Datasets:
Tasks:
Summarization
Modalities:
Text
Sub-tasks:
news-articles-summarization
Languages:
Hebrew
Size:
100K - 1M
License:
File size: 2,423 Bytes
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import csv
csv.field_size_limit(int(1e6))
import os.path
import datasets
from urllib.parse import urlparse
import io
_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"
archive_path = dl_manager.download(urls_to_download)
archive_iter = dl_manager.iter_archive(archive_path)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"archive_iter":archive_iter },
),
]
def _generate_examples(self, archive_iter):
for filepath, f in archive_iter:
csv_file = io.TextIOWrapper(f, encoding="utf-8")
fieldnames = ["articleBody", "description", "headline", "title"]
reader = csv.DictReader(csv_file, delimiter=",", fieldnames=fieldnames)
next(reader)
for idx, row in enumerate(reader):
yield idx, {
"id": idx,
"articleBody": row["articleBody"],
"description": row["description"],
"headline": row["headline"],
"title": row["title"],
}
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