for testing and deploying your application
for finding and fixing issues
for empowering human code reviews
"""Annif backend mixins that can be used to implement features"""
import abc
from annif.suggestion import ListSuggestionResult
class ChunkingBackend(metaclass=abc.ABCMeta):
"""Annif backend mixin that implements chunking of input"""
@abc.abstractmethod
def _suggest_chunks(self, chunktexts, project):
"""Suggest subjects for the chunked text; should be implemented by
the subclass inheriting this mixin"""
pass # pragma: no cover
def _suggest(self, text, project, params):
self.initialize()
self.debug('Suggesting subjects for text "{}..." (len={})'.format(
text[:20], len(text)))
sentences = project.analyzer.tokenize_sentences(text)
self.debug('Found {} sentences'.format(len(sentences)))
chunksize = int(params['chunksize'])
chunktexts = []
for i in range(0, len(sentences), chunksize):
chunktexts.append(' '.join(sentences[i:i + chunksize]))
self.debug('Split sentences into {} chunks'.format(len(chunktexts)))
if len(chunktexts) == 0: # no input, empty result
return ListSuggestionResult(
hits=[], subject_index=project.subjects)
return self._suggest_chunks(chunktexts, project)
NatLibFi /
Annif
