Convert dataset to Parquet (#2)

- Convert dataset to Parquet (b512ea6393f2f27f3189f2d1313c769b04472065)
- Delete loading script (c848ab906ba2b484f47fa1e3d83c2d4e2f2f5402)

README.md

@@ -19,9 +19,9 @@ task_categories:
 task_ids:
 - language-modeling
 - masked-language-modeling
-paperswithcode_id: null
 pretty_name: Indonesian Newspapers 2018
 dataset_info:
+  config_name: id_newspapers_2018
   features:
   - name: id
     dtype: string
@@ -33,13 +33,18 @@ dataset_info:
     dtype: string
   - name: content
     dtype: string
-  config_name: id_newspapers_2018
   splits:
   - name: train
-    num_bytes: 1116031922
+    num_bytes: 1160553070
     num_examples: 499164
-  download_size: 446018349
-  dataset_size: 1116031922
+  download_size: 647992433
+  dataset_size: 1160553070
+configs:
+- config_name: id_newspapers_2018
+  data_files:
+  - split: train
+    path: id_newspapers_2018/train-*
+  default: true
 ---
 
 # Dataset Card for Indonesian Newspapers 2018

id_newspapers_2018.py

@@ -1,115 +0,0 @@
-# coding=utf-8
-# 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.
-"""Indonesian Newspapers 2018"""
-
-
-import json
-
-import datasets
-
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_CITATION = """\
-@inproceedings{id_newspapers_2018,
-  author    = {},
-  title     = {Indonesian Newspapers 2018},
-  year      = {2019},
-  url       = {https://github.com/feryandi/Dataset-Artikel},
-}
-"""
-
-_DESCRIPTION = """\
-The dataset contains around 500K articles (136M of words) from 7 Indonesian newspapers: Detik, Kompas, Tempo,
-CNN Indonesia, Sindo, Republika and Poskota. The articles are dated between 1st January 2018 and 20th August 2018
-(with few exceptions dated earlier). The size of uncompressed 500K json files (newspapers-json.tgz) is around 2.2GB,
-and the cleaned uncompressed in a big text file (newspapers.txt.gz) is about 1GB. The original source in Google Drive
-contains also a dataset in html format which include raw data (pictures, css, javascript, ...)
-from the online news website
-"""
-
-_HOMEPAGE = "https://github.com/feryandi/Dataset-Artikel"
-
-_LICENSE = "Creative Commons Attribution-ShareAlike 4.0 International Public License"
-
-_URL = "http://cloud.uncool.ai/index.php/s/kF83dQHfGeS2LX2/download"
-
-
-class IdNewspapers2018Config(datasets.BuilderConfig):
-    """BuilderConfig for IdNewspapers2018"""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for IdNewspapers2018.
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(IdNewspapers2018Config, self).__init__(**kwargs)
-
-
-class IdNewspapers2018(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        IdNewspapers2018Config(
-            name="id_newspapers_2018",
-            version=VERSION,
-            description="IdNewspapers2018 dataset",
-        ),
-    ]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "id": datasets.Value("string"),
-                "url": datasets.Value("string"),
-                "date": datasets.Value("string"),
-                "title": datasets.Value("string"),
-                "content": datasets.Value("string"),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        archive = dl_manager.download(_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "files": dl_manager.iter_archive(archive),
-                },
-            )
-        ]
-
-    def _generate_examples(self, files):
-        id = 0
-        for path, f in files:
-            if path.startswith("newspapers") and path.endswith(".json"):
-                data = json.loads(f.read().decode("utf-8"))
-                yield id, {
-                    "id": str(id),
-                    "url": data["url"],
-                    "date": data["date"],
-                    "title": data["title"],
-                    "content": data["content"],
-                }
-                id += 1

id_newspapers_2018/train-00000-of-00003.parquet

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+oid sha256:8c558af5e81458790ceb7747640a53d012eb49750d85ea764d1491300a40e68b
+size 213632186

id_newspapers_2018/train-00001-of-00003.parquet

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+oid sha256:fb98c69c9c0d166087329eaea62b6f517851cdad372b9431932c20df690c45fd
+size 216256471

id_newspapers_2018/train-00002-of-00003.parquet

@@ -0,0 +1,3 @@
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+oid sha256:0f8a5ac189faffde3527a9794f01b91ec80a2d28a12422702ea4aefc0df18abd
+size 218103776