# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.
"""Loader script for the GermEval 18 dataset"""


import csv
import json
import os

import datasets


_CITATION = """\
@data{data/0B5VML_2019,
author = {Wiegand, Michael},
publisher = {heiDATA},
title = {{GermEval-2018 Corpus (DE)}},
year = {2019},
version = {V1},
doi = {10.11588/data/0B5VML},
url = {https://doi.org/10.11588/data/0B5VML}
}
"""

_DESCRIPTION = """\
This dataset comprises the training and test data (German tweets) from the GermEval 2018 Shared on Offensive Language Detection.
"""

_HOMEPAGE = "https://doi.org/10.11588/data/0B5VML"

_LICENSE = "CC-BY-4.0 Deed"

# The files are pulled from the official GitHub repository.
# https://github.com/uds-lsv/GermEval-2018-Data
# We use the hashed URL from master branch / June 3th 2024.
_URLS = {
    "germeval18.test.txt":  "https://raw.githubusercontent.com/uds-lsv/GermEval-2018-Data/9877472d39523effd54cd079b4c61157ed141508/germeval2018.test.txt",
    "germeval18.train.txt": "https://raw.githubusercontent.com/uds-lsv/GermEval-2018-Data/9877472d39523effd54cd079b4c61157ed141508/germeval2018.training.txt",
}

class GermEval18(datasets.GeneratorBasedBuilder):
    """The GermEval18 dataset"""

    VERSION = datasets.Version("1.1.0")

    def _info(self):
        features = datasets.Features(
            {
                "text": datasets.Value("string"),
                'coarse': datasets.ClassLabel(num_classes=2, names=['OTHER', 'OFFENSE'], names_file=None, id=None),
                'fine': datasets.ClassLabel(num_classes=4, names=['OTHER', 'ABUSE', 'INSULT', 'PROFANITY'], names_file=None, id=None),
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        downloaded_files = dl_manager.download(_URLS)

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": downloaded_files["germeval18.train.txt"],
                    "split": "train",
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                # These kwargs will be passed to _generate_examples
                gen_kwargs={
                    "filepath": downloaded_files["germeval18.test.txt"],
                    "split": "test"
                },
            ),
        ]

    def _generate_examples(self, filepath, split):
        with open(filepath, encoding="utf-8") as f:
            for key, row in enumerate(f):
                # Every line only has two "\t" tabs.
                data_text, lbl_coarse, lbl_fine = row.rstrip().split("\t")
                yield key, {
                    "text": data_text,
                    "coarse": lbl_coarse,
                    "fine": lbl_fine,
                }