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"""Common functionality for backends.""" |
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import abc |
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from annif import logger |
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class AnnifBackend(metaclass=abc.ABCMeta): |
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"""Base class for Annif backends that perform analysis. The |
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non-implemented methods should be overridden in subclasses.""" |
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name = None |
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needs_subject_index = False |
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needs_subject_vectorizer = False |
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def __init__(self, backend_id, params, datadir): |
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"""Initialize backend with specific parameters. The |
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parameters are a dict. Keys and values depend on the specific |
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backend type.""" |
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self.backend_id = backend_id |
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self.params = params |
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self.datadir = datadir |
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def train(self, corpus, project): |
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"""train the model on the given document or subject corpus""" |
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pass # default is to do nothing, subclasses may override |
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def initialize(self): |
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"""This method can be overridden by backends. It should cause the |
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backend to pre-load all data it needs during operation.""" |
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pass |
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@abc.abstractmethod |
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def _suggest(self, text, project, params): |
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"""This method should implemented by backends. It implements |
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the suggest functionality, with pre-processed parameters.""" |
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pass # pragma: no cover |
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def suggest(self, text, project, params=None): |
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"""Suggest subjects for the input text and return a list of subjects |
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represented as a list of SubjectSuggestion objects.""" |
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beparams = dict(self.params) |
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if params is not None: |
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beparams.update(params) |
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return self._suggest(text, project, params=beparams) |
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def debug(self, message): |
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"""Log a debug message from this backend""" |
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logger.debug("Backend {}: {}".format(self.backend_id, message)) |
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def info(self, message): |
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"""Log an info message from this backend""" |
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logger.info("Backend {}: {}".format(self.backend_id, message)) |
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def warning(self, message): |
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"""Log a warning message from this backend""" |
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logger.warning("Backend {}: {}".format(self.backend_id, message)) |
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class AnnifLearningBackend(AnnifBackend): |
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"""Base class for Annif backends that can perform online learning""" |
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@abc.abstractmethod |
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def learn(self, corpus, project): |
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"""further train the model on the given document or subject corpus""" |
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pass # pragma: no cover |
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NatLibFi /
Annif
