from __future__ import annotations

from mteb.abstasks.TaskMetadata import TaskMetadata

from ....abstasks import AbsTaskClassification


class GermanPoliticiansTwitterSentimentClassification(AbsTaskClassification):
    metadata = TaskMetadata(
        name="GermanPoliticiansTwitterSentimentClassification",
        description="GermanPoliticiansTwitterSentiment is a dataset of German tweets categorized with their sentiment (3 classes).",
        reference="https://aclanthology.org/2022.konvens-1.9",
        dataset={
            "path": "Alienmaster/german_politicians_twitter_sentiment",
            "revision": "65343b17f5a76227ab2e15b9424dfab6466ffcb1",
        },
        type="Classification",
        category="s2s",
        eval_splits=["test"],
        eval_langs=["deu-Latn"],
        main_score="accuracy",
        date=("2021-01-01", "2021-12-31"),
        form=["written"],
        domains=["Social", "Government"],
        task_subtypes=["Sentiment/Hate speech"],
        license="Not specified",
        socioeconomic_status="high",
        annotations_creators="human-annotated",
        dialect=[],
        text_creation="found",
        bibtex_citation="""
            @inproceedings{schmidt-etal-2022-sentiment,
                title = "Sentiment Analysis on {T}witter for the Major {G}erman Parties during the 2021 {G}erman Federal Election",
                author = "Schmidt, Thomas  and
                Fehle, Jakob  and
                Weissenbacher, Maximilian  and
                Richter, Jonathan  and
                Gottschalk, Philipp  and
                Wolff, Christian",
                editor = "Schaefer, Robin  and
                Bai, Xiaoyu  and
                Stede, Manfred  and
                Zesch, Torsten",
                booktitle = "Proceedings of the 18th Conference on Natural Language Processing (KONVENS 2022)",
                month = "12--15 " # sep,
                year = "2022",
                address = "Potsdam, Germany",
                publisher = "KONVENS 2022 Organizers",
                url = "https://aclanthology.org/2022.konvens-1.9",
                pages = "74--87",
            }
        """,
        n_samples={"test": 357},
        avg_character_length={"test": 302.48},
    )

    def dataset_transform(self):
        self.dataset = self.dataset.rename_column("majority_sentiment", "label")