import os
import json
import datasets
from typing import List
import logging
import csv

_DESCRIPTION = """\
A collection of multilingual 3-class sentiments (positive, neutral, negative) dataset.

Most multilingual sentiment datasets are either 5-class ratings of products reviews (e.g. Amazon multilingual dataset) or don't include Asian languages (e.g. Malay).
"""


class MultilingualSentimentsConfig(datasets.BuilderConfig):
    """BuilderConfig for IndoNLU"""

    def __init__(
        self,
        features,
        train_url,
        valid_url,
        test_url,
        citation,
        **kwargs,
    ):
        """BuilderConfig for Multilingual Sentiments.
        Args:
          text_features: `dict[string, string]`, map from the name of the feature
            dict for each text field to the name of the column in the txt/csv/tsv file
          label_column: `string`, name of the column in the txt/csv/tsv file corresponding
            to the label
          label_classes: `list[string]`, the list of classes if the label is categorical
          train_url: `string`, url to train file from
          valid_url: `string`, url to valid file from
          test_url: `string`, url to test file from
          citation: `string`, citation for the data set
          **kwargs: keyword arguments forwarded to super.
        """
        super(MultilingualSentimentsConfig, self).__init__(
            version=datasets.Version("1.0.0"), **kwargs
        )
        self.features = features
        self.train_url = train_url
        self.valid_url = valid_url
        self.test_url = test_url


class MultilingualSentimentsConfig(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        MultilingualSentimentsConfig(
            name="en",
            description="English sentiment analysis dataset",
            features=["text", "label"],
            train_url="https://raw.githubusercontent.com/tyqiangz/multilingual-sentiment-datasets/main/en/train.tsv",
            valid_url="https://raw.githubusercontent.com/tyqiangz/multilingual-sentiment-datasets/main/en/val.tsv",
            test_url="https://raw.githubusercontent.com/tyqiangz/multilingual-sentiment-datasets/main/en/test.tsv",
            version=datasets.Version("0.0.0")
        ),
        MultilingualSentimentsConfig(
            name="id",
            description="Indonesian sentiment analysis dataset",
            features=["text", "label"],
            train_url="https://raw.githubusercontent.com/tyqiangz/multilingual-sentiment-datasets/main/id/train.tsv",
            valid_url="https://raw.githubusercontent.com/tyqiangz/multilingual-sentiment-datasets/main/id/val.tsv",
            test_url="https://raw.githubusercontent.com/tyqiangz/multilingual-sentiment-datasets/main/id/test.tsv"
            version=datasets.Version("0.0.0")
        )
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=self.config.description,
            features=datasets.Features({
                "text": datasets.Value("string"),
                "label": datasets.Value("string")
            })
        )

    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
        train_path = dl_manager.download_and_extract(self.config.train_url)
        valid_path = dl_manager.download_and_extract(self.config.valid_url)
        test_path = dl_manager.download_and_extract(self.config.test_url)

        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={
                                    "filepath": train_path}),
            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={
                                    "filepath": valid_path}),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={
                                    "filepath": test_path}),
        ]

    def _generate_examples(self, filepath):
        logging.info("generating examples from = %s", filepath)

        with open(filepath) as f:
            reader = csv.reader(f, delimiter="\t", quoting=csv.QUOTE_NONE)

            for id_, row in enumerate(reader):
                text, label = row
                yield id_, {"text": text, "label": label}