mirror of
				https://github.com/explosion/spaCy.git
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	* enable fuzzy matching * add fuzzy param to EntityMatcher * include rapidfuzz_capi not yet used * fix type * add FUZZY predicate * add fuzzy attribute list * fix type properly * tidying * remove unnecessary dependency * handle fuzzy sets * simplify fuzzy sets * case fix * switch to FUZZYn predicates use Levenshtein distance. remove fuzzy param. remove rapidfuzz_capi. * revert changes added for fuzzy param * switch to polyleven (Python package) * enable fuzzy matching * add fuzzy param to EntityMatcher * include rapidfuzz_capi not yet used * fix type * add FUZZY predicate * add fuzzy attribute list * fix type properly * tidying * remove unnecessary dependency * handle fuzzy sets * simplify fuzzy sets * case fix * switch to FUZZYn predicates use Levenshtein distance. remove fuzzy param. remove rapidfuzz_capi. * revert changes added for fuzzy param * switch to polyleven (Python package) * fuzzy match only on oov tokens * remove polyleven * exclude whitespace tokens * don't allow more edits than characters * fix min distance * reinstate FUZZY operator with length-based distance function * handle sets inside regex operator * remove is_oov check * attempt build fix no mypy failure locally * re-attempt build fix * don't overwrite fuzzy param value * move fuzzy_match to its own Python module to allow patching * move fuzzy_match back inside Matcher simplify logic and add tests * Format tests * Parametrize fuzzyn tests * Parametrize and merge fuzzy+set tests * Format * Move fuzzy_match to a standalone method * Change regex kwarg type to bool * Add types for fuzzy_match - Refactor variable names - Add test for symmetrical behavior * Parametrize fuzzyn+set tests * Minor refactoring for fuzz/fuzzy * Make fuzzy_match a Matcher kwarg * Update type for _default_fuzzy_match * don't overwrite function param * Rename to fuzzy_compare * Update fuzzy_compare default argument declarations * allow fuzzy_compare override from EntityRuler * define new Matcher keyword arg * fix type definition * Implement fuzzy_compare config option for EntityRuler and SpanRuler * Rename _default_fuzzy_compare to fuzzy_compare, remove from reexported objects * Use simpler fuzzy_compare algorithm * Update types * Increase minimum to 2 in fuzzy_compare to allow one transposition * Fix predicate keys and matching for SetPredicate with FUZZY and REGEX * Add FUZZY6..9 * Add initial docs * Increase default fuzzy to rounded 30% of pattern length * Update docs for fuzzy_compare in components * Update EntityRuler and SpanRuler API docs * Rename EntityRuler and SpanRuler setting to matcher_fuzzy_compare To having naming similar to `phrase_matcher_attr`, rename `fuzzy_compare` setting for `EntityRuler` and `SpanRuler` to `matcher_fuzzy_compare. Organize next to `phrase_matcher_attr` in docs. * Fix schema aliases Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix typo Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Add FUZZY6-9 operators and update tests * Parameterize test over greedy Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Fix type for fuzzy_compare to remove Optional * Rename to spacy.levenshtein_compare.v1, move to spacy.matcher.levenshtein * Update docs following levenshtein_compare renaming Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
		
			
				
	
	
		
			685 lines
		
	
	
		
			25 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			685 lines
		
	
	
		
			25 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
import pytest
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from spacy import registry
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from spacy.tokens import Doc, Span
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from spacy.language import Language
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from spacy.lang.en import English
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from spacy.pipeline import EntityRuler, EntityRecognizer, merge_entities
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from spacy.pipeline import SpanRuler
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from spacy.pipeline.ner import DEFAULT_NER_MODEL
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from spacy.errors import MatchPatternError
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from spacy.tests.util import make_tempdir
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from thinc.api import NumpyOps, get_current_ops
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ENTITY_RULERS = ["entity_ruler", "future_entity_ruler"]
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@pytest.fixture
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def nlp():
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    return Language()
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@pytest.fixture
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@registry.misc("entity_ruler_patterns")
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def patterns():
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    return [
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        {"label": "HELLO", "pattern": "hello world"},
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        {"label": "BYE", "pattern": [{"LOWER": "bye"}, {"LOWER": "bye"}]},
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        {"label": "HELLO", "pattern": [{"ORTH": "HELLO"}]},
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        {"label": "COMPLEX", "pattern": [{"ORTH": "foo", "OP": "*"}]},
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        {"label": "TECH_ORG", "pattern": "Apple", "id": "a1"},
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        {"label": "TECH_ORG", "pattern": "Microsoft", "id": "a2"},
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    ]
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@Language.component("add_ent")
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def add_ent_component(doc):
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    doc.ents = [Span(doc, 0, 3, label="ORG")]
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    return doc
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@pytest.mark.issue(3345)
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_issue3345(entity_ruler_factory):
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    """Test case where preset entity crosses sentence boundary."""
