import datasets
import csv
import os
import sys
csv.field_size_limit(sys.maxsize)

_DESCRIPTION = """persian_blog is a dataset consist of 400K blog posts from various websites and has types of tones.
this dataset can be used in different NLG tasks and as a show-case it's is used in training reformer-persian."""
_PROJECT_URL = """"""


_CITATION = """
https://saied71.github.io/RohanAiLab/,
  author={Saied Alimoradi},
  year={2021}
}
"""

train = "sample_train.zip"
test = "sample_test.zip"

class persian_blog_V2(datasets.GeneratorBasedBuilder):

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": datasets.Value("string")
                }
            ),
            homepage=_PROJECT_URL,
            citation=_CITATION,
        )



    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        dl_train = dl_manager.download_and_extract(train)
        dl_test = dl_manager.download_and_extract(test)
        train_dir = os.path.join(dl_train, "sample_train.csv")
        test_dir = os.path.join(dl_test, "sample_test.csv")
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_dir}),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_dir}),
        ]

    def _generate_examples(self, filepath):
        """Yields examples."""
        with open(filepath, encoding="utf-8") as f:
            reader = csv.reader(f)
            for id_, row in enumerate(reader):
                if id_ == 0:
                    continue
                yield id_, {
                    "text": row[0]
                }