# coding=utf-8
# 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.
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"""Catalan Government Crawling."""

import os

import datasets


_CITATION = """\
@inproceedings{armengol-estape-etal-2021-multilingual,
    title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
    author = "Armengol-Estap{\'e}, Jordi  and
      Carrino, Casimiro Pio  and
      Rodriguez-Penagos, Carlos  and
      de Gibert Bonet, Ona  and
      Armentano-Oller, Carme  and
      Gonzalez-Agirre, Aitor  and
      Melero, Maite  and
      Villegas, Marta",
    booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.findings-acl.437",
    doi = "10.18653/v1/2021.findings-acl.437",
    pages = "4933--4946",
    eprint={2107.07903},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}
"""

_DESCRIPTION = """\
The Catalan Government Crawling Corpus is a 39-million-token web corpus of Catalan built from the web. It has been obtained by crawling the .gencat domain and subdomains, belonging to the Catalan Government during September and October 2020. It consists of 39.117.909 tokens, 1.565.433 sentences and 71.043 documents. Documents are separated by single new lines. It is a subcorpus of the Catalan Textual Corpus.
"""

_HOMEPAGE = "https://zenodo.org/record/5511667"

_LICENSE = "Creative Commons CC0 1.0 Universal"

_URL = "https://zenodo.org/record/5511667/files/catalan_government_crawling.zip?download=1"


class CatalanGovernmentCrawling(datasets.GeneratorBasedBuilder):
    """Catalan Government Crawling."""

    VERSION = datasets.Version("1.0.0")

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features({"text": datasets.Value("string")}),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        data_dir = dl_manager.download_and_extract(_URL)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": os.path.join(
                        data_dir, "catalan_government_crawling", "corpus", "catalan_government_crawling.txt"
                    ),
                },
            ),
        ]

    def _generate_examples(self, filepath):
        with open(filepath, encoding="utf-8") as f:
            text = ""
            for id_, line in enumerate(f):
                if line == "\n":
                    yield id_, {"text": text.strip()}
                    text = ""
                else:
                    text += line