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README.md

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-
-# Dataset Card for [Dataset Name]
-
-## Table of Contents
-- [Table of Contents](#table-of-contents)
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:**
-- **Repository:**
-- **Paper:**
-- **Leaderboard:**
-- **Point of Contact:**
-
-### Dataset Summary
-
-The Ultimate Arabic News Dataset is a collection of single-label modern Arabic texts that are used in news websites and press articles.
-
-Arabic news data was collected by web scraping techniques from many famous news sites such as Al-Arabiya, Al-Youm Al-Sabea (Youm7), the news published on the Google search engine and other various sources.
-
-
-### Supported Tasks and Leaderboards
-
-[More Information Needed]
-
-### Languages
-
-[More Information Needed]
-
-## Dataset Structure
-
-### Data Instances
-
-[More Information Needed]
-
-### Data Fields
-
-[More Information Needed]
-
-### Data Splits
-
-[More Information Needed]
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed]
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-[More Information Needed]
-
-#### Who are the source language producers?
-
-[More Information Needed]
-
-### Annotations
-
-#### Annotation process
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-[More Information Needed]
-
-### Personal and Sensitive Information
-
-[More Information Needed]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed]
-
-### Discussion of Biases
-
-[More Information Needed]
-
-### Other Known Limitations
-
-[More Information Needed]
-
-## Additional Information
-
-### Dataset Curators
-
-[More Information Needed]
-
-### Licensing Information
-
-license: cc-by-4.0
-
-
-### Citation Information
-```
-@book{url,
-  author = {Al-Dulaimi, Ahmed Hashim},
-  year = {2022},
-  month = {05},
-  website = {Mendeley Data, V1},
-  title = {Ultimate Arabic News Dataset},
-  doi = {10.17632/jz56k5wxz7.1}
-}
-
-```
-
-### Contributions
-
-[More Information Needed]

UltimateArabic/ultimate_arabic_news-train-00000-of-00002.parquet

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UltimateArabicPrePros/ultimate_arabic_news-train.parquet

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ultimate_arabic_news.py

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-import csv
-import datasets
-import os
-import textwrap
-
-_DESCRIPTION = "  The Ultimate Arabic News Dataset is a collection of single-label modern Arabic texts that are used in news websites and press articles. Arabic news data was collected by web scraping techniques from many famous news sites such as Al-Arabiya, Al-Youm Al-Sabea (Youm7), the news published on the Google search engine and other various sources."
-
-_CITATION = "Al-Dulaimi, Ahmed Hashim (2022), “Ultimate Arabic News Dataset”, Mendeley Data, V1, doi: 10.17632/jz56k5wxz7.1"
-
-_HOMEPAGE = "https://data.mendeley.com/datasets/jz56k5wxz7/1"
-
-_LICENSE = "CC BY 4.0 "
-
-_URL = {"UltimateArabic":"https://data.mendeley.com/public-files/datasets/jz56k5wxz7/files/b7ca9d26-ed76-4481-bc61-cca9c90178a0/file_downloaded","UltimateArabicPrePros":"https://data.mendeley.com/public-files/datasets/jz56k5wxz7/files/a0bf3c0f-90a5-421f-874f-65e58bf2b977/file_downloaded"}
-        
-          
-class UAN_Config(datasets.BuilderConfig):
-
-    """BuilderConfig for Ultamte Arabic News"""
-
-    def __init__(self, **kwargs):
-        """
-        Args:
-            **kwargs: keyword arguments forwarded to super.
-        """
-        super(UAN_Config, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
-        
-
-class Ultimate_Arabic_News(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.1.0")
-    BUILDER_CONFIGS = [
-    UAN_Config(
-        name="UltimateArabic",
-        description=textwrap.dedent(
-            """\
-      UltimateArabic: A file containing more than 193,000 original Arabic news texts, without pre-processing. The texts contain words, 
-      numbers, and symbols that can be removed using pre-processing to increase accuracy when using the dataset in various Arabic natural 
-      language processing tasks such as text classification."""
-        ),
-    ),
-    UAN_Config(
-        name="UltimateArabicPrePros",
-        description=textwrap.dedent(
-            """UltimateArabicPrePros: It is a file that contains the data mentioned in the first file, but after pre-processing, where 
-            the number of data became about 188,000 text documents, where stop words, non-Arabic words, symbols and numbers have been 
-            removed so that this file is ready for use directly in the various Arabic natural language processing tasks. Like text 
-            classification.
-      """
-            ),
-        ),
-    ]
-
-    def _info(self):
-        # TODO(tydiqa): Specifies the datasets.DatasetInfo object
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # datasets.features.FeatureConnectors
-            features=datasets.Features(
-                {
-
-                    "text": datasets.Value("string"),
-                    "label": datasets.Value("string"),
-                },
-
-            ),
-            # If there's a common (input, target) tuple from the features,
-            # specify them here. They'll be used if as_supervised=True in
-            # builder.as_dataset.
-            supervised_keys=None,
-            # Homepage of the dataset for documentation
-            homepage="https://data.mendeley.com/datasets/jz56k5wxz7/1",
-            citation=_CITATION,
-        )
-
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(tydiqa): Downloads the data and defines the splits
-        # dl_manager is a datasets.download.DownloadManager that can be used to
-        # download and extract URLs
-        UltAr_downloaded = dl_manager.download_and_extract(_URL['UltimateArabic'])
-        UltArPre_downloaded = dl_manager.download_and_extract(_URL['UltimateArabicPrePros'])
-        if self.config.name == "UltimateArabic":
-            return [
-                datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN,
-                    # These kwargs will be passed to _generate_examples
-                    gen_kwargs={"csv_file": UltAr_downloaded},
-                ),
-            ]
-        elif self.config.name == "UltimateArabicPrePros":
-            return [
-                datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN,
-                    # These kwargs will be passed to _generate_examples
-                    gen_kwargs={"csv_file": UltArPre_downloaded},
-                ),
-
-            ]
-            
-    def _generate_examples(self, csv_file):
-        with open(csv_file, encoding="utf-8") as f:
-            data =  csv.DictReader(f)
-            for row, item in enumerate(data):
-                yield row, {"text": item['text'],"label": item['label']}
-        
-