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    nlp = English()
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    doc = Doc(nlp.vocab, words=["I", "live", "in", "New", "York"])
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    doc[4].is_sent_start = True
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    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
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    ruler.add_patterns([{"label": "GPE", "pattern": "New York"}])
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    cfg = {"model": DEFAULT_NER_MODEL}
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    model = registry.resolve(cfg, validate=True)["model"]
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    ner = EntityRecognizer(doc.vocab, model)
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    # Add the OUT action. I wouldn't have thought this would be necessary...
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    ner.moves.add_action(5, "")
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    ner.add_label("GPE")
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    doc = ruler(doc)
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    # Get into the state just before "New"
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    state = ner.moves.init_batch([doc])[0]
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    ner.moves.apply_transition(state, "O")
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    ner.moves.apply_transition(state, "O")
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    ner.moves.apply_transition(state, "O")
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    # Check that B-GPE is valid.
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    assert ner.moves.is_valid(state, "B-GPE")
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@pytest.mark.issue(4849)
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_issue4849(entity_ruler_factory):
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    nlp = English()
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    patterns = [
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        {"label": "PERSON", "pattern": "joe biden", "id": "joe-biden"},
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        {"label": "PERSON", "pattern": "bernie sanders", "id": "bernie-sanders"},
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    ]
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    ruler = nlp.add_pipe(
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        entity_ruler_factory,
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        name="entity_ruler",
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        config={"phrase_matcher_attr": "LOWER"},
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    )
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    ruler.add_patterns(patterns)
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    text = """
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    The left is starting to take aim at Democratic front-runner Joe Biden.
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    Sen. Bernie Sanders joined in her criticism: "There is no 'middle ground' when it comes to climate policy."
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    """
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    # USING 1 PROCESS
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    count_ents = 0
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    for doc in nlp.pipe([text], n_process=1):
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        count_ents += len([ent for ent in doc.ents if ent.ent_id > 0])
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    assert count_ents == 2
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    # USING 2 PROCESSES
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    if isinstance(get_current_ops, NumpyOps):
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        count_ents = 0
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        for doc in nlp.pipe([text], n_process=2):
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            count_ents += len([ent for ent in doc.ents if ent.ent_id > 0])
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        assert count_ents == 2
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@pytest.mark.issue(5918)
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_issue5918(entity_ruler_factory):
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    # Test edge case when merging entities.
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    nlp = English()
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    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
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    patterns = [
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        {"label": "ORG", "pattern": "Digicon Inc"},
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        {"label": "ORG", "pattern": "Rotan Mosle Inc's"},
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        {"label": "ORG", "pattern": "Rotan Mosle Technology Partners Ltd"},
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    ]
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    ruler.add_patterns(patterns)
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    text = """
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        Digicon Inc said it has completed the previously-announced disposition
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        of its computer systems division to an investment group led by
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        Rotan Mosle Inc's Rotan Mosle Technology Partners Ltd affiliate.
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        """
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    doc = nlp(text)
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    assert len(doc.ents) == 3
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    # make it so that the third span's head is within the entity (ent_iob=I)
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    # bug #5918 would wrongly transfer that I to the full entity, resulting in 2 instead of 3 final ents.
