import datasets
import json

_CITATION = """\
@misc{li2023estimating,
      title={Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation}, 
      author={Yucheng Li},
      year={2023},
      eprint={2309.10677},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
"""

_DESCRIPTION = """\
This dataset contains Wikipedia articles of 419 selected pages from 2017 to 2022. The articles are arraged by month. Access the specific month by using the format "YYYY-MM" as config. Such as load_dataset("RealTimeData/wikitext_alltime", "2021-1").
"""

_HOMEPAGE = "https://github.com/liyucheng09/Contamination_Detector"

_TIMES = ["2017-10", "2017-11", "2017-12", "2017-1", "2017-2", "2017-3", "2017-4", "2017-5", "2017-6", "2017-7", "2017-8", "2017-9", "2018-10", "2018-11", "2018-12", "2018-1", "2018-2", "2018-3", "2018-4", "2018-5", "2018-6", "2018-7", "2018-8", "2018-9", "2019-10", "2019-11", "2019-12", "2019-1", "2019-2", "2019-3", "2019-4", "2019-5", "2019-6", "2019-7", "2019-8", "2019-9", "2020-10", "2020-11", "2020-12", "2020-1", "2020-2", "2020-3", "2020-4", "2020-5", "2020-6", "2020-7", "2020-8", "2020-9", "2021-10", "2021-11", "2021-12", "2021-1", "2021-2", "2021-3", "2021-4", "2021-5", "2021-6", "2021-7", "2021-8", "2021-9", "2022-10", "2022-11", "2022-12", "2022-1", "2022-2", "2022-3", "2022-4", "2022-5", "2022-6", "2022-7", "2022-8", "2022-9", "all"]


class Wikitext_alltimes(datasets.GeneratorBasedBuilder):

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name=time, version=datasets.Version("1.0.0"), description=f"419 selected wikipedia articles edited in the priod of {time}"
        )
        for time in _TIMES
    ]

    def _info(self):
        features = datasets.Features(
            {
                "title": datasets.Value("string"),
                "pageid": datasets.Value("int64"),
                "text": datasets.Value("string"),
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        if self.config.name == "all":
            times = _TIMES[:-1]
            files = dl_manager.download_and_extract('all_articles.zip')
            return [
                datasets.SplitGenerator(
                    name=datasets.Split.TRAIN,
                    gen_kwargs={"files": files},
                )
            ]
        else:
            time = self.config.name
            _URL = f"articles/{time}.json"
            file = dl_manager.download(_URL)
            return [
                datasets.SplitGenerator(
                    name=datasets.Split.TRAIN,
                    gen_kwargs={"files": file},
                )
            ]

    def _generate_examples(self, files):
        """Yields examples."""
        if self.config.name == "all":
            assert isinstance(files, list)
            for file in files:
                time = file.strip('.json')
                with open(file, encoding="utf-8") as f:
                    data = json.load(f)
                for title, article in data.items():
                    yield f'{time}-{title}', {
                        "title": article['title'],
                        "pageid": article['pageid'],
                        "text": article['text'],
                    }
        else:
            assert isinstance(files, str)
            time = self.config.name
            with open(files, encoding="utf-8") as f:
                data = json.load(f)
            for title, article in data.items():
                yield f'{time}-{title}', {
                    "title": article['title'],
                    "pageid": article['pageid'],
                    "text": article['text'],
                }