Create banglawiki.py

banglawiki.py

@@ -0,0 +1,142 @@
+# 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
+"""Wikipedia dataset containing cleaned articles of all languages."""
+
+
+import json
+
+import datasets
+import pyarrow.parquet as pq
+
+from .lang_def import WIKIPEDIA_LANGUAGES
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CITATION = """\
+@ONLINE {wikidump,
+    author = {Wikimedia Foundation},
+    title  = {Wikimedia Downloads},
+    url    = {https://dumps.wikimedia.org}
+}
+"""
+
+_DESCRIPTION = """\
+Wikipedia dataset containing cleaned articles of all languages.
+The datasets are built from the Wikipedia dump
+(https://dumps.wikimedia.org/) with one split per language. Each example
+contains the content of one full Wikipedia article with cleaning to strip
+markdown and unwanted sections (references, etc.).
+"""
+
+_LICENSE = (
+    "This work is licensed under the Creative Commons Attribution-ShareAlike "
+    "3.0 Unported License. To view a copy of this license, visit "
+    "http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to "
+    "Creative Commons, PO Box 1866, Mountain View, CA 94042, USA."
+)
+
+_BASE_URL_TMPL = "data/{date}/{lang}"
+
+_VERSION = datasets.Version("1.2.0", "")
+
+
+class WikipediaConfig(datasets.BuilderConfig):
+    """BuilderConfig for Wikipedia."""
+
+    def __init__(self, language=None, date=None, version=_VERSION, **kwargs):
+        """BuilderConfig for Wikipedia.
+        Args:
+          language: string, the language code for the Wikipedia dump to use.
+          date: string, date of the Wikipedia dump in YYYYMMDD format. A list of
+            available dates can be found at https://dumps.wikimedia.org/enwiki/.
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super().__init__(
+            name=f"{date}.{language}",
+            description=f"Wikipedia dataset for {language}, parsed from {date} dump.",
+            version=version,
+            **kwargs,
+        )
+        self.date = date
+        self.language = language
+
+
+class Wikipedia(datasets.ArrowBasedBuilder):
+    """Wikipedia dataset."""
+
+    # Use mirror (your.org) to avoid download caps.
+    BUILDER_CONFIG_CLASS = WikipediaConfig
+    BUILDER_CONFIGS = [
+        WikipediaConfig(
+            language=lang,
+            date=date,
+        )  # pylint:disable=g-complex-comprehension
+        for date in WIKIPEDIA_LANGUAGES.keys()
+        for lang in WIKIPEDIA_LANGUAGES[date]
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "url": datasets.Value("string"),
+                    "title": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                }
+            ),
+            # No default supervised_keys.
+            supervised_keys=None,
+            homepage="https://dumps.wikimedia.org",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        def _base_url(lang):
+            return _BASE_URL_TMPL.format(lang=lang, date=self.config.date)
+
+        lang = self.config.language
+
+        info_file_url = _base_url(lang) + "/info.json"
+        downloaded_info_file = dl_manager.download_and_extract({"info": info_file_url})
+        with open(downloaded_info_file["info"], "r") as f:
+            info = json.load(f)
+
+        shard_urls = [
+            _base_url(lang) + "/" + shard_name for shard_name in info["shards"]
+        ]
+        downloaded_files = dl_manager.download({"train": shard_urls})
+        logger.info("downloaded_files = %s", downloaded_files)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepaths": downloaded_files["train"]},
+            ),
+        ]
+
+    def _generate_tables(self, filepaths):
+        """This function returns the examples in the raw (text) form."""
+
+        for filepath in filepaths:
+            with open(filepath, "rb") as f:
+                pf = pq.ParquetFile(f)
+                for group_i in range(pf.num_row_groups):
+                    tbl = pf.read_row_group(group_i)
+                    yield group_i, tbl