# Loading script for the Telugu-English Codeswitch Transliterate dataset
import datasets

logger = datasets.logging.get_logger(__name__)

_CITATION = """ """

_DESCRIPTION = """Telugu English POS Codeswitch dataset.
               """

_HOMEPAGE = ""

_URL = "https://huggingface.co/datasets/anishka/CodeSwitching-TE-EN/blob/main/"
_TRAINING_FILE = "TWT-train.conllu"
_DEV_FILE = "TWT-dev.conllu"
_TEST_FILE = "TWT-test.conllu"


class TeEnCodeSwitchConfig(datasets.BuilderConfig):
    """ Builder config for the Ancora Ca NER dataset """

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


class TeEnCodeSwitch(datasets.GeneratorBasedBuilder):
    """ Te-En-CodeSwitch dataset."""

    BUILDER_CONFIGS = [
        TeEnCodeSwitchConfig(
            name="Te-En-CodeSwitch",
            version=datasets.Version("0.0.1"),
            description="Te-En-CodeSwitch 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=[
                                "NOUN",
                                "PUNCT",
                                "ADP",
                                "NUM",
                                "SYM",
                                "SCONJ",
                                "ADJ",
                                "PART",
                                "DET",
                                "CCONJ",
                                "PROPN",
                                "PRON",
                                "X",
                                "_",
                                "ADV",
                                "INTJ",
                                "VERB",
                                "AUX",
                            ]
                        )
                    ),
                    "xpos": datasets.Sequence(datasets.Value("string")),
                    "feats": datasets.Sequence(datasets.Value("string")),
                    "head": datasets.Sequence(datasets.Value("string")),
                    "deprel": datasets.Sequence(datasets.Value("string")),
                    "deps": datasets.Sequence(datasets.Value("string")),
                    "misc": datasets.Sequence(datasets.Value("string")),
                }
            ),
            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)
        print ("Downloading files: ")
        print (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.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
        ]

    def _generate_examples(self, filepath):
        id = 0
        for path in filepath:
            with open(path, "r", encoding="utf-8") as data_file:
                tokenlist = list(conllu.parse_incr(data_file))
                for sent in tokenlist:
                    if "sent_id" in sent.metadata:
                        idx = sent.metadata["sent_id"]
                    else:
                        idx = id

                    tokens = [token["form"] for token in sent]

                    if "text" in sent.metadata:
                        txt = sent.metadata["text"]
                    else:
                        txt = " ".join(tokens)

                    yield id, {
                        "idx": str(idx),
                        "text": txt,
                        "tokens": [token["form"] for token in sent],
                        "lemmas": [token["lemma"] for token in sent],
                        "upos": [token["upos"] for token in sent],
                        "xpos": [token["xpos"] for token in sent],
                        "feats": [str(token["feats"]) for token in sent],
                        "head": [str(token["head"]) for token in sent],
                        "deprel": [str(token["deprel"]) for token in sent],
                        "deps": [str(token["deps"]) for token in sent],
                        "misc": [str(token["misc"]) for token in sent],
                    }
                    id += 1