# coding=utf-8
# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
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#     http://www.apache.org/licenses/LICENSE-2.0
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# Lint as: python3
"""Software Applications User Reviews"""


import csv

import datasets


_DESCRIPTION = """\
It is a large dataset of Android applications belonging to 23 differentapps categories, which provides an overview of the types of feedback users report on the apps and documents the evolution of the related code metrics. The dataset contains about 395 applications of the F-Droid repository, including around 600 versions, 280,000 user reviews (extracted with specific text mining approaches)
"""

_CITATION = """\
@InProceedings{Zurich Open Repository and
Archive:dataset,
title = {Software Applications User Reviews},
authors={Grano, Giovanni; Di Sorbo, Andrea; Mercaldo, Francesco; Visaggio, Corrado A; Canfora, Gerardo;
Panichella, Sebastiano},
year={2017}
}
"""

_TRAIN_DOWNLOAD_URL = "https://raw.githubusercontent.com/sealuzh/user_quality/master/csv_files/reviews.csv"


class AppReviews(datasets.GeneratorBasedBuilder):
    """Software Application Reviews by Users."""

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "package_name": datasets.Value("string"),
                    "review": datasets.Value("string"),
                    "date": datasets.Value("string"),
                    "star": datasets.Value("int8"),
                }
            ),
            homepage="https://giograno.me/assets/pdf/workshop/wama17.pdf",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        train_path = dl_manager.download_and_extract(_TRAIN_DOWNLOAD_URL)
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
        ]

    def _generate_examples(self, filepath):
        """Generate Distaster Response Messages examples."""
        with open(filepath, encoding="utf-8") as csv_file:
            csv_reader = csv.reader(
                csv_file, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True
            )
            next(csv_reader, None)
            for id_, row in enumerate(csv_reader):
                row = row[1:5]
                (package_name, review, date, star) = row

                yield id_, {
                    "package_name": (package_name),
                    "review": (review),
                    "date": (date),
                    "star": int(star),
                }