story.py

import csv
import os

import datasets

_CITATION = """\
@Dataset{wisdomify:storyteller,
title = {Korean proverb definitions and examples},
author={Jongyoon Kim, Yubin Kim, Yongtaek Im
},
year={2021}
}
"""

_DESCRIPTION = """\
This dataset is designed to provide forward and reverse dictionary of Korean proverbs.
"""

# TODO: Add a link to an official homepage for the dataset here
_HOMEPAGE = ""

# TODO: Add the licence for the dataset here if you can find it
_LICENSE = ""

# TODO: Add link to the official dataset URLs here
#  If it is dropbox link, you must set 1 for query parameter "dl".
_URLs = {
    'definition': "https://www.dropbox.com/s/4uh564afaimtob3/definition.zip?dl=1",
    'example': "https://www.dropbox.com/s/adlt9n6x5gjs0a6/example.zip?dl=1",
}


class Story(datasets.GeneratorBasedBuilder):
    # version must be "x.y.z' form
    VERSION = datasets.Version("0.0.0")

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name="definition", version=VERSION, description="definition"),
        datasets.BuilderConfig(name="example", version=VERSION, description="example"),
    ]

    # This config is applied when user load dataset without "name".
    DEFAULT_CONFIG_NAME = "definition"

    def _info(self):
        # This method specifies the datasets.DatasetInfo object which contains information
        #                                                            and typings for the dataset

        if self.config.name == "definition":
            # These are the features of your dataset like images, labels ...
            features = datasets.Features(
                {
                    "wisdom": datasets.Value("string"),
                    "def": datasets.Value("string"),

                }
            )
        elif self.config.name == "example":
            features = datasets.Features(
                {
                    "wisdom": datasets.Value("string"),
                    "eg": datasets.Value("string"),
                }
            )
        else:
            raise NotImplementedError(f"Wrong name: {self.config.name}")

        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            supervised_keys=None,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        # This method is used when user loads dataset.
        # dl_manager can be used to download and extract the dataset
        # and also can set split depending onf the configuration

        # Downloading data with _URLs
        downloaded_files = dl_manager.download_and_extract(_URLs[self.config.name])

        dtp = 'def' if self.config.name == "definition" else 'eg'

        train_path = os.path.join(downloaded_files, f'train_wisdom2{dtp}.tsv')
        val_path = os.path.join(downloaded_files, f'val_wisdom2{dtp}.tsv')
        test_path = os.path.join(downloaded_files, f'test_wisdom2{dtp}.tsv')

        return [
            # These gen_kwargs will be passed to _generate_examples
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={"filepath": train_path, "split": "train"},
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={"filepath": val_path, "split": "validation"},
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={"filepath": test_path, "split": "test"},
            ),
        ]

    def _generate_examples(self, filepath, split):
        # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
        """ Yields examples as (key, example) tuples. """
        # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
        # The `key` is here for legacy reason (tfds) and is not important in itself.

        with open(filepath, encoding="utf-8") as f:
            tsv_reader = csv.reader(f, delimiter="\t")
            for id_, row in enumerate(tsv_reader):
                if id_ == 0:
                    continue  # first row shows column info

                if self.config.name == "definition":
                    yield id_, {
                        "wisdom": row[0],
                        "def": row[1],
                    }
                elif self.config.name == "example":
                    yield id_, {
                        "wisdom": row[0],
                        "eg": row[1],
                    }
                else:
                    raise NotImplementedError(f"Wrong name: {self.config.name}")