# coding=utf-8
# Copyright 2020 HuggingFace Datasets Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#
#     http://www.apache.org/licenses/LICENSE-2.0
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# Lint as: python3
"""YOSM: A NEW YORUBA SENTIMENT CORPUS FOR MOVIE REVIEWS"""

import datasets
import json
import pandas as pd

logger = datasets.logging.get_logger(__name__)

_CITATION = """\
        @inproceedings{
        shode2022yosm,
        title={{YOSM}: A {NEW} {YORUBA} {SENTIMENT} {CORPUS} {FOR} {MOVIE} {REVIEWS}},
        author={Iyanuoluwa Shode and David Ifeoluwa Adelani and Anna Feldman},
        booktitle={3rd Workshop on African Natural Language Processing},
        year={2022},
        url={https://openreview.net/forum?id=rRzx5qzVIb9}
        }
        """

_DESCRIPTION = """\
YOSM: A NEW YORUBA SENTIMENT CORPUS FOR MOVIE REVIEWS
- Yoruba
"""

languages=[
    'yoruba'
]

_URL = "https://github.com/IyanuSh/YOSM"
_TRAINING_FILE = "train.tsv"
_DEV_FILE = "dev.tsv"
_TEST_FILE = "test.tsv"

class Yosm(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            version=datasets.Version('1.0.0'),
            name=lang, 
            description='YOSM: A NEW YORUBA SENTIMENT CORPUS FOR MOVIE REVIEWS'
        ) for lang in languages
    ]

    def _info(self):
        features = datasets.features({
            'yo_review': datasets.Value('string'),
            'sentiment': datasets.Value('string')
        })

        return datasets.DatasetInfo(
            # This is the description that will appear on the datasets page.
            description=_DESCRIPTION,
            # This defines the different columns of the dataset and their types
            features=features,  # Here we define them above because they are different between the two configurations
            supervised_keys=None,
            # Homepage of the dataset for documentation
            homepage=_URL,
            # License for the dataset if available
            license='',
            # Citation for the dataset
            citation=_CITATION,
        )
    
    def _split_generators(self, dl_manager):
        lang = self.config.name

        splits = [
            datasets.SplitGenerator(
                name='train',
                gen_kwargs={
                    'filepath': _TRAINING_FILE,
                },
            ),
            datasets.SplitGenerator(
                name='dev',
                gen_kwargs={
                    'filepath': _DEV_FILE,
                },
            ),
            datasets.SplitGenerator(
                name='test',
                gen_kwargs={
                    'filepath': _TEST_FILE,
                },
            )

        ]
        return splits
    
    def _generate_examples(self, filepath):
        yosm_df = pd.read_csv(filepath, sep="\t", lineterminator='\n')
        for index, row in yosm_df.iterrows():
            yield row["yo_review"], row["sentiment"]