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    # TODO: test for logging here
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    # with pytest.warns(UserWarning):
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    #     doc[29].head = doc[33]
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    doc = merge_entities(doc)
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    assert len(doc.ents) == 3
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@pytest.mark.issue(8168)
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_issue8168(entity_ruler_factory):
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    nlp = English()
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    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
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    patterns = [
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        {"label": "ORG", "pattern": "Apple"},
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        {
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            "label": "GPE",
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            "pattern": [{"LOWER": "san"}, {"LOWER": "francisco"}],
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            "id": "san-francisco",
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        },
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        {
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            "label": "GPE",
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            "pattern": [{"LOWER": "san"}, {"LOWER": "fran"}],
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            "id": "san-francisco",
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        },
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    ]
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    ruler.add_patterns(patterns)
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    doc = nlp("San Francisco San Fran")
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    assert all(t.ent_id_ == "san-francisco" for t in doc)
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@pytest.mark.issue(8216)
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_entity_ruler_fix8216(nlp, patterns, entity_ruler_factory):
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    """Test that patterns don't get added excessively."""
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    ruler = nlp.add_pipe(
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        entity_ruler_factory, name="entity_ruler", config={"validate": True}
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    )
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    ruler.add_patterns(patterns)
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    pattern_count = sum(len(mm) for mm in ruler.matcher._patterns.values())
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    assert pattern_count > 0
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    ruler.add_patterns([])
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    after_count = sum(len(mm) for mm in ruler.matcher._patterns.values())
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    assert after_count == pattern_count
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_entity_ruler_init(nlp, patterns, entity_ruler_factory):
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    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
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    ruler.add_patterns(patterns)
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    assert len(ruler) == len(patterns)
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    assert len(ruler.labels) == 4
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    assert "HELLO" in ruler
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    assert "BYE" in ruler
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    nlp.remove_pipe("entity_ruler")
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    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
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    ruler.add_patterns(patterns)
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    doc = nlp("hello world bye bye")
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    assert len(doc.ents) == 2
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    assert doc.ents[0].label_ == "HELLO"
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    assert doc.ents[1].label_ == "BYE"
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_entity_ruler_no_patterns_warns(nlp, entity_ruler_factory):
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    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
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    assert len(ruler) == 0
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    assert len(ruler.labels) == 0
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    nlp.remove_pipe("entity_ruler")
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    nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
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    assert nlp.pipe_names == ["entity_ruler"]
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    with pytest.warns(UserWarning):
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        doc = nlp("hello world bye bye")
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    assert len(doc.ents) == 0
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_entity_ruler_init_patterns(nlp, patterns, entity_ruler_factory):
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    # initialize with patterns
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    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
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    assert len(ruler.labels) == 0
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    ruler.initialize(lambda: [], patterns=patterns)
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    assert len(ruler.labels) == 4
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    doc = nlp("hello world bye bye")
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    assert doc.ents[0].label_ == "HELLO"
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    assert doc.ents[1].label_ == "BYE"
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    nlp.remove_pipe("entity_ruler")
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    # initialize with patterns from misc registry
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    nlp.config["initialize"]["components"]["entity_ruler"] = {
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        "patterns": {"@misc": "entity_ruler_patterns"}
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    }
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    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
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    assert len(ruler.labels) == 0
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    nlp.initialize()
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    assert len(ruler.labels) == 4
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    doc = nlp("hello world bye bye")
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    assert doc.ents[0].label_ == "HELLO"
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    assert doc.ents[1].label_ == "BYE"
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_entity_ruler_init_clear(nlp, patterns, entity_ruler_factory):
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    """Test that initialization clears patterns."""
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    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
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    ruler.add_patterns(patterns)
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    assert len(ruler.labels) == 4
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    ruler.initialize(lambda: [])
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    assert len(ruler.labels) == 0
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_entity_ruler_clear(nlp, patterns, entity_ruler_factory):
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    """Test that initialization clears patterns."""
