adding sample data and sample script

clean.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:55c23af1eb25af74456b5ea2fe05422431bb5172dd7680efd57e0a9b81a228a1
+size 16004

tasnim_daily.py

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+import datasets
+import csv
+import os
+import sys
+csv.field_size_limit(sys.maxsize)
+
+_DESCRIPTION = """
+persian_news_dataset is a collection of 5 million news articles. 
+News articles have been gathered from more than 10 news agencies for the last 12 years. 
+The dataset is provided by Rohan AI lab for research purposes.
+for more information refer to this link:
+"""
+_PROJECT_URL = """"""
+
+
+_CITATION = """
+https://saied71.github.io/RohanAiLab/,
+  author={Saied Alimoradi},
+  year={2021}
+}
+"""
+
+_URL = "persian_news_dataset.zip"
+
+
+
+class Persian_news(datasets.GeneratorBasedBuilder):
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "text": datasets.Value("string"),
+                    "title": datasets.Value("string"),
+                    "category": datasets.Value("string")
+                }
+            ),
+            homepage=_PROJECT_URL,
+            citation=_CITATION,
+        )
+
+
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        dl_dir = dl_manager.download_and_extract(_URL)
+        data_dir = os.path.join(dl_dir, "persian_news_dataset.csv")
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_dir,
+                },),]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        with open(filepath, encoding="utf-8") as f:
+            reader = csv.reader(f)
+            for id_, row in enumerate(reader):
+                if id_ == 0:
+                    continue
+                yield id_, {
+                    "text": row[0],
+                    "title": row[2],
+                    "category": row[1],
+                }
+