Upload ccnews_split.py

ccnews_split.py

@@ -0,0 +1,140 @@
+# coding=utf-8
+# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
+#
+# 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.
+
+# Lint as: python3
+"""The CC-News dataset is based on Common Crawl News Dataset by Sebastian Nagel"""
+
+import json
+import os
+from fnmatch import fnmatch
+
+import datasets
+
+
+def custom_iter_archive(archive):
+    def _iter_archive(f):
+        stream = tarfile.open(fileobj=f, mode="r|*")
+        print(stream)
+        print(len(stream))
+        for tarinfo in stream:
+            file_path = tarinfo.name
+            if not tarinfo.isreg():
+                continue
+            if file_path is None:
+                continue
+            if os.path.basename(file_path).startswith(".") or os.path.basename(file_path).startswith("__"):
+                # skipping hidden files
+                continue
+            file_obj = stream.extractfile(tarinfo)
+            yield file_path, file_obj
+            stream.members = []
+        del stream
+
+    if hasattr(path_or_buf, "read"):
+        yield from _iter_archive(path_or_buf)
+    else:
+        with open(path_or_buf, "rb") as f:
+            yield from _iter_archive(f)
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_DESCRIPTION = """\
+CC-News containing news articles from news sites all over the world \
+The data is available on AWS S3 in the Common Crawl bucket at /crawl-data/CC-NEWS/. \
+This version of the dataset has 708241 articles. It represents a small portion of English  \
+language subset of the CC-News dataset created using news-please(Hamborg et al.,2017) to \
+collect and extract English language portion of CC-News.
+"""
+
+_CITATION = """\
+@InProceedings{Hamborg2017,
+  author     = {Hamborg, Felix and Meuschke, Norman and Breitinger, Corinna and Gipp, Bela},
+  title      = {news-please: A Generic News Crawler and Extractor},
+  year       = {2017},
+  booktitle  = {Proceedings of the 15th International Symposium of Information Science},
+  location   = {Berlin},
+  doi        = {10.5281/zenodo.4120316},
+  pages      = {218--223},
+  month      = {March}
+}
+"""
+_PROJECT_URL = "https://commoncrawl.org/2016/10/news-dataset-available/"
+_DOWNLOAD_URL = "https://storage.googleapis.com/huggingface-nlp/datasets/cc_news/cc_news.tar.gz"
+
+
+class CCNewsConfig(datasets.BuilderConfig):
+    """BuilderConfig for CCNews."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for CCNews.
+        Args:
+        **kwargs: keyword arguments forwarded to super.
+        """
+        super(CCNewsConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+
+
+class CCNews(datasets.GeneratorBasedBuilder):
+    """CC-News dataset."""
+
+    BUILDER_CONFIGS = [
+        CCNewsConfig(
+            name="plain_text",
+            description="Plain text",
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "title": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                    "domain": datasets.Value("string"),
+                    "date": datasets.Value("string"),
+                    "description": datasets.Value("string"),
+                    "url": datasets.Value("string"),
+                    "image_url": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_PROJECT_URL,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        archive = dl_manager.download(_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 article_file_path, f in files:
+            if fnmatch(os.path.basename(article_file_path), "*.json"):
+                article = json.load(f)
+                yield id_, {
+                    "title": article["title"].strip() if article["title"] is not None else "",
+                    "text": article["maintext"].strip() if article["maintext"] is not None else "",
+                    "domain": article["source_domain"].strip() if article["source_domain"] is not None else "",
+                    "date": article["date_publish"].strip() if article["date_publish"] is not None else "",
+                    "description": article["description"].strip() if article["description"] is not None else "",
+                    "url": article["url"].strip() if article["url"] is not None else "",
+                    "image_url": article["image_url"].strip() if article["image_url"] is not None else "",
+                }
+                id_ += 1
+