"""BOUN dataset"""

import datasets

_CITATION = """
@article{celebi2018segmenting,
  title={Segmenting hashtags and analyzing their grammatical structure},
  author={Celebi, Arda and {\"O}zg{\"u}r, Arzucan},
  journal={Journal of the Association for Information Science and Technology},
  volume={69},
  number={5},
  pages={675--686},
  year={2018},
  publisher={Wiley Online Library}
}
"""

_DESCRIPTION = """
Dev-BOUN Development set that includes 500 manually segmented hashtags. These are selected from tweets about movies, 
tv shows, popular people, sports teams etc. Test-BOUN Test set that includes 500 manually segmented hashtags. 
These are selected from tweets about movies, tv shows, popular people, sports teams etc. 
"""
_URLS = {
    "dev": "https://raw.githubusercontent.com/ardax/hashtag-segmentor/master/Dev-BOUN",
    "test": "https://raw.githubusercontent.com/ardax/hashtag-segmentor/master/Test-BOUN"
}

class Boun(datasets.GeneratorBasedBuilder):

    VERSION = datasets.Version("1.0.0")

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "index": datasets.Value("int32"),
                    "hashtag": datasets.Value("string"),
                    "segmentation": datasets.Value("string")
                }
            ),
            supervised_keys=None,
            homepage="https://github.com/ardax/hashtag-segmentor",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        downloaded_files = dl_manager.download(_URLS)
        return [
            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"] }),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"] }),
        ]

    def _generate_examples(self, filepath):

        with open(filepath, 'r') as f:
            for idx, line in enumerate(f):
                yield idx, {
                    "index": idx,
                    "hashtag": line.strip().replace(" ", ""),
                    "segmentation": line.strip()
                }