import os import re import datasets logger = datasets.logging.get_logger(__name__) _DESCRIPTION = """\ Common Crawl - Malayalam. """ _CITATION = """\ @article{qburst, title={Common Crawl - Malayalam}, author={n.d}, year={2020}, journal={n.d}, } """ _URLs = { "malayalam_wiki_2020": "https://huggingface.co/datasets/rajeshradhakrishnan/malayalam_2020_wiki/resolve/main/", "checksum_url": "https://huggingface.co/datasets/rajeshradhakrishnan/malayalam_2020_wiki/resolve/main/ml_sha256.txt" } class MalayalamWikiConfig(datasets.BuilderConfig): """BuilderConfig for MalayalamWiki.""" def __init__(self, **kwargs): """BuilderConfig for MalayalamWiki. Args: **kwargs: keyword arguments forwarded to super. """ super(MalayalamWikiConfig, self).__init__(**kwargs) class MalayalamWiki(datasets.GeneratorBasedBuilder): """Malayalam News topic classification dataset.""" VERSION = datasets.Version("1.0.0") BUILDER_CONFIGS = [ MalayalamWikiConfig( name="malayalam_wiki_2020", version=VERSION, description="Common Crawl - Malayalam." ), ] def remove_special_characters(self, txt): chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“\%\‘\”\�Utrnle\_]' unicode_ignore_regex = r'[\u200e\u200c\u200d]' english_ignore_regex = r'[a-zA-Z]' txt = txt.strip() txt = re.sub(chars_to_ignore_regex, '',txt) txt = re.sub(unicode_ignore_regex, '',txt) + " " txt = re.sub(english_ignore_regex, '',txt) + " " return txt def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "text": datasets.Value("string") } ), supervised_keys=None, homepage="https://github.com/qburst/common-crawl-malayalam", citation=_CITATION ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" checksum_url = _URLs["checksum_url"] checksum_file = dl_manager.download(checksum_url) with open(checksum_file, encoding="utf-8") as f: data_filenames = [line.strip() for line in f if line] data_urls = [_URLs["malayalam_wiki_2020"] + data_filename for data_filename in data_filenames[1:2]] downloaded_files = dl_manager.download(data_urls) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files}), ] def _generate_examples(self, filepaths): """This function returns the examples in the raw (text) form by iterating on all the files.""" for file_id,filepath in enumerate(filepaths): logger.info("generating examples from = %s", filepath) with open(filepath, encoding="utf-8") as f: for row_id, row in enumerate(f): yield f"{file_id}_{row_id}", {"text": self.remove_special_characters(row).strip()}