Upload lampeter_corpus.py

Dataloader for the lampeter corpus

lampeter_corpus.py

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+# 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.
+
+"""The Lampeter Corpus of Early Modern English Tracts is a collection of texts 
+on various subject matter published between 1640 and 1740 – a time that is marked 
+by the rise of mass publication, the development of a public discourse in many 
+areas of everyday life and, last but not least, the standardisation of British English."""
+
+from bs4 import BeautifulSoup
+import datasets
+
+_CITATION = """ @misc{20.500.12024/3193,
+ title = {The Lampeter Corpus of Early Modern English Tracts},
+ url = {http://hdl.handle.net/20.500.12024/3193},
+ note = {Oxford Text Archive},
+ copyright = {Distributed by the University of Oxford under a Creative Commons Attribution-{ShareAlike} 3.0 Unported License},
+"""
+
+_DESCRIPTION = """The Lampeter Corpus of Early Modern English Tracts is a collection of texts on
+ various subject matter published between 1640 and 1740 – a time that is marked by the rise of mass 
+ publication, the development of a public discourse in many areas of everyday life 
+ and, last but not least, the standardisation of British English.
+"""
+
+_HOMEPAGE = "https://ota.bodleian.ox.ac.uk/repository/xmlui/handle/20.500.12024/3193"
+
+_LICENSE = "Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)"
+
+_URL = "https://ota.bodleian.ox.ac.uk/repository/xmlui/bitstream/handle/20.500.12024/3193/3193.xml?sequence=9&isAllowed=y"
+
+_CLASS_MAP = {"L": "Law", "E": "Economy", "M": "Miscellaneous", "P": "Politics", "S": "Science", "R": "Religion"}
+
+class LampeterCorpus(datasets.GeneratorBasedBuilder):
+    """ The Lampeter Corpus of Early Modern English Tracts is a collection of texts on
+        various subject matter published between 1640 and 1740. Each text is associated with a year 
+        and one of the following topics: Law, Economy, Religion, Poitics, Science, Miscellaneous
+    """
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "id": datasets.Value("string"),
+                "text": datasets.Value("string"),
+                "date": datasets.Value("string"),
+                "genre": datasets.Value("string"),
+                "head": datasets.Value("string"),
+                "title": datasets.Value("string")
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_file = dl_manager.download(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_file,
+                    "split": "train",
+                },
+            ),      
+        ]
+
+    def _generate_examples(self, filepath, split):
+        with open(filepath, encoding="utf-8") as f:
+            soup=BeautifulSoup(f, features='xml')
+            for entry in soup.find_all("TEI"):
+                text_parts = []
+                title_with_id = entry.teiHeader.fileDesc.titleStmt.title.text
+                id, title = title_with_id.split(":", maxsplit=1)
+                id = id.strip()
+                title=title.strip()
+                date=id[-4:]
+                content = entry.find("text")
+                head=content.find("body").find("head")
+                if head:
+                    head=head.text
+                else:
+                    head=""
+                body_parts=content.find("body").find_all("p")
+                for body_part in body_parts:
+                    text_parts.append(body_part.text)
+                full_text = " ".join(text_parts)
+                genre=_CLASS_MAP[id[0]]
+                data_point = {
+                    "id": id, 
+                    "text": full_text, 
+                    "genre": genre, 
+                    "date": date, 
+                    "head": head, 
+                    "title": title
+                    }
+                yield id, data_point