# coding=utf-8 # Copyright 2021 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 Books Genre Dataset""" import ast import csv from datetime import datetime from typing import Dict, List import datasets _CITATION = """\ @misc{british library_genre, title={ 19th Century Books - metadata with additional crowdsourced annotations}, url={https://doi.org/10.23636/BKHQ-0312}, author={{British Library} and Morris, Victoria and van Strien, Daniel and Tolfo, Giorgia and Afric, Lora and Robertson, Stewart and Tiney, Patricia and Dogterom, Annelies and Wollner, Ildi}, year={2021}} """ _DESCRIPTION = """\ This dataset contains metadata for resources belonging to the British Library’s digitised printed books (18th-19th century) collection (bl.uk/collection-guides/digitised-printed-books). This metadata has been extracted from British Library catalogue records. The metadata held within our main catalogue is updated regularly. This metadata dataset should be considered a snapshot of this metadata. """ _HOMEPAGE = "doi.org/10.23636/BKHQ-0312" _LICENSE = "CC0 1.0 Universal Public Domain" _URL = "https://bl.iro.bl.uk/downloads/36c7cd20-c8a7-4495-acbe-469b9132c6b1?locale=en" common_features = { "BL record ID": datasets.Value("string"), "Name": datasets.Value("string"), "Dates associated with name": datasets.Value("string"), "Type of name": datasets.Value("string"), "Role": datasets.Value("string"), "All names": datasets.features.Sequence(datasets.Value("string")), "Title": datasets.Value("string"), "Variant titles": datasets.Value("string"), "Series title": datasets.Value("string"), "Number within series": datasets.Value("string"), "Country of publication": datasets.Sequence(datasets.Value("string")), "Place of publication": datasets.Sequence(datasets.Value("string")), "Publisher": datasets.Value("string"), "Date of publication": datasets.Value("string"), "Edition": datasets.Value("string"), "Physical description": datasets.Value("string"), "Dewey classification": datasets.Value("string"), "BL shelfmark": datasets.Value("string"), "Topics": datasets.Value("string"), "Genre": datasets.Value("string"), "Languages": datasets.features.Sequence(datasets.Value("string")), "Notes": datasets.Value("string"), "BL record ID for physical resource": datasets.Value("string"), "classification_id": datasets.Value("string"), "user_id": datasets.Value("string"), "subject_ids": datasets.Value("string"), "annotator_date_pub": datasets.Value("string"), "annotator_normalised_date_pub": datasets.Value("string"), "annotator_edition_statement": datasets.Value("string"), "annotator_FAST_genre_terms": datasets.Value("string"), "annotator_FAST_subject_terms": datasets.Value("string"), "annotator_comments": datasets.Value("string"), "annotator_main_language": datasets.Value("string"), "annotator_other_languages_summaries": datasets.Value("string"), "annotator_summaries_language": datasets.Value("string"), "annotator_translation": datasets.Value("string"), "annotator_original_language": datasets.Value("string"), "annotator_publisher": datasets.Value("string"), "annotator_place_pub": datasets.Value("string"), "annotator_country": datasets.Value("string"), "annotator_title": datasets.Value("string"), "Link to digitised book": datasets.Value("string"), "annotated": datasets.Value("bool"), } raw_features = datasets.Features( { **common_features, **{ "Type of resource": datasets.features.ClassLabel( names=["Monograph", "Serial", "Monographic component part"] ), "created_at": datasets.Value("string"), "annotator_genre": datasets.Value("string"), }, } ) annotated_raw_features = datasets.Features( { **common_features, **{ "Type of resource": datasets.features.ClassLabel( names=[ "Monograph", "Serial", ] ), "created_at": datasets.Value("timestamp[s]"), "annotator_genre": datasets.features.ClassLabel( names=[ "Fiction", "Can't tell", "Non-fiction", "The book contains both Fiction and Non-Fiction", ] ), }, } ) class BlBooksGenre(datasets.GeneratorBasedBuilder): VERSION = datasets.Version("1.1.0") BUILDER_CONFIGS = [ datasets.BuilderConfig( name="title_genre_classifiction", version=VERSION, description="This part of my dataset covers a first domain", ), datasets.BuilderConfig( name="annotated_raw", version=VERSION, description="""\ This version of the dataset includes all fields from the original dataset which are annotated. This includes duplication from different annotators""", ), datasets.BuilderConfig( name="raw", version=VERSION, description="""\ This version of the dataset includes all the fields from the original dataset including rows without annotation. It includes duplications from different annotators""", ), ] DEFAULT_CONFIG_NAME = "title_genre_classifiction" def _info(self): if self.config.name == "title_genre_classifiction": features = datasets.Features( { "BL record ID": datasets.Value("string"), "title": datasets.Value("string"), "label": datasets.features.ClassLabel(names=["Fiction", "Non-fiction"]), } ) if self.config.name == "annotated_raw": features = annotated_raw_features if self.config.name == "raw": features = raw_features return datasets.DatasetInfo( description=_DESCRIPTION, features=features, supervised_keys=None, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" data_file = dl_manager.download(_URL) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, # These kwargs will be passed to _generate_examples gen_kwargs={ "filepath": data_file, "split": "train", }, ), ] def _parse_language(self, row: Dict) -> List[str]: languages = row["Languages"] if not languages: return [] return languages.split(";") def _parse_country(self, row: Dict) -> List[str]: return row["Country of publication"].split(";") if row["Country of publication"] else [] def _parse_place_of_publication(self, row: Dict) -> List[str]: return row["Place of publication"].split(";") if row["Place of publication"] else [] def _parse_all_names(self, row: Dict) -> List[str]: return row["All names"].split(";") if row["All names"] else [] def _generate_examples(self, filepath, split): """Yields examples as (key, example) tuples.""" with open(filepath, encoding="utf-8") as f: reader = csv.DictReader(f) if self.config.name == "title_genre_classifiction": unique = set() id_ = 0 for row in reader: annotated = ast.literal_eval(row["annotated"]) if not annotated: continue label = row["annotator_genre"] if label not in {"Fiction", "Non-fiction"}: continue title = row["Title"] if title in unique: continue unique.add(title) id_ += 1 yield id_, { "BL record ID": row["BL record ID"], "title": title, "label": label, } if self.config.name == "annotated_raw": id_ = 0 for row in reader: annotated = ast.literal_eval(row["annotated"]) if not annotated: continue created_at = datetime.strptime(row["created_at"], "%Y-%m-%d %H:%M:%S %Z") id_ += 1 yield id_, { "BL record ID": row["BL record ID"], "Type of resource": row["Type of resource"], "Name": row["Name"], "Dates associated with name": row["Dates associated with name"], "Type of name": row["Type of name"], "Role": row["Role"], "All names": self._parse_all_names(row), "Title": row["Title"], "Variant titles": row["Variant titles"], "Series title": row["Series title"], "Number within series": row["Number within series"], "Country of publication": self._parse_country(row), "Place of publication": self._parse_place_of_publication(row), "Publisher": row["Publisher"], "Date of publication": row["Date of publication"], "Edition": row["Edition"], "Physical description": row["Physical description"], "Dewey classification": row["Dewey classification"], "BL shelfmark": row["BL shelfmark"], "Topics": row["Topics"], "Genre": row["Genre"], "Languages": self._parse_language(row), "Notes": row["Notes"], "BL record ID for physical resource": row["BL record ID for physical resource"], "classification_id": row["classification_id"], "user_id": row["user_id"], "created_at": created_at, "subject_ids": row["subject_ids"], "annotator_date_pub": row["annotator_date_pub"], "annotator_normalised_date_pub": row["annotator_normalised_date_pub"], "annotator_edition_statement": row["annotator_edition_statement"], "annotator_genre": row["annotator_genre"], "annotator_FAST_genre_terms": row["annotator_FAST_genre_terms"], "annotator_FAST_subject_terms": row["annotator_FAST_subject_terms"], "annotator_comments": row["annotator_comments"], "annotator_main_language": row["annotator_main_language"], "annotator_other_languages_summaries": row["annotator_other_languages_summaries"], "annotator_summaries_language": row["annotator_summaries_language"], "annotator_translation": row["annotator_translation"], "annotator_original_language": row["annotator_original_language"], "annotator_publisher": row["annotator_publisher"], "annotator_place_pub": row["annotator_place_pub"], "annotator_country": row["annotator_country"], "annotator_title": row["annotator_title"], "Link to digitised book": row["Link to digitised book"], "annotated": annotated, } if self.config.name == "raw": for id_, row in enumerate(reader): yield id_, { "BL record ID": row["BL record ID"], "Type of resource": row["Type of resource"], "Name": row["Name"], "Dates associated with name": row["Dates associated with name"], "Type of name": row["Type of name"], "Role": row["Role"], "All names": self._parse_all_names(row), "Title": row["Title"], "Variant titles": row["Variant titles"], "Series title": row["Series title"], "Number within series": row["Number within series"], "Country of publication": self._parse_country(row), "Place of publication": self._parse_place_of_publication(row), "Publisher": row["Publisher"], "Date of publication": row["Date of publication"], "Edition": row["Edition"], "Physical description": row["Physical description"], "Dewey classification": row["Dewey classification"], "BL shelfmark": row["BL shelfmark"], "Topics": row["Topics"], "Genre": row["Genre"], "Languages": self._parse_language(row), "Notes": row["Notes"], "BL record ID for physical resource": row["BL record ID for physical resource"], "classification_id": row["classification_id"], "user_id": row["user_id"], "created_at": row["created_at"], "subject_ids": row["subject_ids"], "annotator_date_pub": row["annotator_date_pub"], "annotator_normalised_date_pub": row["annotator_normalised_date_pub"], "annotator_edition_statement": row["annotator_edition_statement"], "annotator_genre": row["annotator_genre"], "annotator_FAST_genre_terms": row["annotator_FAST_genre_terms"], "annotator_FAST_subject_terms": row["annotator_FAST_subject_terms"], "annotator_comments": row["annotator_comments"], "annotator_main_language": row["annotator_main_language"], "annotator_other_languages_summaries": row["annotator_other_languages_summaries"], "annotator_summaries_language": row["annotator_summaries_language"], "annotator_translation": row["annotator_translation"], "annotator_original_language": row["annotator_original_language"], "annotator_publisher": row["annotator_publisher"], "annotator_place_pub": row["annotator_place_pub"], "annotator_country": row["annotator_country"], "annotator_title": row["annotator_title"], "Link to digitised book": row["Link to digitised book"], "annotated": ast.literal_eval(row["annotated"]), }