masader.py

# 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.
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# 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}
      }
"""

columns = ['No.', 'Name', 'Subsets', 'Link', 'License', 'Year', 'Language',
       'Dialect', 'Domain', 'Form', 'Collection Style', 'Description',
       'Volume', 'Unit', 'Ethical Risks', 'Provider', 'Derived From',
       'Paper Title', 'Paper Link', 'Script', 'Tokenized', 'Host', 'Access',
       'Cost', 'Test Split']

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(
                {
                    columns[i]: datasets.Value("string") for i in range(len(columns))
                }
            ),
            supervised_keys=None,
            homepage="https://github.com/arbml/Masader",
            citation=_CITATION,)

    def _split_generators(self, dl_manager):
        sheet_id = "1YO-Vl4DO-lnp8sQpFlcX1cDtzxFoVkCmU1PVw_ZHJDg"
        sheet_name = "filtered_clean"
        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(34))
        subsets = {}
        entry_list = []
        i = 0
        idx = 0
         
        while i < len(df.values) - 1:
            
            next_entry = df.values[i+1]
            curr_entry = df.values[i]
            
            i+= 1
            if str(curr_entry[0]) != "nan":
                entry_list = curr_entry
                
            if str(next_entry[0]) == "nan":
                subsets[next_entry[2]] = {'Dialect':next_entry[7], 'Volume':next_entry[12], 'Unit':next_entry[13]}
                continue                
            idx += 1
            masader_entry = {col:entry_list[j] for j,col in enumerate(columns) if j != 2}
            masader_entry['Subsets'] = subsets
            subsets = {}

            yield idx, masader_entry