# 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"]),
}