.ClassLabel(names=CATEGORY_MAPPING)),
                }
            ),
            homepage="",
            citation=_CITATION,
            # task_templates=[TextClassification(text_column="text", label_column="label")],
        )

    def _split_generators(self, dl_manager):
        train_path = dl_manager.download_and_extract(_TRAIN_DOWNLOAD_URL)
        test_path = dl_manager.download_and_extract(_TEST_DOWNLOAD_URL)
        valid_path = dl_manager.download_and_extract(_VALID_DOWNLOAD_URL)
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}),
            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": valid_path}),
        ]

    def _generate_examples(self, filepath):
        """Generate examples."""
        with open(filepath, encoding="utf-8") as csv_file:
            csv_reader = csv.reader(
                csv_file, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True
            )
            _ = next(csv_reader) # skip header
            for id_, row in enumerate(csv_reader):
                text, label = row
                label = [int(ind) for ind in label.strip(']').strip('[').split(",")]
                yield id_, {"text": text, "label": label}