import datasets


logger = datasets.logging.get_logger(__name__)


_CITATION = """
ALBUQUERQUE2022,author="Albuquerque, Hidelberg O. and Costa, Rosimeire and Silvestre, Gabriel and Souza, Ellen and da Silva, N{\'a}dia F. F. and Vit{\'o}rio, Douglas and Moriyama, Gyovana and Martins, Lucas and Soezima, Luiza and Nunes, Augusto and Siqueira, Felipe and Tarrega, Jo{\~a}o P. and Beinotti, Joao V. and Dias, Marcio and Silva, Matheus and Gardini, Miguel and Silva, Vinicius and de Carvalho, Andr{\'e} C. P. L. F. and Oliveira, Adriano L. I.", title="{UlyssesNER-Br}: A Corpus of Brazilian Legislative Documents for Named Entity Recognition", booktitle="Computational Processing of the Portuguese Language", year="2022", pages="3--14",@inproceedings{inPress, PROPOR2022}
"""

_DESCRIPTION = """
PL-corpus is a Portuguese language dataset for named entity recognition applied to legislative documents. Its parte of the UlyssesBR-corpus, and consists entirely of manually annotated public bills texts (projetos de leis) and contains tags for persons, locations, date entities, organizations, legal foundation and bills.
"""

_HOMEPAGE = "https://github.com/Convenio-Camara-dos-Deputados/ulyssesner-br-propor"

_URL = "https://raw.githubusercontent.com/bergoliveira/assessment-of-deep-learning-models-icann/main/pl-corpus/"
_TRAINING_FILE = "train.conll"
_DEV_FILE = "dev.conll"
_TEST_FILE = "test.conll"


class PlCorpus(datasets.GeneratorBasedBuilder):
    """pL-corpus dataset"""

    VERSION = datasets.Version("1.0.0")

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name="pl-corpus", version=VERSION, description="PL-corpus dataset"),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "id": datasets.Value("string"),
                    "tokens": datasets.Sequence(datasets.Value("string")),
                    "ner_tags": datasets.Sequence(
                        datasets.features.ClassLabel(
                            names=[
                                "O",
                                "B-ORGANIZACAO",
                                "I-ORGANIZACAO",
                                "B-PESSOA",
                                "I-PESSOA",
                                "B-DATA",
                                "I-DATA",
                                "B-LOCAL",
                                "I-LOCAL",
                                "B-FUNDAMENTO",
                                "I-FUNDAMENTO",
                                "B-PRODUTODELEI",
                                "I-PRODUTODELEI",
                                "B-EVENTO",
                                "I-EVENTO",
                            ]
                        )
                    ),
                }
            ),
            supervised_keys=None,
            homepage="https://github.com/Convenio-Camara-dos-Deputados/ulyssesner-br-propor",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        urls_to_download = {
            "train": f"{_URL}{_TRAINING_FILE}",
            "dev": f"{_URL}{_DEV_FILE}",
            "test": f"{_URL}{_TEST_FILE}",
        }
        downloaded_files = dl_manager.download_and_extract(urls_to_download)

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={"filepath": downloaded_files["train"], "split": "train"},
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={"filepath": downloaded_files["dev"], "split": "validation"},
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={"filepath": downloaded_files["test"], "split": "test"},
            ),
        ]

    def _generate_examples(self, filepath, split):
        """Yields examples."""

        logger.info("⏳ Generating examples from = %s", filepath)

        with open(filepath, encoding="utf-8") as f:

            guid = 0
            tokens = []
            ner_tags = []

            for line in f:
                if line == "" or line == "\n":
                    if tokens:
                        yield guid, {
                            "id": str(guid),
                            "tokens": tokens,
                            "ner_tags": ner_tags,
                        }
                        guid += 1
                        tokens = []
                        ner_tags = []
                else:
                    splits = line.split(" ")
                    tokens.append(splits[0])
                    ner_tags.append(splits[1].rstrip())

            # last example
            yield guid, {
                "id": str(guid),
                "tokens": tokens,
                "ner_tags": ner_tags,
            }