import datasets
import pandas as pd

_CITATION = """\
@InProceedings{huggingface:dataset,
title = {spam-text-messages-dataset},
author = {TrainingDataPro},
year = {2023}
}
"""

_DESCRIPTION = """\
The SMS spam dataset contains a collection of text messages. The dataset
includes a diverse range of spam messages, including promotional offers,
fraudulent schemes, phishing attempts, and other forms of unsolicited
communication.
Each SMS message is represented as a string of text, and each entry in the
dataset also has a link to the corresponding screenshot. The dataset's content
represents real-life examples of spam messages that users encounter in their
everyday communication.
"""
_NAME = 'spam-text-messages-dataset'

_HOMEPAGE = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}"

_LICENSE = ""

_DATA = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}/resolve/main/data/"


class SpamTextMessagesDataset(datasets.GeneratorBasedBuilder):
    """Small sample of image-text pairs"""

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features({
                'image': datasets.Image(),
                'text': datasets.Value('string')
            }),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        images = dl_manager.download(f"{_DATA}images.tar.gz")
        annotations = dl_manager.download(f"{_DATA}{_NAME}.csv")
        images = dl_manager.iter_archive(images)
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN,
                                    gen_kwargs={
                                        "images": images,
                                        'annotations': annotations
                                    }),
        ]

    def _generate_examples(self, images, annotations):
        annotations_df = pd.read_csv(annotations, sep=';')

        for idx, (image_path, image) in enumerate(images):
            yield idx, {
                "image": {
                    "path": image_path,
                    "bytes": image.read()
                },
                'text':
                    annotations_df.loc[annotations_df['image'].str.lower() ==
                                       image_path.lower()]['text'].values[0]
            }