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"""Public domain texts from Project Ben-Yehuda- a set of books extracted from the Project BenYehuda library""" |
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import csv |
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csv.field_size_limit(1000000000) |
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from pathlib import Path |
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import datasets |
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import logging |
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_CITATION = """\ |
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@article{, |
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author = {}, |
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title = {Public domain texts from Project Ben-Yehuda}, |
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journal = {}, |
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url = {https://github.com/projectbenyehuda/public_domain_dump}, |
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year = {2020}, |
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} |
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""" |
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_DESCRIPTION = """\ |
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This repository contains a dump of thousands of public domain works in Hebrew, from Project Ben-Yehuda, in plaintext UTF-8 files, with and without diacritics (nikkud). The metadata (pseudocatalogue.csv) file is a list of titles, authors, genres, and file paths, to help you process the dump. |
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All these works are in the public domain, so you are free to make any use of them, and do not need to ask for permission. |
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There are 10078 files, 3181136 lines |
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""" |
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logger = logging.getLogger(__name__) |
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URLS = dict( |
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html="https://github.com/projectbenyehuda/public_domain_dump/releases/download/2022-12/html.zip", |
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catalogue="https://github.com/projectbenyehuda/public_domain_dump/releases/download/2022-12/pseudocatalogue.csv", |
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txt="https://github.com/projectbenyehuda/public_domain_dump/releases/download/2022-12/txt.zip", |
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txt_stripped="https://github.com/projectbenyehuda/public_domain_dump/releases/download/2022-12/txt_stripped.zip", |
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) |
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class HebrewProjectbenyehuda(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("0.2.0") |
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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( |
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{ |
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"id": datasets.Value("int32"), |
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"path": datasets.Value("string"), |
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"title": datasets.Value("string"), |
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"authors": datasets.Value("string"), |
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"translators": datasets.Value("string"), |
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"original_language": datasets.Value("string"), |
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"genre": datasets.Value("string"), |
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"source_edition": datasets.Value("string"), |
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"text": datasets.Value("string"), |
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"txt_stripped": datasets.Value("string"), |
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"html": datasets.Value("string"), |
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} |
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), |
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supervised_keys=None, |
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homepage="https://github.com/projectbenyehuda/public_domain_dump", |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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paths = {} |
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for key, url in URLS.items(): |
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logger.info("Downloading %s", url) |
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paths[key] = dl_manager.download_and_extract(url) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepaths": paths, |
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}, |
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) |
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] |
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def _generate_examples(self, filepaths): |
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catalogue_path = filepaths["catalogue"] |
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html_path = Path(filepaths["html"]) / "html" |
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txt_path = Path(filepaths["txt"]) / "txt" |
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txt_stripped_path = Path(filepaths["txt_stripped"]) / "txt_stripped" |
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with open(catalogue_path, encoding="utf-8") as f: |
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metadata_dict = csv.DictReader( |
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f, |
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fieldnames=[ |
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"_id", |
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"path", |
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"title", |
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"authors", |
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"translators", |
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"original_language", |
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"genre", |
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"source_edition", |
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], |
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) |
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for data in metadata_dict: |
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if data["path"] == "path": |
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continue |
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yield data["_id"], { |
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"id": data["_id"], |
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"title": data["title"], |
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"path": data["path"], |
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"authors": data["authors"], |
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"translators": data["translators"], |
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"original_language": data["original_language"], |
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"genre": data["genre"], |
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"source_edition": data["source_edition"], |
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"text": self.read_file(txt_path / f"{data['path'].strip('/')}.txt"), |
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"txt_stripped": self.read_file( |
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txt_stripped_path / f"{data['path'].strip('/')}.txt" |
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), |
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"html": self.read_file(html_path / f"{data['path'].strip('/')}.html"), |
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} |
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def read_file(self, filepath): |
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filepath = Path(filepath) |
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if filepath.exists(): |
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with open(filepath, encoding="utf-8") as f: |
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return f.read() |
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else: |
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return None |
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