# dadrah_dataset.json
# persian-conversational-dataset
"""TODO(empathetic_dialogues): Add a description here."""


import csv,json

import datasets


_DESCRIPTION = """\
persian-conversational-dataset
"""
_URL = "https://dl.fbaipublicfiles.com/parlai/empatheticdialogues/empatheticdialogues.tar.gz"


class persianConversation(datasets.GeneratorBasedBuilder):

    VERSION = datasets.Version("0.1.0")

    def _info(self):
        # TODO(empathetic_dialogues): Specifies the datasets.DatasetInfo object
        return datasets.DatasetInfo(
            # This is the description that will appear on the datasets page.
            description=_DESCRIPTION,
            # datasets.features.FeatureConnectors
            features=datasets.Features(
                {
                    "title": datasets.Value("string"),
                    "question": datasets.Value("string"),
                    "answers": datasets.Value("list"),
                    "keywords": datasets.Value("list"),
                    # These are the features of your dataset like images, labels ...
                }
            ),
            # If there's a common (input, target) tuple from the features,
            # specify them here. They'll be used if as_supervised=True in
            # builder.as_dataset.
            supervised_keys=None,
            # Homepage of the dataset for documentation
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        # TODO(empathetic_dialogues): Downloads the data and defines the splits
        # dl_manager is a datasets.download.DownloadManager that can be used to
        # download and extract URLs
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                # These kwargs will be passed to _generate_examples
                gen_kwargs={"files": ["dadrah_dataset.json"], "split_file": "dadrah_dataset.json"},
            ),
        ]

    def _generate_examples(self, files, split_file):
        """Yields examples."""
        for path, f in files:
            if split_file == path:
                with open(split_file, 'r', encoding='utf-8') as fmm:
                    data=json.load(fmm)
                for id_, row in enumerate(data):
                    title=row[0]
                    question=row[1]
                    answers=row[2]
                    keywords=row[3]
                    if id_==20:
                        break;
                    yield id_, {
                        "title": title,
                        "question": question,
                        "answers": answers,
                        "keywords": keywords,
                    }
                    
                break