| import csv | |
| import datasets | |
| class GenericCSVLoader(datasets.GeneratorBasedBuilder): | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description="Generic CSV loader script for Hugging Face Datasets.", | |
| features=datasets.Features({ | |
| "RequestID": datasets.Value("string"), | |
| "Boro": datasets.Value("string"), | |
| "Yr": datasets.Value("string"), | |
| "M": datasets.Value("string"), | |
| "D": datasets.Value("string"), | |
| "HH": datasets.Value("string"), | |
| "MM": datasets.Value("string"), | |
| "Vol": datasets.Value("string"), | |
| "SegmentID": datasets.Value("string"), | |
| "WktGeom": datasets.Value("string"), | |
| "street": datasets.Value("string"), | |
| "fromSt": datasets.Value("string"), | |
| "toSt": datasets.Value("string"), | |
| "Direction": datasets.Value("string") | |
| }), | |
| supervised_keys=None, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| data_path = dl_manager.download_and_extract("sample_traffic.csv") | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_path}) | |
| ] | |
| def _generate_examples(self, filepath): | |
| with open(filepath, newline="", encoding="utf-8") as f: | |
| reader = csv.DictReader(f) | |
| for i, row in enumerate(reader): | |
| yield i, row | |