# 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.
# See the License for the specific language governing permissions and
# limitations under the License.
# TODO: Address all TODOs and remove all explanatory comments


import csv
import json
import os

import datasets


_CITATION = """"""

_DESCRIPTION = """This new dataset is designed to measure Language Models abstractness and inclusiveness understanding in Italian."""

_HOMEPAGE = ""

_LICENSE = "CC BY 4.0"


_URLS = {
    "abs": "https://raw.githubusercontent.com/aramelior/ABRICOT-ABstRactness-and-Inclusiveness-in-COntexT/main/dataset_it.csv"
}


class abricot(datasets.GeneratorBasedBuilder):

    VERSION = datasets.Version("0.1.0")

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name="abs", version=VERSION, description="Abstraction assessment"),
        # datasets.BuilderConfig(name="ita", version=VERSION, description="Italian Understanding"),
    ]

    DEFAULT_CONFIG_NAME = "abs"

    def _info(self):
        if self.config.name == "abs":
            features = datasets.Features(
                # TODO: add after the image col is there "immagine": datasets.Value("string"),
                {
                    "ID": datasets.Value("string"),
                    "domain": datasets.Value("string"),
                    "begin": datasets.Value("int64"),
                    "end": datasets.Value("int64"),
                    "text": datasets.Value("string"),
                    "target_token": datasets.Value("string"),
                    "target_lemma": datasets.Value("string"),
                    "inc_mean": datasets.Value("float"),
                    "inc_std": datasets.Value("float"),
                    "abs_mean": datasets.Value("float"),
                    "abs_std": datasets.Value("float"),
                    "target_number": datasets.Value("string"),
                }
            )

        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):

        urls = _URLS[self.config.name]
        # data_dir = dl_manager.extract(urls)
        # if self.config.name == "abs":
        #     data_file = "dataset_it.csv"
        data_file = dl_manager.download(urls)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                # These kwargs will be passed to _generate_examples
                gen_kwargs={
                    "filepath": data_file,
                    "split": "val",
                },
            ),
        ]

    def _generate_examples(self, filepath, split):
        ds = datasets.load_dataset("csv", data_files=filepath)["train"]
        for key, row in enumerate(ds):
            # data = json.loads(row)
            if self.config.name == "abs":
                # Yields examples as (key, example) tuples
                out = {
                    "ID": row["ID"],
                    "domain": row["domain"],
                    "begin": row["begin"],
                    "end": row["end"],
                    "text": row["text"],
                    "target_token": row["target_token"],
                    "target_lemma": row["target_lemma"],
                    "inc_mean": row["inc_mean"],
                    "inc_std": row["inc_std"],
                    "abs_mean": row["abs_mean"],
                    "abs_std": row["abs_std"],
                    "target_number": row["target_number"],
                }

                yield key, out