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"""TTC4900: A Benchmark Data for Turkish Text Categorization""" |
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from __future__ import absolute_import, division, print_function |
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import csv |
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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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_DESCRIPTION = """\ |
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The data set is taken from kemik group |
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http://www.kemik.yildiz.edu.tr/ |
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The data are pre-processed for the text categorization, collocations are found, character set is corrected, and so forth. |
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We named TTC4900 by mimicking the name convention of TTC 3600 dataset shared by the study http://journals.sagepub.com/doi/abs/10.1177/0165551515620551 |
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""" |
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_CITATION = "" |
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_LICENSE = "CC0: Public Domain" |
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_HOMEPAGE = "https://www.kaggle.com/savasy/ttc4900" |
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_FILENAME = "7allV03.csv" |
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class TTC4900Config(datasets.BuilderConfig): |
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"""BuilderConfig for TTC4900""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig for TTC4900. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(TTC4900Config, self).__init__(**kwargs) |
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class TTC4900(datasets.GeneratorBasedBuilder): |
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"""TTC4900: A Benchmark Data for Turkish Text Categorization""" |
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BUILDER_CONFIGS = [ |
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TTC4900Config( |
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name="ttc4900", |
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version=datasets.Version("1.0.0"), |
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description="A Benchmark Data for Turkish Text Categorization", |
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), |
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] |
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@property |
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def manual_download_instructions(self): |
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return """\ |
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You need to go to https://www.kaggle.com/savasy/ttc4900, |
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and manually download the ttc4900. Once it is completed, |
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a file named archive.zip will be appeared in your Downloads folder |
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or whichever folder your browser chooses to save files to. You then have |
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to unzip the file and move 7allV03.csv under <path/to/folder>. |
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The <path/to/folder> can e.g. be "~/manual_data". |
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ttc4900 can then be loaded using the following command `datasets.load_dataset("ttc4900", data_dir="<path/to/folder>")`. |
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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( |
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{ |
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"category": datasets.features.ClassLabel( |
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names=["siyaset", "dunya", "ekonomi", "kultur", "saglik", "spor", "teknoloji"] |
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), |
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"text": datasets.Value("string"), |
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} |
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), |
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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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"""Returns SplitGenerators.""" |
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path_to_manual_file = os.path.abspath(os.path.expanduser(dl_manager.manual_dir)) |
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if not os.path.exists(path_to_manual_file): |
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raise FileNotFoundError( |
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"{} does not exist. Make sure you insert a manual dir via `datasets.load_dataset('ttc4900', data_dir=...)` that includes a file name {}. Manual download instructions: {})".format( |
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path_to_manual_file, _FILENAME, self.manual_download_instructions |
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) |
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) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(path_to_manual_file, _FILENAME)} |
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) |
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] |
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def _generate_examples(self, filepath): |
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"""Generate TTC4900 examples.""" |
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logger.info("⏳ Generating examples from = %s", filepath) |
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with open(filepath, encoding="utf-8") as f: |
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rdr = csv.reader(f, delimiter=",") |
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next(rdr) |
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rownum = 0 |
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for row in rdr: |
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rownum += 1 |
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yield rownum, { |
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"category": row[0], |
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"text": row[1], |
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} |
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