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    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
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    ruler.add_patterns(patterns)
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    assert len(ruler.labels) == 4
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    doc = nlp("hello world")
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    assert len(doc.ents) == 1
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    ruler.clear()
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    assert len(ruler.labels) == 0
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    with pytest.warns(UserWarning):
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        doc = nlp("hello world")
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    assert len(doc.ents) == 0
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_entity_ruler_existing(nlp, patterns, entity_ruler_factory):
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    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
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    ruler.add_patterns(patterns)
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    nlp.add_pipe("add_ent", before="entity_ruler")
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    doc = nlp("OH HELLO WORLD bye bye")
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    assert len(doc.ents) == 2
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    assert doc.ents[0].label_ == "ORG"
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    assert doc.ents[1].label_ == "BYE"
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_entity_ruler_existing_overwrite(nlp, patterns, entity_ruler_factory):
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    ruler = nlp.add_pipe(
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        entity_ruler_factory, name="entity_ruler", config={"overwrite_ents": True}
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    )
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    ruler.add_patterns(patterns)
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    nlp.add_pipe("add_ent", before="entity_ruler")
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    doc = nlp("OH HELLO WORLD bye bye")
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    assert len(doc.ents) == 2
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    assert doc.ents[0].label_ == "HELLO"
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    assert doc.ents[0].text == "HELLO"
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    assert doc.ents[1].label_ == "BYE"
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_entity_ruler_existing_complex(nlp, patterns, entity_ruler_factory):
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    ruler = nlp.add_pipe(
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        entity_ruler_factory, name="entity_ruler", config={"overwrite_ents": True}
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    )
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    ruler.add_patterns(patterns)
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    nlp.add_pipe("add_ent", before="entity_ruler")
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    doc = nlp("foo foo bye bye")
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    assert len(doc.ents) == 2
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    assert doc.ents[0].label_ == "COMPLEX"
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    assert doc.ents[1].label_ == "BYE"
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    assert len(doc.ents[0]) == 2
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    assert len(doc.ents[1]) == 2
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_entity_ruler_entity_id(nlp, patterns, entity_ruler_factory):
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    ruler = nlp.add_pipe(
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        entity_ruler_factory, name="entity_ruler", config={"overwrite_ents": True}
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    )
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    ruler.add_patterns(patterns)
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    doc = nlp("Apple is a technology company")
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    assert len(doc.ents) == 1
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    assert doc.ents[0].label_ == "TECH_ORG"
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    assert doc.ents[0].ent_id_ == "a1"
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_entity_ruler_cfg_ent_id_sep(nlp, patterns, entity_ruler_factory):
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    config = {"overwrite_ents": True, "ent_id_sep": "**"}
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    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler", config=config)
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    ruler.add_patterns(patterns)
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    doc = nlp("Apple is a technology company")
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    if isinstance(ruler, EntityRuler):
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        assert "TECH_ORG**a1" in ruler.phrase_patterns
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    assert len(doc.ents) == 1
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    assert doc.ents[0].label_ == "TECH_ORG"
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    assert doc.ents[0].ent_id_ == "a1"
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@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
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def test_entity_ruler_serialize_bytes(nlp, patterns, entity_ruler_factory):
