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"""Dummy backend for testing basic interaction of projects and backends""" |
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from __future__ import annotations |
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from typing import TYPE_CHECKING, Any |
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from annif.corpus import Document |
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from annif.suggestion import SubjectSuggestion |
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from . import backend |
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if TYPE_CHECKING: |
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from annif.corpus.document import DocumentCorpus |
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class DummyBackend(backend.AnnifLearningBackend): |
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name = "dummy" |
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initialized = False |
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subject_id = 0 |
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is_trained = True |
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modification_time = None |
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def initialize(self, parallel: bool = False) -> None: |
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self.initialized = True |
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def _suggest( |
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self, doc: Document, params: dict[str, Any] |
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) -> list[SubjectSuggestion]: |
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score = float(params.get("score", doc.metadata.get("score", 1.0))) |
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# Ensure tests fail if "doc" with wrong type ends up here |
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assert isinstance(doc, Document) |
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assert isinstance(doc.text, str) |
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# Give no hits for no text |
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if len(doc.text) == 0: |
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return [] |
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# allow overriding returned subject via uri parameter |
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if "uri" in params: |
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subject_id = self.project.subjects.by_uri(params["uri"]) |
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else: |
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subject_id = self.subject_id |
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return [SubjectSuggestion(subject_id=subject_id, score=score)] |
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def _learn( |
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self, |
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corpus: DocumentCorpus, |
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params: dict[str, Any], |
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) -> None: |
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# in this dummy backend we "learn" by picking up the subject ID |
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# of the first subject of the first document in the learning set |
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# and using that in subsequent analysis results |
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for doc in corpus.documents: |
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if doc.subject_set: |
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self.subject_id = doc.subject_set[0] |
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break |
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NatLibFi /
Annif
