import datasets
import zipfile
import urllib.request
import os


logger = datasets.logging.get_logger(__name__)


_DESCRIPTION = """\
A colossal, cleaned version of Common Crawl's web crawl corpus.
Based on Common Crawl dataset: "https://commoncrawl.org".
This is the processed version of Google's mC4 dataset by AllenAI.
"""

_CITATION = """
@article{2019t5,
    author = {Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu},
    title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer},
    journal = {arXiv e-prints},
    year = {2019},
    archivePrefix = {arXiv},
    eprint = {1910.10683},
}
"""

_URL = "https://linghub.ru/static/Taiga/news.zip"

_DATA_URL = "https://linghub.ru/static/Taiga/news.zip"


class TaigaConfig(datasets.BuilderConfig):
    """BuilderConfig for mC4."""

    def __init__(self, *args, **kwargs):
        """BuilderConfig for mC4.
        Args:
            languages (:obj:`List[str]`): list of languages to load
            **kwargs: keyword arguments forwarded to super.
        """
        super().__init__(
            *args,
            name="taiga",
            **kwargs,
        )


class Taiga(datasets.GeneratorBasedBuilder):
    """mC4, a colossal, cleaned version of Common Crawl's web crawl corpus."""

    BUILDER_CONFIGS = [TaigaConfig()]
    BUILDER_CONFIG_CLASS = TaigaConfig

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": datasets.Value("string"),
                }
            ),
        )

    def _split_generators(self, dl_manager):
        downloaded_file = dl_manager.download(['proza_ru2.zip', 'stihi_ru.zip', 'proza_ru1.zip'])
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_file}),
        ]

    def _generate_examples(self, filepaths):
        """This function returns the examples in the raw (text) form by iterating on all the files."""
        id_ = 0
        for filepath in filepaths:
            logger.info("generating examples from = %s", filepath)
            with zipfile.ZipFile(filepath) as z:
                for filename in z.namelist():
                    if not os.path.isdir(filename) and '.txt' in filename.split('/') and len(filename.split('/')) > 2:
                        # read the file
                        with z.open(filename) as f:
                            txt = f.read().decode('utf-8')
                            yield id_, {'text': txt}
                            id_ += 1