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import datasets
from glob import glob
import json
import zipfile
from random import shuffle
_DESCRIPTION = """\
Masader is the largest public catalogue for Arabic NLP datasets, which consists of more than 200 datasets annotated with 25 attributes.
"""
_CITATION = """\
@misc{alyafeai2021masader,
title={Masader: Metadata Sourcing for Arabic Text and Speech Data Resources},
author={Zaid Alyafeai and Maraim Masoud and Mustafa Ghaleb and Maged S. Al-shaibani},
year={2021},
eprint={2110.06744},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
"""
class MasaderConfig(datasets.BuilderConfig):
"""BuilderConfig for Masader."""
def __init__(self, **kwargs):
"""BuilderConfig for MetRec.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(MasaderConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
class Masader(datasets.GeneratorBasedBuilder):
"""Masaderdataset."""
BUILDER_CONFIGS = [
MasaderConfig(
name="plain_text",
description="Plain text",
)
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
'Name': datasets.Value("string"),
'Subsets': [{'Name':datasets.Value("string"),
'Dialect':datasets.Value("string") ,
'Volume':datasets.Value("string") ,
'Unit':datasets.Value("string")}],
'HF Link': datasets.Value("string"),
'Link': datasets.Value("string"),
'License': datasets.Value("string"),
'Year': datasets.Value("int32"),
'Language': datasets.Value("string"),
'Dialect': datasets.Value("string"),
'Domain': datasets.Value("string"),
'Form': datasets.Value("string"),
'Collection Style': datasets.Value("string"),
'Description': datasets.Value("string"),
'Volume': datasets.Value("string"),
'Unit': datasets.Value("string"),
'Ethical Risks': datasets.Value("string"),
'Provider': datasets.Value("string"),
'Derived From': datasets.Value("string"),
'Paper Title': datasets.Value("string"),
'Paper Link': datasets.Value("string"),
'Script': datasets.Value("string"),
'Tokenized': datasets.Value("string"),
'Host': datasets.Value("string"),
'Access': datasets.Value("string"),
'Cost': datasets.Value("string"),
'Test Split': datasets.Value("string"),
'Tasks': datasets.Value("string"),
'Venue Title': datasets.Value("string"),
'Citations': datasets.Value("string"),
'Venue Type': datasets.Value("string"),
'Venue Name': datasets.Value("string"),
'Authors': datasets.Value("string"),
'Affiliations': datasets.Value("string"),
'Abstract': datasets.Value("string"),
'Added By': datasets.Value("string"),
}
),
supervised_keys=None,
homepage="https://github.com/arbml/Masader",
citation=_CITATION,)
def extract_all(self, dir):
zip_files = glob(dir+'/**/**.zip', recursive=True)
for file in zip_files:
with zipfile.ZipFile(file) as item:
item.extractall('/'.join(file.split('/')[:-1]))
def _split_generators(self, dl_manager):
url = ['https://github.com/ARBML/masader/archive/main.zip']
downloaded_files = dl_manager.download_and_extract(url)
self.extract_all(downloaded_files[0])
all_files = sorted(glob(downloaded_files[0]+'/masader-main/datasets/**.json'))
shuffle(all_files)
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'filepaths':{'inputs':all_files} })]
def _generate_examples(self, filepaths):
for idx,filepath in enumerate(filepaths['inputs']):
with open(filepath, 'r') as f:
data = json.load(f)
yield idx, data |