import json

import datasets

logger = datasets.logging.get_logger(__name__)

# TODO: Add BibTeX citation
# Find for instance the citation on arxiv or on the dataset repo/website
_CITATION = """\
@InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
}
"""

# TODO: Add description of the dataset here
# You can copy an official description
_DESCRIPTION = """\
SemEval 2023 Task LegalEval
"""

# TODO: Add a link to an official homepage for the dataset here
_HOMEPAGE = ""

# TODO: Add the licence for the dataset here if you can find it
_LICENSE = ""

# TODO: Add link to the official dataset URLs here
# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
_URLS = ""


class LegalevalRrConfig(datasets.BuilderConfig):
    """BuilderConfig for Multiconer2"""

    def __init__(self, **kwargs):
        """BuilderConfig for Multiconer2.
        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(LegalevalRrConfig, self).__init__(**kwargs)


class LegalevalRr(datasets.GeneratorBasedBuilder):
    VERSION = datasets.Version("1.0.0")

    # This is an example of a dataset with multiple configurations.
    # If you don't want/need to define several sub-sets in your dataset,
    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.

    # If you need to make complex sub-parts in the datasets with configurable options
    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
    # BUILDER_CONFIG_CLASS = MyBuilderConfig

    # You will be able to load one or the other configurations in the following list with
    # data = datasets.load_dataset('my_dataset', 'first_domain')
    # data = datasets.load_dataset('my_dataset', 'second_domain')
    BUILDER_CONFIGS = [
        LegalevalRrConfig(name="it", version=VERSION),
        LegalevalRrConfig(name="cl", version=VERSION),
        LegalevalRrConfig(name="all", version=VERSION),
    ]

    DEFAULT_CONFIG_NAME = "all"

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "id": datasets.Value("uint32"),
                    "annotation_id": datasets.Value("string"),
                    "text": datasets.Value("string"),
                    "label":
                        datasets.features.ClassLabel(
                            names=[
                                'NONE',
                                "RPC",
                                "RATIO",
                                "PRE_NOT_RELIED",
                                "PRE_RELIED",
                                "STA",
                                "ANALYSIS",
                                "ARG_RESPONDENT",
                                "ARG_PETITIONER",
                                "ISSUE",
                                "RLC",
                                "FAC",
                                "PREAMBLE"]
                        )
                }
            ),
            supervised_keys=None,
            homepage="",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager: datasets.DownloadManager):
        """Returns SplitGenerators."""

        downloaded_files = dl_manager.download_and_extract({
            "train": "train.json",
            "dev": "dev.json",
            "test": "RR_TEST_DATA_FS.json"
        })

        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)
        config_name = self.config.name
        with open(filepath, encoding="utf-8") as f:
            data = json.load(f)
        cnt = 0
        for row in data:
            meta_group = row["meta"]["group"]
            if config_name == "it" and meta_group != "Tax":
                continue
            if config_name == "cl" and meta_group != "Criminal":
                continue
            for annotation in row["annotations"][0]['result']:
                yield cnt, {
                    "id": row["id"],
                    "annotation_id": annotation["id"],
                    "text": annotation["value"]["text"],
                    "label": annotation["value"]["labels"][0],
                }
                cnt += 1