# coding=utf-8
# Copyright 2023 Devrim Cavusoglu and the HuggingFace Datasets Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# Lint as: python3
"""Goodwiki Long Subset."""


import json

import datasets

logger = datasets.logging.get_logger(__name__)


_DESCRIPTION = """\
Dataset consisting of long wikipedia articles in markdown format.
"""

_URLS = {
    "train": [
        "train/partition_0.jsonl",
    ],
    "test": [
        "test/partition_1.jsonl",
    ]
}


class GoodWikiLongDatasetConfig(datasets.BuilderConfig):
    """BuilderConfig for Dataset."""

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

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

    @property
    def features(self):
        return {
            "id": datasets.Value("string"),
            "url": datasets.Value("null"),
            "title": datasets.Value("string"),
            "text": datasets.Value("string"),
            "revid": datasets.Value("string"),
            "description": datasets.Value("string"),
            "categories": datasets.Sequence(datasets.Value("string")),
        }


class GoodWikiLongDataset(datasets.GeneratorBasedBuilder):
    """WikiLongDataset Classification dataset. Version 1.0."""

    BUILDER_CONFIGS = [
        GoodWikiLongDatasetConfig(
            version=datasets.Version("1.0.0", ""), description="Goodwiki Long Articles"
        )
    ]
    BUILDER_CONFIG_CLASS = GoodWikiLongDatasetConfig

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(self.config.features),
        )

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

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir["train"]}
            ),
        ]

    def _generate_examples(self, filepath):
        """This function returns the examples in the raw (text) form."""
        logger.info("generating examples from = %s", filepath)
        if isinstance(filepath, str):
            filepath = [filepath]
        key = 0
        for path in filepath:
            with open(path, encoding="utf-8") as data:
                for article_data in data:
                    article = json.loads(article_data)
                    article["id"] = article.pop("pageid")
                    article["text"] = "# " + article["title"] + "\n\n" + article.pop("markdown")
                    article["url"] = None
                    yield key, article
                    key += 1