# 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
"""Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition"""

import csv
import os

import datasets


logger = datasets.logging.get_logger(__name__)


_CITATION = """\
@inproceedings{lozhnikov2018stance,
  title={Stance prediction for russian: data and analysis},
  author={Lozhnikov, Nikita and Derczynski, Leon and Mazzara, Manuel},
  booktitle={International Conference in Software Engineering for Defence Applications},
  pages={176--186},
  year={2018},
  organization={Springer}
}
"""

_DESCRIPTION = """\
This is a stance prediction dataset in Russian. The dataset contains comments on news articles,
and rows are a comment, the title of the news article it responds to, and the stance of the comment
towards the article.
"""

_URL = "rustance_dataset.csv"


class RuStanceConfig(datasets.BuilderConfig):
    """BuilderConfig for RuStance"""

    def __init__(self, **kwargs):
        """BuilderConfig RuStance.

        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(RuStanceConfig, self).__init__(**kwargs)


class RuStance(datasets.GeneratorBasedBuilder):
    """RuStance dataset."""

    BUILDER_CONFIGS = [
        RuStanceConfig(name="rustance", version=datasets.Version("1.0.0"), description="Stance dataset in Russian"),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "id": datasets.Value("string"),
                    "text": datasets.Value("string"),
                    "title": datasets.Value("string"),
                    "stance": datasets.features.ClassLabel(
                        names=[
                            "support",
                            "deny",
                            "query",
                            "comment",
                        ]
                    )
                }
            ),
            supervised_keys=None,
            homepage="https://link.springer.com/chapter/10.1007/978-3-030-14687-0_16",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        downloaded_file = dl_manager.download_and_extract(_URL)

        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file}),
        ]

    def _generate_examples(self, filepath):
        logger.info("⏳ Generating examples from = %s", filepath)
        with open(filepath, encoding="utf-8") as f:
            rustance_reader = csv.DictReader(f, delimiter=";", quotechar='"')
            guid = 0
            for instance in rustance_reader:
                instance["id"] = str(guid)
                if instance['Stance'] == "s":
                    instance['Stance'] = "support"
                elif instance['Stance'] == "d":
                    instance['Stance'] = "deny" 
                elif instance['Stance'] == "q":
                    instance['Stance'] = "query" 
                elif instance['Stance'] == "c":
                    instance['Stance'] = "comment" 

                instance["text"] = instance.pop("Text")
                instance["title"] = instance.pop("Title")
                instance["stance"] = instance.pop("Stance")

                yield guid, instance
                guid += 1