Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes

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README.md

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+---
+annotations_creators:
+- no-annotation
+language_creators:
+- found
+languages:
+- ar
+multilinguality:
+- monolingual
+size_categories:
+- n>1M
+source_datasets:
+- original
+task_categories:
+- other
+task_ids:
+- other-other-data-mining
+---
+
+# Dataset Card for ArCOV19
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [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)
+
+## Dataset Description
+
+- **Homepage:**  
+- **Repository:** https://gitlab.com/bigirqu/ArCOV-19
+- **Paper:** [ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks](https://arxiv.org/abs/2004.05861)
+- **Leaderboard:** [More Information Needed]
+- **Point of Contact:** [Fatima Haouari](mailto:200159617@qu.edu.qa)
+
+### Dataset Summary
+
+ArCOV-19 is an Arabic COVID-19 Twitter dataset that covers the period from 27th of January till 30th of April 2020. ArCOV-19 is the first publicly-available Arabic Twitter dataset covering COVID-19 pandemic that includes over 1M tweets alongside the propagation networks of the most-popular subset of them (i.e., most-retweeted and-liked). The propagation networks include both retweets and conversational threads (i.e., threads of replies). ArCOV-19 is designed to enable research under several domains including natural language processing, information retrieval, and social computing, among others. Preliminary analysis shows that ArCOV-19 captures rising discussions associated with the first reported cases of the disease as they appeared in the Arab world. In addition to the source tweets and the propagation networks, we also release the search queries and the language-independent crawler used to collect the tweets to encourage the curation of similar datasets.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+Arabic
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+tweet_id: the Twitter assigned ID for the tweet object.
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+The dataset collection approach is presented in the following paper: [ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks](https://arxiv.org/abs/2004.05861)
+### 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
+No annotation was provided with the dataset.
+
+#### Annotation process
+
+No annotation was provided with the dataset.
+
+#### Who are the annotators?
+
+No annotation was provided with the dataset.
+
+### 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
+
+**Team:** [bigIR](https://sites.google.com/view/bigir) from Qatar University ([@bigIR_group](https://twitter.com/bigIR_group))
+
+- [Fatima Haouari](mailto:200159617@qu.edu.qa)
+- [Maram Hasanain](mailto:maram.hasanain@qu.edu.qa)
+- [Reem Suwaileh](mailto:rs081123@qu.edu.qa)
+- [Dr. Tamer Elsayed](mailto:telsayed@qu.edu.qa)
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+@article{haouari2020arcov19,
+  title={ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks},
+  author={Fatima Haouari and Maram Hasanain and Reem Suwaileh and Tamer Elsayed},
+  journal={arXiv preprint arXiv:2004.05861},
+  year={2020}
+}

ar_cov19.py

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+# coding=utf-8
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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.
+"""TODO: Add a description here."""
+
+from __future__ import absolute_import, division, print_function
+
+import glob
+import os
+
+import pandas as pd
+
+import datasets
+
+
+# TODO: Add BibTeX citation
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """\
+@article{haouari2020arcov19,
+  title={ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks},
+  author={Fatima Haouari and Maram Hasanain and Reem Suwaileh and Tamer Elsayed},
+  journal={arXiv preprint arXiv:2004.05861},
+  year={2020}
+"""
+
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """\
+ArCOV-19 is an Arabic COVID-19 Twitter dataset that covers the period from 27th of January till 30th of April 2020. ArCOV-19 is designed to enable research under several domains including natural language processing, information retrieval, and social computing, among others
+"""
+
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = "https://gitlab.com/bigirqu/ArCOV-19"
+
+# TODO: Add the licence for the dataset here if you can find it
+# _LICENSE = ""
+
+# TODO: Add link to the official dataset URLs here
+# The HuggingFace dataset library don't host the datasets but only point to the original files
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_URL = "https://gitlab.com/bigirqu/ArCOV-19/-/archive/master/ArCOV-19-master.zip"
+# _URL="https://gitlab.com/bigirqu/ArCOV-19/-/archive/master/ArCOV-19-master.zip?path=dataset/all_tweets"
+
+
+class ArCov19Config(datasets.BuilderConfig):
+    """BuilderConfig for ArCOV19."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for ArCOV19.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(ArCov19Config, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+
+
+# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
+class ArCov19(datasets.GeneratorBasedBuilder):
+    """ArCOV-19 is an Arabic COVID-19 Twitter dataset that covers the period from 27th of January till 30th of April 2020. ArCOV-19 is designed to enable research under several domains including natural language processing, information retrieval, and social computing, among others"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    # This is an example of a dataset with multiple configurations.
+    # If you don't want/need to define several sub-sets in your dataset,
+    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
+
+    # If you need to make complex sub-parts in the datasets with configurable options
+    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
+    # BUILDER_CONFIG_CLASS = MyBuilderConfig
+
+    # You will be able to load one or the other configurations in the following list with
+    # data = datasets.load_dataset('my_dataset', 'first_domain')
+    # data = datasets.load_dataset('my_dataset', 'second_domain')
+    BUILDER_CONFIGS = [
+        ArCov19Config(
+            name="ar_cov19",
+            description="Plain text",
+        )
+    ]
+
+    def _info(self):
+
+        features = {}
+
+        features["tweetID"] = datasets.Value("int64")
+
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features=datasets.Features(
+                features
+            ),  # Here we define them above because they are different between the two configurations
+            # 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=_HOMEPAGE,
+            # License for the dataset if available
+            # license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
+        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
+        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
+        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
+        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
+        data_dir = dl_manager.download_and_extract(_URL)
+        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"data_dir": data_dir})]
+
+    def _generate_examples(self, data_dir):
+        """ Yields examples. """
+        # TODO: This method will receive as arguments the `gen_kwargs` defined in the previous `_split_generators` method.
+        # It is in charge of opening the given file and yielding (key, example) tuples from the dataset
+        # The key is not important, it's more here for legacy reason (legacy from tfds)
+        for fname in sorted(glob.glob(os.path.join(data_dir, "ArCOV-19-master/dataset/all_tweets/2020-*"))):
+
+            df = pd.read_csv(fname, names=["tweetID"])
+            for id_, record in df.iterrows():
+
+                tweetID = record["tweetID"]
+
+                yield str(id_), {"tweetID": tweetID}

dataset_infos.json

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+{"ar_cov19": {"description": "ArCOV-19 is an Arabic COVID-19 Twitter dataset that covers the period from 27th of January till 30th of April 2020. ArCOV-19 is designed to enable research under several domains including natural language processing, information retrieval, and social computing, among others\n", "citation": "@article{haouari2020arcov19,\n  title={ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks},\n  author={Fatima Haouari and Maram Hasanain and Reem Suwaileh and Tamer Elsayed},\n  journal={arXiv preprint arXiv:2004.05861},\n  year={2020}\n", "homepage": "https://gitlab.com/bigirqu/ArCOV-19", "license": "", "features": {"tweetID": {"dtype": "int64", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "ar_cov19", "config_name": "ar_cov19", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 8724728, "num_examples": 1090591, "dataset_name": "ar_cov19"}}, "download_checksums": {"https://gitlab.com/bigirqu/ArCOV-19/-/archive/master/ArCOV-19-master.zip": {"num_bytes": 54902390, "checksum": "96211408035f8082c072a5eb4fbccf28ef4de00379abfc9523c552ab84646579"}}, "download_size": 54902390, "post_processing_size": null, "dataset_size": 8724728, "size_in_bytes": 63627118}}

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