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"""E Corpus""" |
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import re |
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import datasets |
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_CITATION = """\ |
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@misc{E Dataset, |
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title={E Dataset}, |
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author={Jameson Quave}, |
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howpublished{\\url{https://huggingface.co/jquave}}, |
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year={2023} |
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} |
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""" |
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_DESCRIPTION = """\ |
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An open-source replication of E |
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""" |
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_N_DATA_FILES = 17 |
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_N_DATA_FILES = 1 |
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_DATA_FILES = ["ethereum_{:02d}.tar".format(i) for i in range(_N_DATA_FILES)] |
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print(_DATA_FILES) |
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class EDataset(datasets.GeneratorBasedBuilder): |
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"""The E dataset.""" |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name="plain_text", |
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description="Plain text", |
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version=datasets.Version("1.0.0"), |
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) |
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] |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features({"train": datasets.Value("string")}), |
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homepage="https://huggingface.co/jquave", |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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archives = dl_manager.download(_DATA_FILES) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={ |
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"archive_iterators": [ |
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dl_manager.iter_archive(archive) for archive in archives |
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], |
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"iter_archive": dl_manager.iter_archive |
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}), |
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] |
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def _generate_examples(self, archive_iterators, iter_archive): |
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"""Yields examples.""" |
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for archive_iterator in archive_iterators: |
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for code_path, code_f in archive_iterator: |
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if code_path.endswith(".sol.txt") or code_path.endswith(".sol"): |
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yield code_path, {"train": code_f.read().decode("utf-8").strip()} |