def book_info_to_metadata(self, subgraph, book_info):
"""Filters raw book information to exclude irrelevant or unhelpful data.
:returns: None if information is unhelpful; metadata object otherwise.
"""
if not self._has_relevant_types(book_info):
# This book is not available in any format we're
# interested in from a metadata perspective.
return None
(oclc_id_type,
oclc_id,
titles,
descriptions,
subjects,
creator_uris,
publisher_names,
publication_dates,
example_uris) = self.extract_useful_data(subgraph, book_info)
if not oclc_id_type or not oclc_id:
return None
self.log.info("Processing edition %s: %r", oclc_id, titles)
metadata = Metadata(self.source)
metadata.primary_identifier = IdentifierData(
type=oclc_id_type, identifier=oclc_id
)
if titles:
metadata.title = titles[0]
for d in publication_dates:
try:
metadata.published = datetime.datetime.strptime(d[:4], "%Y")
except Exception, e:
pass
def book_info_to_metadata(self, subgraph, book_info):
"""Filters raw book information to exclude irrelevant or unhelpful data.
:returns: None if information is unhelpful; metadata object otherwise.
"""
if not self._has_relevant_types(book_info):
# This book is not available in any format we're
# interested in from a metadata perspective.
return None
(oclc_id_type, oclc_id, titles, descriptions, subjects, creator_uris,
publisher_names, publication_dates,
example_uris) = self.extract_useful_data(subgraph, book_info)
if not oclc_id_type or not oclc_id:
return None
self.log.info("Processing edition %s: %r", oclc_id, titles)
metadata = Metadata(self.source)
metadata.primary_identifier = IdentifierData(type=oclc_id_type,
identifier=oclc_id)
if titles:
metadata.title = titles[0]
for d in publication_dates:
try:
metadata.published = datetime.datetime.strptime(d[:4], "%Y")
except Exception, e:
pass
def lookup_info_to_metadata(self, lookup_representation):
"""Transforms a NoveList JSON representation into a Metadata object"""
if not lookup_representation.content:
return None
lookup_info = json.loads(lookup_representation.content)
book_info = lookup_info['TitleInfo']
if book_info:
novelist_identifier = book_info.get('ui')
if not book_info or not novelist_identifier:
# NoveList didn't know the ISBN.
return None
primary_identifier, ignore = Identifier.for_foreign_id(
self._db, Identifier.NOVELIST_ID, novelist_identifier)
metadata = Metadata(self.source, primary_identifier=primary_identifier)
# Get the equivalent ISBN identifiers.
metadata.identifiers += self._extract_isbns(book_info)
author = book_info.get('author')
if author:
metadata.contributors.append(ContributorData(sort_name=author))
description = book_info.get('description')
if description:
metadata.links.append(
LinkData(rel=Hyperlink.DESCRIPTION,
content=description,
media_type=Representation.TEXT_PLAIN))
audience_level = book_info.get('audience_level')
if audience_level:
metadata.subjects.append(
SubjectData(Subject.FREEFORM_AUDIENCE, audience_level))
novelist_rating = book_info.get('rating')
if novelist_rating:
metadata.measurements.append(
MeasurementData(Measurement.RATING, novelist_rating))
# Extract feature content if it is available.
series_info = None
appeals_info = None
lexile_info = None
goodreads_info = None
recommendations_info = None
feature_content = lookup_info.get('FeatureContent')
if feature_content:
series_info = feature_content.get('SeriesInfo')
appeals_info = feature_content.get('Appeals')
lexile_info = feature_content.get('LexileInfo')
goodreads_info = feature_content.get('GoodReads')
recommendations_info = feature_content.get('SimilarTitles')
metadata, title_key = self.get_series_information(
metadata, series_info, book_info)
metadata.title = book_info.get(title_key)
subtitle = TitleProcessor.extract_subtitle(metadata.title,
book_info.get('full_title'))
metadata.subtitle = self._scrub_subtitle(subtitle)
