# 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.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# Lint as: python3
"""MasakhaNEWS: News Topic Classification for African languages"""

import datasets
import pandas
import pandas as pd

logger = datasets.logging.get_logger(__name__)


_CITATION = """
@inproceedings{lawallanre-2023-geoNLPSent,
    author = "Olanrewaju",
    month = "Nov",
    year = "2023",
    address = "Lagos, Nigeria",
}
"""

_DESCRIPTION = """\
geoNLPSent is  dataset of transport tweets extrcted from twitter
The language is:
- English (eng)
"""


_URL = "https://github.com/lawallanre00490038/GeoNLP/raw/main/data/"
_TRAINING_FILE = "train.tsv"
_DEV_FILE = "dev.tsv"
_TEST_FILE = "test.tsv"


class GeoNLPSentiConfig(datasets.BuilderConfig):
    """BuilderConfig for GeoNLPsenti"""

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


class GeoNLPSenti(datasets.GeneratorBasedBuilder):
    """GeoNLPsenti dataset."""

    BUILDER_CONFIGS = [
        GeoNLPSentiConfig(name="en", version=datasets.Version("1.0.0"), description="Nollysenti English dataset")
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "label": datasets.features.ClassLabel(
                        names=["Positive", "Negative", "Neutral"]
                    ),
                    "review": datasets.Value("string"),
                }
            ),
            supervised_keys=None,
            homepage="https://github.com/lawallanre00490038/GeoNLP",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        urls_to_download = {
            "train": f"{_URL}{self.config.name}/{_TRAINING_FILE}",
            "dev": f"{_URL}{self.config.name}/{_DEV_FILE}",
            "test": f"{_URL}{self.config.name}/{_TEST_FILE}",
        }
        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"]}),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
        ]

    def _generate_examples(self, filepath):
        logger.info("⏳ Generating examples from = %s", filepath)
        df = pd.read_csv(filepath, sep='\t')
        df = df.dropna()
        N = df.shape[0]

        for id_ in range(N):
            yield id_, {
                "label": df['sentiment'].iloc[id_],
                "review": df['tweet'].iloc[id_],
            }