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    ruler = EntityRuler(nlp, patterns=patterns)
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    assert len(ruler) == len(patterns)
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    assert len(ruler.labels) == 4
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    ruler_bytes = ruler.to_bytes()
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    new_ruler = EntityRuler(nlp)
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    assert len(new_ruler) == 0
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    assert len(new_ruler.labels) == 0
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    new_ruler = new_ruler.from_bytes(ruler_bytes)
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    assert len(new_ruler) == len(patterns)
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    assert len(new_ruler.labels) == 4
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    assert len(new_ruler.patterns) == len(ruler.patterns)
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    for pattern in ruler.patterns:
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        assert pattern in new_ruler.patterns
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    assert sorted(new_ruler.labels) == sorted(ruler.labels)
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						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_serialize_phrase_matcher_attr_bytes(
 | 
						|
    nlp, patterns, entity_ruler_factory
 | 
						|
):
 | 
						|
    ruler = EntityRuler(nlp, phrase_matcher_attr="LOWER", patterns=patterns)
 | 
						|
    assert len(ruler) == len(patterns)
 | 
						|
    assert len(ruler.labels) == 4
 | 
						|
    ruler_bytes = ruler.to_bytes()
 | 
						|
    new_ruler = EntityRuler(nlp)
 | 
						|
    assert len(new_ruler) == 0
 | 
						|
    assert len(new_ruler.labels) == 0
 | 
						|
    assert new_ruler.phrase_matcher_attr is None
 | 
						|
    new_ruler = new_ruler.from_bytes(ruler_bytes)
 | 
						|
    assert len(new_ruler) == len(patterns)
 | 
						|
    assert len(new_ruler.labels) == 4
 | 
						|
    assert new_ruler.phrase_matcher_attr == "LOWER"
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_validate(nlp, entity_ruler_factory):
 | 
						|
    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
    validated_ruler = EntityRuler(nlp, validate=True)
 | 
						|
 | 
						|
    valid_pattern = {"label": "HELLO", "pattern": [{"LOWER": "HELLO"}]}
 | 
						|
    invalid_pattern = {"label": "HELLO", "pattern": [{"ASDF": "HELLO"}]}
 | 
						|
 | 
						|
    # invalid pattern raises error without validate
 | 
						|
    with pytest.raises(ValueError):
 | 
						|
        ruler.add_patterns([invalid_pattern])
 | 
						|
 | 
						|
    # valid pattern is added without errors with validate
 | 
						|
    validated_ruler.add_patterns([valid_pattern])
 | 
						|
 | 
						|
    # invalid pattern raises error with validate
 | 
						|
    with pytest.raises(MatchPatternError):
 | 
						|
        validated_ruler.add_patterns([invalid_pattern])
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_properties(nlp, patterns, entity_ruler_factory):
 | 
						|
    ruler = EntityRuler(nlp, patterns=patterns, overwrite_ents=True)
 | 
						|
    assert sorted(ruler.labels) == sorted(["HELLO", "BYE", "COMPLEX", "TECH_ORG"])
 | 
						|
    assert sorted(ruler.ent_ids) == ["a1", "a2"]
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_overlapping_spans(nlp, entity_ruler_factory):
 | 
						|
    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
    patterns = [
 | 
						|
        {"label": "FOOBAR", "pattern": "foo bar"},
 | 
						|
        {"label": "BARBAZ", "pattern": "bar baz"},
 | 
						|
    ]
 | 
						|
    ruler.add_patterns(patterns)
 | 
						|
    doc = nlp("foo bar baz")
 | 
						|
    assert len(doc.ents) == 1
 | 
						|
    assert doc.ents[0].label_ == "FOOBAR"
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_fuzzy_pipe(nlp, entity_ruler_factory):
 | 
						|
    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
    patterns = [{"label": "HELLO", "pattern": [{"LOWER": {"FUZZY": "hello"}}]}]
 | 
						|
    ruler.add_patterns(patterns)
 | 
						|
    doc = nlp("helloo")
 | 
						|
    assert len(doc.ents) == 1
 | 
						|
    assert doc.ents[0].label_ == "HELLO"
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_fuzzy(nlp, entity_ruler_factory):
 | 
						|
    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
    patterns = [{"label": "HELLO", "pattern": [{"LOWER": {"FUZZY": "hello"}}]}]
 | 
						|
    ruler.add_patterns(patterns)
 | 
						|
    doc = nlp("helloo")
 | 
						|
    assert len(doc.ents) == 1
 | 
						|
    assert doc.ents[0].label_ == "HELLO"
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_fuzzy_disabled(nlp, entity_ruler_factory):
 | 
						|
    @registry.misc("test_fuzzy_compare_disabled")
 | 
						|
    def make_test_fuzzy_compare_disabled():
 | 
						|
        return lambda x, y, z: False
 | 
						|
 | 
						|
    ruler = nlp.add_pipe(
 | 
						|
        entity_ruler_factory,
 | 
						|
        name="entity_ruler",
 | 
						|
        config={"matcher_fuzzy_compare": {"@misc": "test_fuzzy_compare_disabled"}},
 | 
						|
    )
 | 
						|
    patterns = [{"label": "HELLO", "pattern": [{"LOWER": {"FUZZY": "hello"}}]}]
 | 
						|
    ruler.add_patterns(patterns)
 | 
						|
    doc = nlp("helloo")
 | 
						|
    assert len(doc.ents) == 0
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("n_process", [1, 2])
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_multiprocessing(nlp, n_process, entity_ruler_factory):
 | 
						|
    if isinstance(get_current_ops, NumpyOps) or n_process < 2:
 | 
						|
        texts = ["I enjoy eating Pizza Hut pizza."]
