# coding=utf-8
# Copyright 2020 The TensorFlow Datasets Authors and the 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
"""mrobust dataset."""

import datasets


# _CITATION = """
# @misc{bonifacio2021mmarco,
#       title={mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Dataset},
#       author={Luiz Henrique Bonifacio and Israel Campiotti and Vitor Jeronymo and Hugo Queiroz Abonizio and Roberto Lotufo and Rodrigo Nogueira},
#       year={2021},
#       eprint={2108.13897},
#       archivePrefix={arXiv},
#       primaryClass={cs.CL}
# }
# """

# _URL = "https://github.com/unicamp-dl/mMARCO"

_DESCRIPTION = """
Robust04 translated datasets
"""

def generate_examples_tuples(filepath):
    with open(filepath, encoding="utf-8") as f:
        for (idx, line) in enumerate(f):
            idx, text = line.rstrip().split("\t")
            features = {
                "id": idx,
                "text": text,
            }
            yield idx, features

_BASE_URLS = {
    "collections": "https://huggingface.co/datasets/unicamp-dl/mrobust/resolve/main/data/collections/",
    "queries": "https://huggingface.co/datasets/unicamp-dl/mrobust/resolve/main/data/queries/",
}

LANGUAGES = [
    "chinese",
    "dutch",
    "english",
    "french",
    "german",
    "indonesian",
    "italian",
    "portuguese",
    "russian",
    "spanish",
    "vietnamese",
]


class MRobust(datasets.GeneratorBasedBuilder):

    BUILDER_CONFIGS = (
        [
            datasets.BuilderConfig(
                name=f"collection-{language}",
                description=f"{language.capitalize()} collection",
                version=datasets.Version("1.0.0"),
            )
            for language in LANGUAGES
        ]
        + [
            datasets.BuilderConfig(
                name=f"queries-{language}",
                description=f"{language.capitalize()} queries",
                version=datasets.Version("1.0.0"),
            )
            for language in LANGUAGES
        ]
    )

    DEFAULT_CONFIG_NAME = "english"

    def _info(self):
        name = self.config.name
        if name.startswith("collection") or name.startswith("queries"):
            features = {
                "id": datasets.Value("string"),
                "text": datasets.Value("string"),
            }

        return datasets.DatasetInfo(
            description=f"{_DESCRIPTION}\n{self.config.description}",
            features=datasets.Features(features),
            supervised_keys=None,
            # homepage=_URL,
            # citation=_CITATION,
        )

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

        if self.config.name.startswith("collection"):
            url = _BASE_URLS["collections"] + self.config.name[11:] + "_collection.tsv"
            dl_path = dl_manager.download_and_extract(url)
            return (datasets.SplitGenerator(name="collection", gen_kwargs={"filepath": dl_path}),)
        elif self.config.name.startswith("queries"):
            url = _BASE_URLS["queries"] + self.config.name[8:] + "_queries.tsv"
            dl_path = dl_manager.download_and_extract(url)
            return (datasets.SplitGenerator(name="queries", gen_kwargs={"filepath": dl_path}),)

    def _generate_examples(self, filepath, args=None):
        """Yields examples."""

        if self.config.name.startswith("collection") or self.config.name.startswith("queries"):
            return generate_examples_tuples(filepath)