forked from mirrors/bookwyrm
115 lines
3.7 KiB
Python
115 lines
3.7 KiB
Python
''' using a bookwyrm instance as a source of book data '''
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from functools import reduce
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import operator
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from django.contrib.postgres.search import SearchRank, SearchVector
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from django.db.models import Count, F, Q
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from bookwyrm import models
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from .abstract_connector import AbstractConnector, SearchResult
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class Connector(AbstractConnector):
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''' instantiate a connector '''
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# pylint: disable=arguments-differ
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def search(self, query, min_confidence=0.1, raw=False):
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''' search your local database '''
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if not query:
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return []
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# first, try searching unqiue identifiers
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results = search_identifiers(query)
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if not results:
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# then try searching title/author
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results = search_title_author(query, min_confidence)
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search_results = []
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for result in results:
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if raw:
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search_results.append(result)
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else:
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search_results.append(self.format_search_result(result))
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if len(search_results) >= 10:
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break
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if not raw:
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search_results.sort(key=lambda r: r.confidence, reverse=True)
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return search_results
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def format_search_result(self, search_result):
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return SearchResult(
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title=search_result.title,
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key=search_result.remote_id,
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author=search_result.author_text,
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year=search_result.published_date.year if \
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search_result.published_date else None,
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connector=self,
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confidence=search_result.rank if \
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hasattr(search_result, 'rank') else 1,
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)
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def is_work_data(self, data):
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pass
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def get_edition_from_work_data(self, data):
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pass
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def get_work_from_edition_data(self, data):
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pass
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def get_authors_from_data(self, data):
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return None
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def parse_search_data(self, data):
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''' it's already in the right format, don't even worry about it '''
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return data
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def expand_book_data(self, book):
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pass
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def search_identifiers(query):
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''' tries remote_id, isbn; defined as dedupe fields on the model '''
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filters = [{f.name: query} for f in models.Edition._meta.get_fields() \
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if hasattr(f, 'deduplication_field') and f.deduplication_field]
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results = models.Edition.objects.filter(
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reduce(operator.or_, (Q(**f) for f in filters))
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).distinct()
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# when there are multiple editions of the same work, pick the default.
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# it would be odd for this to happen.
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return results.filter(parent_work__default_edition__id=F('id')) \
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or results
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def search_title_author(query, min_confidence):
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''' searches for title and author '''
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vector = SearchVector('title', weight='A') +\
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SearchVector('subtitle', weight='B') +\
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SearchVector('authors__name', weight='C') +\
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SearchVector('series', weight='D')
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results = models.Edition.objects.annotate(
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search=vector
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).annotate(
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rank=SearchRank(vector, query)
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).filter(
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rank__gt=min_confidence
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).order_by('-rank')
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# when there are multiple editions of the same work, pick the closest
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editions_of_work = results.values(
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'parent_work'
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).annotate(
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Count('parent_work')
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).values_list('parent_work')
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for work_id in set(editions_of_work):
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editions = results.filter(parent_work=work_id)
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default = editions.filter(parent_work__default_edition=F('id'))
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default_rank = default.first().rank if default.exists() else 0
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# if mutliple books have the top rank, pick the default edition
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if default_rank == editions.first().rank:
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yield default.first()
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else:
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yield editions.first()
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