Create arabic-tweets.py

arabic-tweets.py

@@ -0,0 +1,103 @@
+# 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.
+
+import csv
+import json
+import os
+
+import datasets
+
+
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """\
+@INPROCEEDINGS{10022652,
+  author={Al-Fetyani, Mohammad and Al-Barham, Muhammad and Abandah, Gheith and Alsharkawi, Adham and Dawas, Maha},
+  booktitle={2022 IEEE Spoken Language Technology Workshop (SLT)}, 
+  title={MASC: Massive Arabic Speech Corpus}, 
+  year={2023},
+  volume={},
+  number={},
+  pages={1006-1013},
+  doi={10.1109/SLT54892.2023.10022652}}
+"""
+
+# You can copy an official description
+_DESCRIPTION = """\
+This dataset has been collected from twitter which is more than 41 GB of clean data of Arabic Tweets with nearly 4-billion Arabic words (12-million unique Arabic words).
+"""
+
+_HOMEPAGE = "https://ieee-dataport.org/open-access/masc-massive-arabic-speech-corpus"
+
+_LICENSE = "https://creativecommons.org/licenses/by/4.0/"
+
+# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_URLS = {
+    "train": "https://huggingface.co/datasets/pain/Arabic-Tweets/blob/main/lm_twitter.txt",
+}
+
+
+# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
+class arabic_tweets(datasets.GeneratorBasedBuilder):
+    """This dataset has been collected from twitter which is more than 41 GB of clean data of Arabic Tweets with nearly 4-billion Arabic words (12-million unique Arabic words)."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+
+        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(
+                {
+                    "text": datasets.Value("string")
+                }
+            ),  # Here we define them above because they are different between the two configurations
+            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
+            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
+            # supervised_keys=("sentence", "label"),
+            # 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):
+
+        urls = _URLS["train"]
+        data_dir = dl_manager.download_and_extract(urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir),
+                    "split": "train",
+                },
+            ),
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, filepath, split):
+
+            """Yields examples."""
+            with open(filepath, encoding="utf-8") as f:
+                for idx, row in enumerate(f):
+                    if row.strip():
+                        yield idx, {"text": row}
+                    else:
+                        yield idx, {"text": ""}