import csv
import datasets
import numpy as np

_HOMEPAGE = 'http://yann.lecun.com/exdb/mnist/'
_LICENSE = '-'
_DESCRIPTION = '''\
The MNIST database of handwritten digits, available from this page, has a training set of 60,000 examples, and a test set of 10,000 examples.
It is a subset of a larger set available from NIST.
The digits have been size-normalized and centered in a fixed-size image.
'''
_CITATION = '''-'''
_NAMES = list('0123456789')


class MNISTConfig(datasets.BuilderConfig):
    '''Builder Config for MNIST'''

    def __init__(
        self, description, homepage, **kwargs
    ):
        super(MNISTConfig, self).__init__(
            version=datasets.Version('1.0.0', ''),
            **kwargs
        )
        self.description = description
        self.homepage = homepage
        self.train_image_url = 'data/train.csv'
        self.test_image_url = 'data/test.csv'


class MNIST(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        MNISTConfig(
            description=_DESCRIPTION,
            homepage=_HOMEPAGE
        )
    ]

    def _info(self):
        features = datasets.Features({
            'image': datasets.Image(mode='L', decode=True, id=None),
            'label': datasets.ClassLabel(names=_NAMES)
        })
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION
        )

    def _split_generators(self, dl_manager):
        train_image_path = dl_manager.download(
            self.config.train_image_url
        )
        test_image_path = dl_manager.download(
            self.config.test_image_url
        )
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    'data_path': f'{train_image_path}'
                }
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    'data_path': f'{test_image_path}'
                }
            )
        ]

    def _generate_examples(self, data_path):
        idx = 0
        with open(data_path, newline='', encoding='utf-8') as csvfile:
            csvreader = csv.reader(csvfile)
            next(csvreader)
            for row in csvreader:
                example = {
                    'image': np.array(row[1:], np.uint8).reshape(28, 28),
                    'label': row[0]
                }
                yield idx, example
                idx += 1