amazon.py

import csv
import os

import datasets

logger = datasets.logging.get_logger(__name__)

_DESCRIPTION = """
"""

_URLS = {
    "clothing": "https://drive.google.com/u/0/uc?id=1HP3EPX9Q8JffUUZz2czXD7qudzvitscq&export=download",
    "electronics": "https://drive.google.com/u/0/uc?id=1W50FNd0707qK1CCktEF30nlDqsImLg3X&export=download",
    "office": "https://drive.google.com/u/0/uc?id=1lsttnBIjFD4nQw9idZYQNUWKSzj5VibD&export=download",
}

_FIELDS = ["date", "rating", "reviewText", "summary"]
_RATINGS = ["1", "2", "3", "4", "5"]


class AmazonConfig(datasets.BuilderConfig):
    def __init__(
        self,
        training_files,
        testing_files,
        url,
        label_classes=_RATINGS,
        **kwargs,
    ):
        super().__init__(version=datasets.Version("1.0.0", ""), **kwargs)
        self.label_classes = label_classes
        self.training_files = training_files
        self.testing_files = testing_files
        self.url = url


class Amazon(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        AmazonConfig(
            name="clothing_majorshift01",
            description="",
            url=_URLS["clothing"],
            training_files=[
                "201011.csv",
                "201012.csv",
                "201101.csv",
                "201102.csv",
                "201103.csv",
                "201104.csv",
                "201105.csv",
                "201106.csv",
                "201107.csv",
                "201108.csv",
                "201109.csv",
                "201110.csv",
                "201111.csv",
                "201112.csv",
                "201201.csv",
                "201202.csv",
                "201203.csv",
                "201204.csv",
                "201205.csv",
                "201206.csv",
                "201207.csv",
                "201208.csv",
                "201209.csv",
                "201210.csv",
            ],
            testing_files=[
                "201211.csv",
                "201212.csv",
                "201301.csv",
                "201302.csv",
                "201303.csv",
                "201304.csv",
            ],
        ),
        AmazonConfig(
            name="clothing_majorshift02",
            description="",
            url=_URLS["clothing"],
            training_files=[
                "200808.csv",
                "200809.csv",
                "200810.csv",
                "200811.csv",
                "200812.csv",
                "200901.csv",
                "200902.csv",
                "200903.csv",
                "200904.csv",
                "200905.csv",
                "200906.csv",
                "200907.csv",
                "200908.csv",
                "200909.csv",
                "200910.csv",
                "200911.csv",
                "200912.csv",
                "201001.csv",
                "201002.csv",
                "201003.csv",
                "201004.csv",
                "201005.csv",
                "201006.csv",
                "201007.csv",
            ],
            testing_files=[
                "201008.csv",
                "201009.csv",
                "201010.csv",
                "201011.csv",
                "201012.csv",
                "201101.csv",
            ],
        ),
        AmazonConfig(
            name="clothing_majorshift03",
            description="",
            url=_URLS["clothing"],
            training_files=[
                "201602.csv",
                "201603.csv",
                "201604.csv",
                "201605.csv",
                "201606.csv",
                "201607.csv",
                "201608.csv",
                "201609.csv",
                "201610.csv",
                "201611.csv",
                "201612.csv",
                "201701.csv",
                "201702.csv",
                "201703.csv",
                "201704.csv",
                "201705.csv",
                "201706.csv",
                "201707.csv",
                "201708.csv",
                "201709.csv",
                "201710.csv",
                "201711.csv",
                "201712.csv",
                "201801.csv",
            ],
            testing_files=[
                "201802.csv",
                "201803.csv",
                "201804.csv",
                "201805.csv",
                "201806.csv",
                "201807.csv",
            ],
        ),
    ]

    def _info(self):
        features = {
            "date": datasets.Value("string"),
            "id": datasets.Value("int32"),
            "label": datasets.features.ClassLabel(names=self.config.label_classes),
            "text": datasets.Value("string"),
        }
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(features),
        )

    def _split_generators(self, dl_manager):
        dirname = dl_manager.download_and_extract(self.config.url)
        logger.info(str(dirname))
        category = self.config.name.split("_")[
            0
        ]  # extract category name from the config
        train_filepaths = tuple(
            os.path.join(dirname, category, fname)
            for fname in self.config.training_files
        )
        test_filepaths = tuple(
            os.path.join(dirname, category, fname)
            for fname in self.config.testing_files
        )
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={"filepaths": train_filepaths},
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={"filepaths": test_filepaths},
            ),
        ]

    def _generate_examples(self, filepaths):
        logger.info(f"generating examples from {len(filepaths)} files")
        idx = 0
        for filepath in filepaths:
            with open(filepath, encoding="utf-8") as f:
                reader = csv.DictReader(f, fieldnames=_FIELDS)
                for row in reader:
                    yield idx, {
                        "date": row["date"],
                        "id": idx,
                        "label": row["rating"],
                        "text": row["reviewText"],
                    }
                    idx += 1