# Loading script for the Ancora NER dataset. 
import datasets

logger = datasets.logging.get_logger(__name__)

_CITATION = """ """

_DESCRIPTION = """CEIL (Catalan Entity Identification and Linking).
                  This is a dataset for complex Named Eentity Reacognition (NER) created by the AINA project in the BSC for 
                  Machine Learning and Language Model evaluation purposes.
                  
                  CEIL corpus is used under [CC-by] (https://creativecommons.org/licenses/by/4.0/) licence.
                  This dataset was developed by BSC as part of the AINA project, and to enrich the Catalan Language Understanding Benchmark (CLUB).
               """

_HOMEPAGE = """https://aina.bsc.es"""

_URL = "https://huggingface.co/datasets/crodri/ceil/resolve/main/"
_TRAINING_FILE = "train.conll"
_DEV_FILE = "dev.conll"
#_TEST_FILE = "test.conll"
#_TEST_FILE = "test.conll"


class CEILConfig(datasets.BuilderConfig):
    """ Builder config for the CEIL dataset """

    def __init__(self, **kwargs):
        """BuilderConfig for CEIL.
        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(CEILConfig, self).__init__(**kwargs)


class CEIL(datasets.GeneratorBasedBuilder):
    """ CEIL dataset."""

    BUILDER_CONFIGS = [
        CEILConfig(
            name="CEIL",
            version=datasets.Version("2.0.0"),
            description="CEIL 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',
                                'I-product-vehicle',
                                'I-organization-sportsteam',
                                'B-location-road/railway/highway/transit',
                                'I-CW-other',
                                'B-event-other',
                                'I-CW-painting',
                                'I-person-group',
                                'B-CW-music',
                                'I-location-other',
                                'B-organization-religious',
                                'I-product-E-device',
                                'B-product-software',
                                'B-event-attack/terrorism/militaryconflict',
                                'B-organization-politicalparty',
                                'B-person-scholar/scientist',
                                'I-person-artist/author',
                                'B-CW-other',
                                'I-person-influencer',
                                'B-event-protest',
                                'I-building-other',
                                'I-organization-other',
                                'B-organization-sportsteam',
                                'B-organization-media',
                                'I-event-disaster',
                                'I-organization-privatecompany',
                                'I-event-other',
                                'B-location-other',
                                'B-product-clothing',
                                'B-organization-education',
                                'B-building-sportsfacility',
                                'I-building-shops',
                                'I-location-park',
                                'B-organization-government',
                                'I-person-politician',
                                'B-building-airport',
                                'B-CW-writtenart',
                                'B-location-park',
                                'B-location-island',
                                'I-building-hotel',
                                'B-Other',
                                'B-organization-other',
                                'B-person-group',
                                'B-event-disaster',
                                'I-organization-onlinebusiness',
                                'B-product-consumer_good',
                                'I-CW-broadcastprogram',
                                'I-person-other',
                                'B-building-hotel',
                                'B-product-vehicle',
                                'I-organization-politicalparty',
                                'B-event-political',
                                'B-location-mountain',
                                'I-organization-religious',
                                'B-GPE',
                                'I-location-mountain',
                                'I-CW-film',
                                'I-CW-music',
                                'B-location-bodiesofwater',
                                'I-location-road/railway/highway/transit',
                                'I-event-sportsevent',
                                'B-organization-onlinebusiness',
                                'I-organization-government',
                                'I-person-actor/director',
                                'B-person-athlete',
                                'I-organization-education',
                                'I-event-attack/terrorism/militaryconflict',
                                'I-product-consumer_good',
                                'I-building-hospital',
                                'B-building-shops',
                                'I-event-political',
                                'I-building-religious',
                                'B-CW-painting',
                                'I-building-sportsfacility',
                                'I-event-protest',
                                'B-building-restaurant',
                                'B-person-politician',
                                'B-product-other',
                                'I-CW-writtenart',
                                'I-product-other',
                                'I-product-food',
                                'B-event-sportsevent',
                                'B-CW-film',
                                'I-product-clothing',
                                'B-CW-broadcastprogram',
                                'I-product-software',
                                'I-person-athlete',
                                'B-product-E-device',
                                'B-person-actor/director',
                                'B-building-religious',
                                'I-GPE',
                                'B-person-artist/author',
                                'B-organization-privatecompany',
                                'I-building-restaurant',
                                'B-building-hospital',
                                'I-Other',
                                'I-person-scholar/scientist',
                                'B-person-influencer',
                                'B-person-other',
                                'I-location-bodiesofwater',
                                'I-building-airport',
                                'I-organization-media',
                                'B-product-food',
                                'B-building-other',
                                'B-building-governmentfacility',
                                'I-building-governmentfacility',
                                'I-location-island'
                            ]
                        )
                    ),
                }
            ),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            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"]}),
            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
#            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["test"]}),
        ]

    def _generate_examples(self, filepath):
        logger.info("⏳ Generating examples from = %s", filepath)
        with open(filepath, encoding="utf-8") as f:
            guid = 0
            tokens = []
            ner_tags = []
            n = 0
            for line in f:
                try:
                    n += 1
                    if line.startswith("-DOCSTART-") or line == "" or line == "\n" or line == "\xa0\n":
                        if tokens:
                            yield guid, {
                                "id": str(guid),
                                "tokens": tokens,
                                "ner_tags": ner_tags,
                            }
                            guid += 1
                            tokens = []
                            ner_tags = []
                    else:
                        # CEIL tokens are tab separated
                        splits = line.split('\t')
                        tokens.append(splits[0])
                        ner_tags.append(splits[-1].rstrip())
                except  Exception as error:
                    print(error)
                    print("line: ",n)
                    print("Error line: ",line)
            # last example
            yield guid, {
                "id": str(guid),
                "tokens": tokens,
                "ner_tags": ner_tags,
            }