# TODO: How well do we trust this data? We could conceivably bump up
# the weight here.
if appeals_info:
extracted_genres = False
for appeal in appeals_info:
genres = appeal.get('genres')
if genres:
for genre in genres:
metadata.subjects.append(
SubjectData(Subject.TAG, genre['Name']))
extracted_genres = True
if extracted_genres:
break
if lexile_info:
metadata.subjects.append(
SubjectData(Subject.LEXILE_SCORE, lexile_info['Lexile']))
if goodreads_info:
metadata.measurements.append(
MeasurementData(Measurement.RATING,
goodreads_info['average_rating']))
metadata = self.get_recommendations(metadata, recommendations_info)
# If nothing interesting comes from the API, ignore it.
if not (metadata.measurements or metadata.series_position
or metadata.series or metadata.subjects or metadata.links
or metadata.subtitle or metadata.recommendations):
metadata = None
return metadata
def lookup_info_to_metadata(self, lookup_representation):
"""Transforms a NoveList JSON representation into a Metadata object"""
if not lookup_representation.content:
return None
lookup_info = json.loads(lookup_representation.content)
book_info = lookup_info['TitleInfo']
if book_info:
novelist_identifier = book_info.get('ui')
if not book_info or not novelist_identifier:
# NoveList didn't know the ISBN.
return None
primary_identifier, ignore = Identifier.for_foreign_id(
self._db, Identifier.NOVELIST_ID, novelist_identifier
)
metadata = Metadata(self.source, primary_identifier=primary_identifier)
# Get the equivalent ISBN identifiers.
metadata.identifiers += self._extract_isbns(book_info)
author = book_info.get('author')
if author:
metadata.contributors.append(ContributorData(sort_name=author))
description = book_info.get('description')
if description:
metadata.links.append(LinkData(
rel=Hyperlink.DESCRIPTION, content=description,
media_type=Representation.TEXT_PLAIN
))
audience_level = book_info.get('audience_level')
if audience_level:
metadata.subjects.append(SubjectData(
Subject.FREEFORM_AUDIENCE, audience_level
))
novelist_rating = book_info.get('rating')
if novelist_rating:
metadata.measurements.append(MeasurementData(
Measurement.RATING, novelist_rating
))
# Extract feature content if it is available.
series_info = None
appeals_info = None
lexile_info = None
goodreads_info = None
recommendations_info = None
feature_content = lookup_info.get('FeatureContent')
if feature_content:
series_info = feature_content.get('SeriesInfo')
appeals_info = feature_content.get('Appeals')
lexile_info = feature_content.get('LexileInfo')
goodreads_info = feature_content.get('GoodReads')
recommendations_info = feature_content.get('SimilarTitles')
metadata, title_key = self.get_series_information(
metadata, series_info, book_info
)
metadata.title = book_info.get(title_key)
subtitle = TitleProcessor.extract_subtitle(
metadata.title, book_info.get('full_title')
)
metadata.subtitle = self._scrub_subtitle(subtitle)
if appeals_info:
extracted_genres = False
for appeal in appeals_info:
genres = appeal.get('genres')
if genres:
for genre in genres:
metadata.subjects.append(SubjectData(
Subject.TAG, genre['Name']
))
extracted_genres = True
if extracted_genres:
break
if lexile_info:
metadata.subjects.append(SubjectData(
Subject.LEXILE_SCORE, lexile_info['Lexile']
))
if goodreads_info:
metadata.measurements.append(MeasurementData(
Measurement.RATING, goodreads_info['average_rating']
))
metadata = self.get_recommendations(metadata, recommendations_info)
# If nothing interesting comes from the API, ignore it.
if not (metadata.measurements or metadata.series_position or
metadata.series or metadata.subjects or metadata.links or
metadata.subtitle or metadata.recommendations
):
metadata = None
return metadata
