"""
Data loader script for the eur-lex-sum summarization dataset by Aumiller, Chouhan and Gertz.
The script itself was adapted from the XLSum data loader.
"""
import os
import json

import datasets
from datasets.tasks import Summarization


logger = datasets.logging.get_logger(__name__)


_CITATION = """\
@article{aumiller-etal-2022-eur,
author = {Aumiller, Dennis and Chouhan, Ashish and Gertz, Michael},
title = {{EUR-Lex-Sum: A Multi- and Cross-lingual Dataset for Long-form Summarization in the Legal Domain}},
journal = {CoRR},
volume = {abs/2210.13448},
eprinttype = {arXiv},
eprint = {2210.13448},
url = {https://arxiv.org/abs/2210.13448}
}
"""

_HOMEPAGE = "https://github.com/achouhan93/eur-lex-sum"

_LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)"

_DESCRIPTION = """\
The EUR-Lex-Sum dataset is a multilingual resource intended for text summarization in the legal domain.
It is based on human-written summaries of legal acts issued by the European Union.
It distinguishes itself by introducing a smaller set of high-quality human-written samples,
each of which have much longer references (and summaries!) than comparable datasets.
Additionally, the underlying legal acts provide a challenging domain-specific application to legal texts,
which are so far underrepresented in non-English languages.
For each legal act, the sample can be available in up to 24 languages
(the officially recognized languages in the European Union);
the validation and test samples consist entirely of samples available in all languages,
and are aligned across all languages at the paragraph level.
"""

_LANGUAGES = [
    "bulgarian",
    "czech",
    "dutch",
    "estonian",
    "french",
    "greek",
    "",
    "irish",
    "latvian",
    "maltese",
    "portuguese",
    "slovak",
    "spanish",
    "croatian",
    "danish",
    "english",
    "finnish",
    "german",
    "hungarian",
    "italian",
    "lithuanian",
    "polish",
    "romanian",
    "slovenian",
    "swedish"
]

_URL = "https://huggingface.co/datasets/dennlinger/eur-lex-sum/resolve/main/data/"
_URLS = {
    "train": _URL + "{}/train.json",
    "validation": _URL + "{}/validation.json",
    "test": _URL + "{}/test.json",
}


class EurLexSumConfig(datasets.BuilderConfig):
    """BuilderConfig for EUR-Lex-Sum."""

    def __init__(self, **kwargs):
        """BuilderConfig for EUR-Lex-Sum.
        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(EurLexSumConfig, self).__init__(**kwargs)


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

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name=f"{lang}",
            version=datasets.Version("1.0.0")
        )
        for lang in _LANGUAGES
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "celex_id": datasets.Value("string"),
                    "reference": datasets.Value("string"),
                    "summary": datasets.Value("string")
                }
            ),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            citation=_CITATION,
            license=_LICENSE,
            task_templates=[
                Summarization(task="summarization", text_column="reference", summary_column="summary")
            ],
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        lang = str(self.config.name)

        # Add language tag for each split
        urls = {k: url.format(lang) for k, url in _URLS.items()}
        data_dir = dl_manager.download_and_extract(urls)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": data_dir["train"],
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={
                    "filepath": data_dir["validation"],
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "filepath": data_dir["test"],
                },
            ),
        ]

    def _generate_examples(self, filepath):
        """Yields examples as (key, example) tuples."""
        with open(filepath) as f:
            for idx_, row in enumerate(f):
                data = json.loads(row)
                yield idx_, data