# coding=utf-8
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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#
#     http://www.apache.org/licenses/LICENSE-2.0
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# Lint as: python3
"""Turkish News Category Dataset (270K - Lite Version) - Interpress Media Monitoring Company"""


import csv
import os

import datasets


logger = datasets.logging.get_logger(__name__)


_DESCRIPTION = """\
It is a Turkish news data set consisting of 273601 news in 10 categories, compiled from print media and news websites between 2010 and 2017 by the Interpress (https://www.interpress.com/) media monitoring company. It has been rearranged as easily separable and with fewer classes.
"""

_CITATION = ""
_LICENSE = "unknown"
_HOMEPAGE = "https://www.interpress.com/"
_DOWNLOAD_URL = "https://www.interpress.com/downloads/interpress_news_category_tr_270k_lite.zip"
_DATASET_URLS = {
    "train": "interpress_news_category_tr_270k_lite_train.tsv",
    "test": "interpress_news_category_tr_270k_lite_test.tsv",
}


class InterpressNewsCategoryTRLiteConfig(datasets.BuilderConfig):
    """BuilderConfig for InterpressNewsCategoryTRLite."""

    def __init__(self, **kwargs):
        """BuilderConfig for InterpressNewsCategoryTRLite.

        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(InterpressNewsCategoryTRLiteConfig, self).__init__(**kwargs)


class InterpressNewsCategoryTRLite(datasets.GeneratorBasedBuilder):
    """Turkish News Category Dataset (270K - Lite Version) - Interpress Media Monitoring Company"""

    BUILDER_CONFIGS = [
        InterpressNewsCategoryTRLiteConfig(
            name="270k_10class",
            version=datasets.Version("1.0.0"),
            description="Turkish News Category Dataset (270K - Lite Version) - Interpress Media Monitoring Company",
        ),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "content": datasets.Value("string"),
                    "category": datasets.features.ClassLabel(
                        names=[
                            "kültürsanat",
                            "ekonomi",
                            "siyaset",
                            "eğitim",
                            "dünya",
                            "spor",
                            "teknoloji",
                            "magazin",
                            "sağlık",
                            "gündem",
                        ]
                    ),
                }
            ),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        dl_dir = dl_manager.download_and_extract(_DOWNLOAD_URL)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(dl_dir, _DATASET_URLS["train"])}
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(dl_dir, _DATASET_URLS["test"])}
            ),
        ]

    def _generate_examples(self, filepath):
        """Generate InterpressNewsCategoryTRLite examples."""
        logger.info("⏳ Generating examples from = %s", filepath)
        with open(filepath, encoding="utf-8") as f:
            reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
            for idx, row in enumerate(reader):
                yield idx, {
                    "content": row["news"],
                    "category": int(row["label"]),
                }