Create snappfood-sentiment-analysis

snappfood-sentiment-analysis

@@ -0,0 +1,55 @@
+import csv
+import datasets
+
+_CITATION = ""
+
+
+_DESCRIPTION = """ Snappfood sentiment analysis dataset"""
+
+FILENAME = "Snappfood - Sentiment Analysis.csv"
+
+class SnappfoodSentiment(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="snappfood_sentiment",
+            version=datasets.Version("1.0.0", ""),
+            description="snappfood sentiment analysis dataset",
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "comment": datasets.Value("string"),
+                    "label": datasets.Value("string"),
+                    "label_id": datasets.Value("float64"),
+                }
+            ),
+            # No default supervised_keys.
+            supervised_keys=None,
+            homepage="https://www.kaggle.com/datasets/soheiltehranipour/snappfood-persian-sentiment-analysis",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        dl_dir = dl_manager.download_and_extract(FILENAME)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": dl_dir})
+        ]
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        try:
+            with open(filepath, encoding="utf-8") as f:
+                reader = csv.DictReader(f, delimiter="\t")
+                for idx, row in enumerate(reader):
+                    yield idx, {
+                        "comment": row["comment"],
+                        "label": row["label"],
+                        "label_id": row["label_id"],
+                    }
+        except Exception as e:
+            print(e)