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import datasets
import json
class HfreviewsConfig(datasets.BuilderConfig):
def __init__(self, features, **kwargs):
super(HfreviewsConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
self.features = features
class MedicalInstitutionsReviews(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
HfreviewsConfig(
name="simple",
description="Simple config",
features=["review_id", "content", "general", "quality", "service", "equipment", "food", "location"],
)
]
def _info(self):
return datasets.DatasetInfo(
description='Healthcare facilities reviews dataset.',
features=datasets.Features(
{
"review_id": datasets.Value("string"),
"content": datasets.Value("string"),
"general": datasets.Value("string"),
"quality": datasets.Value("string"),
"service": datasets.Value("string"),
"equipment": datasets.Value("string"),
"food": datasets.Value("string"),
"location": datasets.Value("string"),
"Idx": datasets.Value("int32"),
}
),
)
def _split_generators(self, dl_manager: datasets.DownloadManager):
urls_to_download = {
"train": "medical_institutions_reviews.jsonl"
}
downloaded_files = dl_manager.download_and_extract(urls_to_download)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]})
]
def _generate_examples(self, filepath):
"""Yields examples."""
with open(filepath, encoding="utf-8") as f:
for uid, row in enumerate(f):
data = json.loads(row)
data["Idx"] = uid
yield uid, data
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