# Config file by Simon Hengchen, https://hengchen.net

import os
import datasets

logger = datasets.logging.get_logger(__name__)

_CITATION = """
@misc{botenanna,
    title = {"Jag känner en bot, hon heter [MASK]. A BERT for older Swedish, and a more usable dataset for historical newspapers"},
    author = {Simon Hengchen} 
    year={2023},
}
 """

_DESCRIPTION = """
This is a version of the Kubhist 2 dataset created, curated and made available by Språkbanken Text (SBX) at the University of Gothenburg (Sweden) under the CC BY 4.0 license. 
This is a a corpus of OCRed newspapers from Sweden spanning the 1640s to the 1900s.
The original data is available with many types of annotation in XML at https://spraakbanken.gu.se/en/resources/kubhist2. 
A good description of the data is available in this blog entry by Dana Dannélls: https://spraakbanken.gu.se/blogg/index.php/2019/09/15/the-kubhist-corpus-of-swedish-newspapers/

In a nutshell, this hugginface dataset version offers:
- only the OCRed text
- available in decadal subsets

License is CC BY 4.0 with attribution.
"""

_URL = "https://github.com/ChangeIsKey/kubhist2"

_URLS = {'1640': './text/1640/1640.txt.gz',
        '1650': './text/1650/1650.txt.gz',
        '1660': './text/1660/1660.txt.gz',
        '1670': './text/1670/1670.txt.gz',
        '1680': './text/1680/1680.txt.gz',
        '1690': './text/1690/1690.txt.gz',
        '1700': './text/1700/1700.txt.gz',
        '1710': './text/1710/1710.txt.gz',
        '1720': './text/1720/1720.txt.gz',
        '1730': './text/1730/1730.txt.gz',
        '1740': './text/1740/1740.txt.gz',
        '1750': './text/1750/1750.txt.gz',
        '1760': './text/1760/1760.txt.gz',
        '1770': './text/1770/1770.txt.gz',
        '1780': './text/1780/1780.txt.gz',
        '1790': './text/1790/1790.txt.gz',
        '1800': './text/1800/1800.txt.gz',
        '1810': './text/1810/1810.txt.gz',
        '1820': './text/1820/1820.txt.gz',
        '1830': './text/1830/1830.txt.gz',
        '1840': './text/1840/1840.txt.gz',
        '1850': './text/1850/1850.txt.gz',
        '1860': './text/1860/1860.txt.gz',
        '1870': './text/1870/1870.txt.gz',
        '1880': './text/1880/1880.txt.gz',
        '1890': './text/1890/1890.txt.gz',
        '1900': './text/1900/1900.txt.gz',
        'all': './text/all/all.txt.gz',
        }


class kubhist2Config(datasets.BuilderConfig):
    """BuilderConfig for kubhist2."""

    def __init__(self, period="all", **kwargs):
        """Constructs a kubhist2Dataset.
        Args:
        period: can be any key in _URLS, `all` takes all
        **kwargs: keyword arguments forwarded to super.
        """
        if str(period) not in _URLS.keys():
            #logger.warning("No period specified or wrong period, getting everything instead.")
            self.period = "all"
        else:
            self.period = str(period)
        super(kubhist2Config, self).__init__(**kwargs)


class kubhist2(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIG_CLASS = kubhist2Config

    BUILDER_CONFIGS = []
    for key in _URLS:
        BUILDER_CONFIGS.append(
            kubhist2Config(
            name=key,
            version=datasets.Version("1.0.3", ""),
            description=f"Kubhist2: {key}",
            period=key,
            )
        )
    
    DEFAULT_CONFIG_NAME = "all"

    def _info(self):
        f = datasets.Features(
            {
            "text": datasets.Value("string")
            }
        )

        return datasets.DatasetInfo(
            features=f,
            supervised_keys=None,
            homepage="https://github.com/ChangeIsKey",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        url = {"train" : _URLS[self.config.period]}
        downloaded_files = dl_manager.download_and_extract(url)
        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]})]
        

    def _generate_examples(self, filepath):
        """Yields examples."""
        with open(filepath) as f:
            for i, line in enumerate(f):
                yield i, {"text" : line.rstrip()}