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import gzip |
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import json |
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from functools import partial |
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from pathlib import Path |
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import datasets |
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from datasets import DatasetDict, load_dataset |
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AVAILABLE_DATASETS = { |
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'main': 'https://amazon-berkeley-objects.s3.amazonaws.com/archives/abo-listings.tar' |
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} |
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VERSION = datasets.Version("0.0.1") |
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_FIELDS = [ |
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"item_id", |
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"brand", |
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"bullet_point", |
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"color", |
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"item_name", |
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"model_name", |
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"model_number", |
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"model_year", |
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"product_type", |
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"style", |
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"main_image_id", |
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"other_image_id", |
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"item_keywords", |
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"country", |
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"marketplace", |
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"domain_name", |
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"node", |
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] |
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class AbolistingsDataset(datasets.GeneratorBasedBuilder): |
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"""AbolistingsDataset dataset.""" |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name=data_name, version=VERSION, description=f"{data_name} abolistings dataset" |
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) |
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for data_name in AVAILABLE_DATASETS |
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] |
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@staticmethod |
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def load(data_name_config: str = "main") -> DatasetDict: |
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ds = load_dataset(__file__, data_name_config) |
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return ds |
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def _info(self): |
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return datasets.DatasetInfo( |
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description="", |
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features=datasets.Features( |
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{ |
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"item_id": datasets.Value("string"), |
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"brand": datasets.Sequence(datasets.Value("string")), |
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"bullet_point": datasets.Sequence(datasets.Value("string")), |
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"color": datasets.Sequence(datasets.Value("string")), |
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"item_name": datasets.Sequence(datasets.Value("string")), |
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"model_name": datasets.Sequence(datasets.Value("string")), |
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"model_number": datasets.Sequence(datasets.Value("string")), |
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"model_year": datasets.Sequence(datasets.Value("string")), |
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"product_type": datasets.Sequence(datasets.Value("string")), |
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"style": datasets.Sequence(datasets.Value("string")), |
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"main_image_id": datasets.Value("string"), |
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"other_image_id": datasets.Sequence(datasets.Value("string")), |
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"item_keywords": datasets.Sequence(datasets.Value("string")), |
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"country": datasets.Value("string"), |
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"marketplace": datasets.Value("string"), |
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"domain_name": datasets.Value("string"), |
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"node": datasets.Sequence(datasets.Value("string")), |
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} |
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), |
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supervised_keys=None, |
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homepage="https://amazon-berkeley-objects.s3.amazonaws.com/index.html#download", |
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citation="", |
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) |
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def _split_generators(self, dl_manager): |
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downloader = partial( |
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lambda: dl_manager.download_and_extract(AVAILABLE_DATASETS[self.config.name]) |
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) |
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root_path = Path(downloader()) / 'listings' / 'metadata' |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, gen_kwargs={"root_path": root_path} |
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), |
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] |
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def _generate_examples(self, root_path): |
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root_path = Path(root_path) |
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files = list(root_path.glob("*.json.gz")) |
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idx = 0 |
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for file in files: |
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with gzip.GzipFile(file) as f_in: |
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for l in f_in: |
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l = l.decode("utf-8") |
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sample = json.loads(l) |
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yield idx, {k: sample.get(k) for k in _FIELDS} |
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idx += 1 |
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