 | 
						|
 | 
						|
        patterns = [{"label": "FASTFOOD", "pattern": "Pizza Hut", "id": "1234"}]
 | 
						|
 | 
						|
        ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
        ruler.add_patterns(patterns)
 | 
						|
 | 
						|
        for doc in nlp.pipe(texts, n_process=2):
 | 
						|
            for ent in doc.ents:
 | 
						|
                assert ent.ent_id_ == "1234"
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_serialize_jsonl(nlp, patterns, entity_ruler_factory):
 | 
						|
    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
    ruler.add_patterns(patterns)
 | 
						|
    with make_tempdir() as d:
 | 
						|
        ruler.to_disk(d / "test_ruler.jsonl")
 | 
						|
        ruler.from_disk(d / "test_ruler.jsonl")  # read from an existing jsonl file
 | 
						|
        with pytest.raises(ValueError):
 | 
						|
            ruler.from_disk(d / "non_existing.jsonl")  # read from a bad jsonl file
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_serialize_dir(nlp, patterns, entity_ruler_factory):
 | 
						|
    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
    ruler.add_patterns(patterns)
 | 
						|
    with make_tempdir() as d:
 | 
						|
        ruler.to_disk(d / "test_ruler")
 | 
						|
        ruler.from_disk(d / "test_ruler")  # read from an existing directory
 | 
						|
        with pytest.raises(ValueError):
 | 
						|
            ruler.from_disk(d / "non_existing_dir")  # read from a bad directory
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_remove_basic(nlp, entity_ruler_factory):
 | 
						|
    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
    patterns = [
 | 
						|
        {"label": "PERSON", "pattern": "Dina", "id": "dina"},
 | 
						|
        {"label": "ORG", "pattern": "ACME", "id": "acme"},
 | 
						|
        {"label": "ORG", "pattern": "ACM"},
 | 
						|
    ]
 | 
						|
    ruler.add_patterns(patterns)
 | 
						|
    doc = nlp("Dina went to school")
 | 
						|
    assert len(ruler.patterns) == 3
 | 
						|
    assert len(doc.ents) == 1
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        assert "PERSON||dina" in ruler.phrase_matcher
 | 
						|
    assert doc.ents[0].label_ == "PERSON"
 | 
						|
    assert doc.ents[0].text == "Dina"
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        ruler.remove("dina")
 | 
						|
    else:
 | 
						|
        ruler.remove_by_id("dina")
 | 
						|
    doc = nlp("Dina went to school")
 | 
						|
    assert len(doc.ents) == 0
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        assert "PERSON||dina" not in ruler.phrase_matcher
 | 
						|
    assert len(ruler.patterns) == 2
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_remove_same_id_multiple_patterns(nlp, entity_ruler_factory):
 | 
						|
    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
    patterns = [
 | 
						|
        {"label": "PERSON", "pattern": "Dina", "id": "dina"},
 | 
						|
        {"label": "ORG", "pattern": "DinaCorp", "id": "dina"},
 | 
						|
        {"label": "ORG", "pattern": "ACME", "id": "acme"},
 | 
						|
    ]
 | 
						|
    ruler.add_patterns(patterns)
 | 
						|
    doc = nlp("Dina founded DinaCorp and ACME.")
 | 
						|
    assert len(ruler.patterns) == 3
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        assert "PERSON||dina" in ruler.phrase_matcher
 | 
						|
        assert "ORG||dina" in ruler.phrase_matcher
 | 
						|
    assert len(doc.ents) == 3
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        ruler.remove("dina")
 | 
						|
    else:
 | 
						|
        ruler.remove_by_id("dina")
 | 
						|
    doc = nlp("Dina founded DinaCorp and ACME.")
