Create web_archive_classification.py

web_archive_classification.py

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+# Copyright 2022 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.
+"""British Library Web Classification Dataset."""
+
+import datasets
+import csv
+
+_CITATION = """\
+TODO
+"""
+
+_DESCRIPTION = """\
+        The dataset comprises a manually curated selective archive produced by UKWA which includes the classification of sites into a two-tiered subject hierarchy. 
+        """
+_HOMEPAGE = "https://doi.org/10.5259/ukwa.ds.1/classification/1"
+
+_LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/"
+
+_URL = "https://bl.iro.bl.uk/downloads/78e2421a-70ea-426d-8a67-57e4a8b23019?locale=en"
+
+
+class WebArchiveClassificationDataset(datasets.GeneratorBasedBuilder):
+    """Web Archive Classification Dataset"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "primary_category": datasets.ClassLabel(
+                    names=[
+                        "Arts & Humanities",
+                        "Business, Economy & Industry",
+                        "Company Web Sites",
+                        "Computer Science, Information Technology and Web Technology",
+                        "Crime, Criminology, Police and Prisons",
+                        "Digital Society",
+                        "Education & Research",
+                        "Environment",
+                        "Government, Law & Politics",
+                        "History",
+                        "Law and Legal System",
+                        "Libraries, Archives and Museums",
+                        "Life Sciences",
+                        "Literature",
+                        "Medicine & Health",
+                        "Politics, Political Theory and Political Systems",
+                        "Popular Science",
+                        "Publishing, Printing and Bookselling",
+                        "Religion",
+                        "Science & Technology",
+                        "Social Problems and Welfare",
+                        "Society & Culture",
+                        "Sports and Recreation",
+                        "Travel & Tourism",
+                    ]
+                ),
+                "secondary_category": datasets.ClassLabel(
+                    names=[
+                        "Architecture",
+                        "Art and Design",
+                        "Comedy and Humour",
+                        "Dance",
+                        "Family History / Genealogy",
+                        "Film / Cinema",
+                        "Geography",
+                        "History",
+                        "Languages",
+                        "Literature",
+                        "Live Art",
+                        "Local History",
+                        "Music",
+                        "News and Contemporary Events",
+                        "Oral History in the UK",
+                        "Philosophy and Ethics",
+                        "Publishing, Printing and Bookselling",
+                        "Religion",
+                        "TV and Radio",
+                        "Theatre",
+                        "Agriculture, Fishing, and Forestry",
+                        "Banking, Insurance, Accountancy and Financial Economics",
+                        "Business Studies and Management Theory",
+                        "Company Web Sites",
+                        "Credit Crunch",
+                        "Economic Development, Enterprise and Aid",
+                        "Economics and Economic Theory",
+                        "Employment, Unemployment and Labour Economics",
+                        "Energy",
+                        "Industries",
+                        "Marketing and Market Research",
+                        "Trade, Commerce, and Globalisation",
+                        "Transport and Infrastructure",
+                        "Cambridge Network",
+                        "Video Games",
+                        "Governing the Police",
+                        "Blogs",
+                        "Dictionaries, Encyclopaedias, and Reference Works",
+                        "Further Education",
+                        "Higher Education",
+                        "Libraries, Archives and Museums",
+                        "Library Key Issues",
+                        "Lifelong Learning",
+                        "Preschool Education",
+                        "School Education",
+                        "Special Needs Education",
+                        "Vocational Education",
+                        "Indian Ocean Tsunami December 2004",
+                        "Central Government",
+                        "Civil Rights, Pressure Groups, and Trade Unions",
+                        "Crime, Criminology, Police and Prisons",
+                        "Devolved Government",
+                        "European Parliament Elections 2009",
+                        "Inter-Governmental Agencies",
+                        "International Relations, Diplomacy, and Peace",
+                        "Law and Legal System",
+                        "Local Government",
+                        "London Mayoral Election 2008",
+                        "Political Parties",
+                        "Politics, Political Theory and Political Systems",
+                        "Public Inquiries",
+                        "Scottish Parliamentary Election - 2007",
+                        "Spending Cuts 2010: Impact on Social Welfare",
+                        "UK General Election 2005",
+                        "Slavery and Abolition in the Caribbean",
+                        "Religion, politics and law since 2005",
+                        "Evolving role of libraries in the UK",
+                        "History of Libraries Collection",
+                        "Darwin 200",
+                        "19th Century English Literature",
+                        "Alternative Medicine / Complementary Medicine",
+                        "Conditions and Diseases",
+                        "Health Organisations and Services",
+                        "Medicines, Treatments and Therapies",
+                        "Men's Issues",
+                        "Mental Health",
+                        "Pandemic Influenza",
+                        "Personal Experiences of Illness",
+                        "Public Health and Safety",
+                        "Women's Issues",
+                        "Political Action and Communication",
+                        "E-publishing Trends",
+                        "Free Church",
+                        "Quakers",
+                        "Computer Science, Information Technology and Web Technology",
+                        "Engineering",
+                        "Environment",
+                        "Life Sciences",
+                        "Mathematics",
+                        "Physical Sciences",
+                        "Popular Science",
+                        "Zoology, Veterinary Science and Animal Health",
+                        "Communities",
+                        "Digital Society",
+                        "Food and Drink",
+                        "London Terrorist Attack 7th July 2005",
+                        "Queen's Diamond Jubilee, 2012",
+                        "Social Problems and Welfare",
+                        "Sociology, Anthropology and Population Studies",
+                        "Sports and Recreation",
+                        "Travel & Tourism",
+                        "British Countryside",
+                        "Olympic & Paralympic Games 2012",
+                        "Cornwall",
+                    ]
+                ),
+                "title": datasets.Value("string"),
+                "url": datasets.Value("string"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+
+        csv_file = dl_manager.download_and_extract(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"csv_file": csv_file},
+            ),
+        ]
+
+    def _generate_examples(self, csv_file):
+        with open(csv_file) as f:
+            reader = csv.DictReader(f, dialect="excel-tab")
+            for id_, row in enumerate(reader):
+                yield id_, {
+                    "primary_category": row["Primary Category"],
+                    "secondary_category": row["Secondary Category"],
+                    "title": row["Title"],
+                    "url": row["URL"],
+                }