"""TODO: DATASET SHORT DESCRIPTION"""

import json
import datasets
from datasets.tasks import TextClassification

_DESCRIPTION = """TODO: DATASET DESCRIPTION"""

_CITATION = """TODO: CITATIONS"""

_URL = "https://huggingface.co/datasets/rsgrava/deepage2_qa_dataset/resolve/main/"
_URLS = {
    "train": _URL + "expanded_ds-train.json",
    "dev": _URL + "expanded_ds-test.json",
}

class SquadV1PtBr(datasets.GeneratorBasedBuilder):
    """TODO: SHORT DATASET DESCRIPTION"""

    VERSION = datasets.Version("1.1.0")

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "source_text": datasets.Value("string"),
                    "target_text": datasets.Value("string"),
                }
            ),
            # No default supervised_keys (as we have to pass both question and context as input).
            supervised_keys=None,
            homepage="TODO: HOMEPAGE",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        urls_to_download = _URLS
        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"]}),
        ]

    def _generate_examples(self, filepath):
        with open(filepath) as f:
            key = 0
            ids = []
            squad = json.load(f)
            for article in squad["data"]:
                for paragraph in article["paragraphs"]:
                    source_text = paragraph["context"].strip()
                    questions = []
                    for qa in paragraph["qas"]:
                        id_ = qa["id"]
                        if id_ in ids:
                            #skip duplicate entries
                            continue
                        else:
                            ids.append(id_)
                        questions.append(qa["question"].strip())
                    target_text = "<sep>".join(questions)

                    yield key, {
                        "source_text": source_text,
                        "target_text": target_text,
                    }
                    key += 1