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# coding=utf-8
# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# Lint as: python3
"""Arabic Poetry Metric dataset."""
import os
import datasets
import pandas as pd
_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 AdawatConfig(datasets.BuilderConfig):
"""BuilderConfig for Masader."""
def __init__(self, **kwargs):
"""BuilderConfig for Adawat.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(AdawatConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
class Adawat(datasets.GeneratorBasedBuilder):
"""Adawatdataset."""
BUILDER_CONFIGS = [
AdawatConfig(
name="plain_text",
description="Plain text",
)
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
'Id': datasets.Value("string"),
'Name': datasets.Value("string"),
'Link': datasets.Value("string"),
'Colab link': datasets.Value("string"),
'GitHub Repo': datasets.Value("string"),
'Pricing': datasets.Value("string"),
'Accessibility': datasets.Value("string"),
'License': datasets.Value("string"),
'Version': datasets.Value("string"),
'Description': datasets.Value("string"),
'Paper Title': datasets.Value("string"),
'Paper URL': datasets.Value("string"),
'Release Year': datasets.Value("int32"),
'Tasks': datasets.Value("string"),
'Supported language(s)': datasets.Value("string"),
'Tool Type': datasets.Value("string"),
'Interface': datasets.Value("string"),
'Programming Language': datasets.Value("string"),
'Added by': datasets.Value("string"),
'Evaluated datasets': datasets.Value("string"),
}
),
supervised_keys=None,
homepage="https://github.com/arbml/Masader",
citation=_CITATION,)
def _split_generators(self, dl_manager):
sheet_id = "1uLqCbygNS9Pvsp1UkkR4Qe9SQrJVwpZDXzcpBfufmE8"
sheet_name = "main"
url = f"https://docs.google.com/spreadsheets/d/{sheet_id}/gviz/tq?tqx=out:csv&sheet={sheet_name}"
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN, gen_kwargs={"url":url }
),
]
def _generate_examples(self, url):
"""Generate examples."""
# For labeled examples, extract the label from the path.
df = pd.read_csv(url, usecols=range(22))
entry_list = []
i = 0
idx = 0
for i in range(len(df)):
masader_entry = {col.strip():df.values[i][j] for j,col in enumerate(df.columns) if j not in [18,20]}
yield i, masader_entry