import datasets
from datasets.tasks import TaskTemplate
from sklearn.model_selection import train_test_split

_ORIGIN = "https://archive-beta.ics.uci.edu/dataset/17/breast+cancer+wisconsin+diagnostic"
_CITATION = """\
Wolberg,William, Street,W. & Mangasarian,Olvi. (1995). Breast Cancer Wisconsin (Diagnostic). UCI Machine Learning Repository. https://doi.org/10.24432/C5DW2B.
"""
_DESCRIPTION = """\
Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass.  They describe characteristics of the cell nuclei present in the image. A few of the images can be found at http://www.cs.wisc.edu/~street/images/
"""

class WisconsinBreastCancer(datasets.GeneratorBasedBuilder):
    def _info(self) -> datasets.DatasetInfo:
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            citation=_CITATION,
            homepage=_ORIGIN,
            license="",
        )
    

    def _split_generators(self, dl_manager):
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": "train.csv"}),
            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": "test.csv"}),
        ]
    
    def _generate_examples(self, filepath):
        with open(filepath, "r") as f:
            next(f)
            for key, row in enumerate(f):
                yield key, {"data": row[:-1], "label": row[-1]}