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"""Indonesian Newspapers 2018""" |
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import glob |
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import json |
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import os |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_CITATION = """\ |
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@inproceedings{id_newspapers_2018, |
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author = {}, |
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title = {Indonesian Newspapers 2018}, |
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year = {2019}, |
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url = {https://github.com/feryandi/Dataset-Artikel}, |
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} |
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""" |
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_DESCRIPTION = """\ |
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The dataset contains around 500K articles (136M of words) from 7 Indonesian newspapers: Detik, Kompas, Tempo, |
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CNN Indonesia, Sindo, Republika and Poskota. The articles are dated between 1st January 2018 and 20th August 2018 |
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(with few exceptions dated earlier). The size of uncompressed 500K json files (newspapers-json.tgz) is around 2.2GB, |
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and the cleaned uncompressed in a big text file (newspapers.txt.gz) is about 1GB. The original source in Google Drive |
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contains also a dataset in html format which include raw data (pictures, css, javascript, ...) |
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from the online news website |
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""" |
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_HOMEPAGE = "https://github.com/feryandi/Dataset-Artikel" |
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_LICENSE = "Creative Commons Attribution-ShareAlike 4.0 International Public License" |
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_URLs = ["http://cloud.uncool.ai/index.php/s/kF83dQHfGeS2LX2/download"] |
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class IdNewspapers2018Config(datasets.BuilderConfig): |
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"""BuilderConfig for IdNewspapers2018""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig for IdNewspapers2018. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(IdNewspapers2018Config, self).__init__(**kwargs) |
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class IdNewspapers2018(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("1.0.0") |
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BUILDER_CONFIGS = [ |
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IdNewspapers2018Config( |
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name="id_newspapers_2018", |
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version=VERSION, |
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description="IdNewspapers2018 dataset", |
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), |
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] |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"url": datasets.Value("string"), |
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"date": datasets.Value("string"), |
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"title": datasets.Value("string"), |
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"content": datasets.Value("string"), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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my_urls = _URLs[0] |
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data_dir = dl_manager.download_and_extract(my_urls) |
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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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"article_dir": os.path.join(data_dir, "newspapers"), |
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"split": "train", |
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}, |
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) |
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] |
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def _generate_examples(self, article_dir, split): |
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logger.info("⏳ Generating %s examples from = %s", split, article_dir) |
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id = 0 |
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for path in sorted(glob.glob(os.path.join(article_dir, "**/*.json"), recursive=True)): |
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with open(path, encoding="utf-8") as f: |
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data = json.load(f) |
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yield id, { |
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"id": str(id), |
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"url": data["url"], |
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"date": data["date"], |
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"title": data["title"], |
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"content": data["content"], |
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} |
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id += 1 |
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