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import json
import datasets
_AMAZON_REVIEW_2023_DESCRIPTION = """\
Amazon Review 2023 is an updated version of the Amazon Review 2018 dataset.
This dataset mainly includes reviews (ratings, text) and item metadata (desc-
riptions, category information, price, brand, and images). Compared to the pre-
vious versions, the 2023 version features larger size, newer reviews (up to Sep
2023), richer and cleaner meta data, and finer-grained timestamps (from day to
milli-second).
"""
class RawMetaAmazonReview2023Config(datasets.BuilderConfig):
def __init__(self, **kwargs):
super(RawMetaAmazonReview2023Config, self).__init__(**kwargs)
self.suffix = 'jsonl'
self.domain = self.name[len(f'raw_meta_'):]
self.description = f'This is a subset for items in domain: {self.domain}.'
self.data_dir = f'raw/meta_categories/meta_{self.domain}.jsonl'
class AmazonReview2023(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
# Raw item metadata
RawMetaAmazonReview2023Config(name='raw_meta_All_Beauty'),
RawMetaAmazonReview2023Config(name='raw_meta_Toys_and_Games'),
RawMetaAmazonReview2023Config(name='raw_meta_Cell_Phones_and_Accessories'),
RawMetaAmazonReview2023Config(name='raw_meta_Industrial_and_Scientific'),
RawMetaAmazonReview2023Config(name='raw_meta_Gift_Cards'),
RawMetaAmazonReview2023Config(name='raw_meta_Musical_Instruments'),
RawMetaAmazonReview2023Config(name='raw_meta_Electronics'),
RawMetaAmazonReview2023Config(name='raw_meta_Handmade_Products'),
RawMetaAmazonReview2023Config(name='raw_meta_Arts_Crafts_and_Sewing'),
RawMetaAmazonReview2023Config(name='raw_meta_Baby_Products'),
RawMetaAmazonReview2023Config(name='raw_meta_Health_and_Household'),
RawMetaAmazonReview2023Config(name='raw_meta_Office_Products'),
RawMetaAmazonReview2023Config(name='raw_meta_Digital_Music'),
RawMetaAmazonReview2023Config(name='raw_meta_Grocery_and_Gourmet_Food'),
RawMetaAmazonReview2023Config(name='raw_meta_Sports_and_Outdoors'),
RawMetaAmazonReview2023Config(name='raw_meta_Home_and_Kitchen'),
RawMetaAmazonReview2023Config(name='raw_meta_Subscription_Boxes'),
RawMetaAmazonReview2023Config(name='raw_meta_Tools_and_Home_Improvement'),
RawMetaAmazonReview2023Config(name='raw_meta_Pet_Supplies'),
RawMetaAmazonReview2023Config(name='raw_meta_Video_Games'),
RawMetaAmazonReview2023Config(name='raw_meta_Kindle_Store'),
RawMetaAmazonReview2023Config(name='raw_meta_Clothing_Shoes_and_Jewelry'),
RawMetaAmazonReview2023Config(name='raw_meta_Patio_Lawn_and_Garden'),
RawMetaAmazonReview2023Config(name='raw_meta_Unknown'),
RawMetaAmazonReview2023Config(name='raw_meta_Books'),
RawMetaAmazonReview2023Config(name='raw_meta_Automotive'),
RawMetaAmazonReview2023Config(name='raw_meta_CDs_and_Vinyl'),
RawMetaAmazonReview2023Config(name='raw_meta_Beauty_and_Personal_Care'),
RawMetaAmazonReview2023Config(name='raw_meta_Amazon_Fashion'),
RawMetaAmazonReview2023Config(name='raw_meta_Magazine_Subscriptions'),
RawMetaAmazonReview2023Config(name='raw_meta_Software'),
RawMetaAmazonReview2023Config(name='raw_meta_Health_and_Personal_Care'),
RawMetaAmazonReview2023Config(name='raw_meta_Appliances'),
RawMetaAmazonReview2023Config(name='raw_meta_Movies_and_TV'),
]
def _info(self):
return datasets.DatasetInfo(
description=_AMAZON_REVIEW_2023_DESCRIPTION + self.config.description
)
def _split_generators(self, dl_manager):
dl_dir = dl_manager.download_and_extract(self.config.data_dir)
return [
datasets.SplitGenerator(
name='full',
gen_kwargs={"filepath": dl_dir}
)
]
def _generate_examples(self, filepath):
with open(filepath, 'r', encoding='utf-8') as file:
for idx, line in enumerate(file):
if self.config.suffix == 'jsonl':
try:
dp = json.loads(line)
"""
For item metadata, 'details' is free-form structured data
Here we dump it to string to make huggingface datasets easy
to store.
"""
if isinstance(self.config, RawMetaAmazonReview2023Config):
if 'details' in dp:
dp['details'] = json.dumps(dp['details'])
if 'price' in dp:
dp['price'] = str(dp['price'])
except:
continue
else:
raise ValueError(f'Unknown suffix {self.config.suffix}.')
yield idx, dp
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