import datasets

_CITATION = """\
@InProceedings{huggingface:dataset,
title = {Unsplash 25K Photos},
author={James Briggs},
year={2022}
}
"""

_DESCRIPTION = """\
This is a dataset that streams photos data from the Unsplash 25K servers.
"""
_HOMEPAGE = "https://github.com/unsplash/datasets/"

_LICENSE = ""

_URL = "https://unsplash.com/data/lite/latest"

class Unsplash(datasets.GeneratorBasedBuilder):
    """The Unsplash 25K dataset for photos"""

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "imdb_id": datasets.Value("string"),
                    "movie_id": datasets.Value("int32"),
                    "user_id": datasets.Value("int32"),
                    "rating": datasets.Value("float32"),
                    "title": datasets.Value("string"),
                    "year": datasets.Value("int32"),
                }
            ),
            supervised_keys=None,
            homepage="https://grouplens.org/datasets/movielens/",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        new_url = dl_manager.download_and_extract(_URL)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={"filepath": new_url+"/photos.tsv000"}
            ),
        ]

    def _generate_examples(self, filepath):
        """This function returns the examples in the raw (text) form."""
        with open(filepath, "r") as f:
            id_ = 0
            for line in f:
                if id_ == 0:
                    cols = line.split("\t")
                    id_ += 1
                else:
                    values = line.split("\t")
                    print(id_, {cols[i]: values[i] for i in range(len(cols))})
                    id_ += 1
                if id_ > 5: break