init

data/news.tar.gz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ca04dec098e4f775891e5c3ad9c32571e4c2c5d335eb4f44b4a5e71a63bfc64c
+size 213600962

hebrew_news.py

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+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+import csv
+import os.path
+
+import datasets
+from urllib.parse import urlparse
+
+_CITATION = """
+"""
+
+_DESCRIPTION = """\
+"""
+
+
+class HebrewNewsConfig(datasets.BuilderConfig):
+    """BuilderConfig"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(HebrewNewsConfig, self).__init__(**kwargs)
+
+
+class HebrewNews(datasets.GeneratorBasedBuilder):
+    """HebrewNews dataset."""
+
+    BUILDER_CONFIGS = [
+        HebrewNewsConfig(
+            name="hebrew_news", version=datasets.Version("1.0.0"),
+            description=f"hebrew news dataset"
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "articleBody": datasets.Value("string"),
+                    "description": datasets.Value("string"),
+                    "headline": datasets.Value("string"),
+                    "title": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage="",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = "data/news.tar.gz"
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": downloaded_files},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            fieldnames = ["articleBody", "description", "headline", "title"]
+            reader = csv.DictReader(f, delimiter=",", fieldnames=fieldnames)
+            for idx, row in enumerate(reader):
+                yield idx, {
+                    "id": idx,
+                    "articleBody": row["articleBody"],
+                    "description": row["description"],
+                    "headline": row["headline"],
+                    "title": row["title"],
+                }