import os from pdb import set_trace import datasets import pandas as pd _CITATION = """\ Put your dataset citation here. """ _DESCRIPTION = """\ Description of your dataset goes here. """ _HOMEPAGE = "https://your-dataset-homepage.com" _LICENSE = "License information goes here." class Test(datasets.GeneratorBasedBuilder): """Your dataset description""" BUILDER_CONFIGS = [ datasets.BuilderConfig( name="customers", version=datasets.Version("1.0.0"), description="This is subset A"), datasets.BuilderConfig( name="products", version=datasets.Version("1.0.0"), description="This is subset B"), ] def _info(self): # set_trace() if self.config.name == "customers": features = datasets.Features( { "customer_id": datasets.Value("int64"), "name": datasets.Value("string"), "age": datasets.Value("int64"), } ) elif self.config.name == "products": features = datasets.Features( { "product_id": datasets.Value("int64"), "name": datasets.Value("string"), "price": datasets.Value("double"), } ) else: raise ValueError(f"Unknown subset: {self.config.name}") return datasets.DatasetInfo( description=_DESCRIPTION, features=features, supervised_keys=None, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, ) def _split_generators(self, dl_manager): data_dir = dl_manager.manual_dir or "./" data_dir = os.path.join(data_dir, self.config.name) print(data_dir) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(data_dir, "train.csv")}, ), datasets.SplitGenerator( name=datasets.Split.VALIDATION, gen_kwargs={"filepath": os.path.join(data_dir, "val.csv")}, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(data_dir, "test.csv")}, ), ] def _generate_examples(self, filepath): # set_trace() with open(filepath, encoding="utf-8") as f: df = pd.read_csv(filepath, index_col=0) for id_, item in df.iterrows(): yield id_, item.to_dict()