 | 
						|
    assert len(ruler.patterns) == 1
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        assert "PERSON||dina" not in ruler.phrase_matcher
 | 
						|
        assert "ORG||dina" not in ruler.phrase_matcher
 | 
						|
    assert len(doc.ents) == 1
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_remove_nonexisting_pattern(nlp, entity_ruler_factory):
 | 
						|
    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
    patterns = [
 | 
						|
        {"label": "PERSON", "pattern": "Dina", "id": "dina"},
 | 
						|
        {"label": "ORG", "pattern": "ACME", "id": "acme"},
 | 
						|
        {"label": "ORG", "pattern": "ACM"},
 | 
						|
    ]
 | 
						|
    ruler.add_patterns(patterns)
 | 
						|
    assert len(ruler.patterns) == 3
 | 
						|
    with pytest.raises(ValueError):
 | 
						|
        ruler.remove("nepattern")
 | 
						|
    if isinstance(ruler, SpanRuler):
 | 
						|
        with pytest.raises(ValueError):
 | 
						|
            ruler.remove_by_id("nepattern")
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_remove_several_patterns(nlp, entity_ruler_factory):
 | 
						|
    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
    patterns = [
 | 
						|
        {"label": "PERSON", "pattern": "Dina", "id": "dina"},
 | 
						|
        {"label": "ORG", "pattern": "ACME", "id": "acme"},
 | 
						|
        {"label": "ORG", "pattern": "ACM"},
 | 
						|
    ]
 | 
						|
    ruler.add_patterns(patterns)
 | 
						|
    doc = nlp("Dina founded her company ACME.")
 | 
						|
    assert len(ruler.patterns) == 3
 | 
						|
    assert len(doc.ents) == 2
 | 
						|
    assert doc.ents[0].label_ == "PERSON"
 | 
						|
    assert doc.ents[0].text == "Dina"
 | 
						|
    assert doc.ents[1].label_ == "ORG"
 | 
						|
    assert doc.ents[1].text == "ACME"
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        ruler.remove("dina")
 | 
						|
    else:
 | 
						|
        ruler.remove_by_id("dina")
 | 
						|
    doc = nlp("Dina founded her company ACME")
 | 
						|
    assert len(ruler.patterns) == 2
 | 
						|
    assert len(doc.ents) == 1
 | 
						|
    assert doc.ents[0].label_ == "ORG"
 | 
						|
    assert doc.ents[0].text == "ACME"
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        ruler.remove("acme")
 | 
						|
    else:
 | 
						|
        ruler.remove_by_id("acme")
 | 
						|
    doc = nlp("Dina founded her company ACME")
 | 
						|
    assert len(ruler.patterns) == 1
 | 
						|
    assert len(doc.ents) == 0
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_remove_patterns_in_a_row(nlp, entity_ruler_factory):
 | 
						|
    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
    patterns = [
 | 
						|
        {"label": "PERSON", "pattern": "Dina", "id": "dina"},
 | 
						|
        {"label": "ORG", "pattern": "ACME", "id": "acme"},
 | 
						|
        {"label": "DATE", "pattern": "her birthday", "id": "bday"},
 | 
						|
        {"label": "ORG", "pattern": "ACM"},
 | 
						|
    ]
 | 
						|
    ruler.add_patterns(patterns)
 | 
						|
    doc = nlp("Dina founded her company ACME on her birthday")
 | 
						|
    assert len(doc.ents) == 3
 | 
						|
    assert doc.ents[0].label_ == "PERSON"
 | 
						|
    assert doc.ents[0].text == "Dina"
 | 
						|
    assert doc.ents[1].label_ == "ORG"
 | 
						|
    assert doc.ents[1].text == "ACME"
 | 
						|
    assert doc.ents[2].label_ == "DATE"
 | 
						|
    assert doc.ents[2].text == "her birthday"
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        ruler.remove("dina")
 | 
						|
        ruler.remove("acme")
 | 
						|
        ruler.remove("bday")
 | 
						|
    else:
 | 
						|
        ruler.remove_by_id("dina")
 | 
						|
        ruler.remove_by_id("acme")
 | 
						|
        ruler.remove_by_id("bday")
 | 
						|
    doc = nlp("Dina went to school")
 | 
						|
    assert len(doc.ents) == 0
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_remove_all_patterns(nlp, entity_ruler_factory):
 | 
						|
    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
    patterns = [
 | 
						|
        {"label": "PERSON", "pattern": "Dina", "id": "dina"},
 | 
						|
        {"label": "ORG", "pattern": "ACME", "id": "acme"},
 | 
						|
        {"label": "DATE", "pattern": "her birthday", "id": "bday"},
 | 
						|
    ]
 | 
						|
    ruler.add_patterns(patterns)
 | 
						|
    assert len(ruler.patterns) == 3
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        ruler.remove("dina")
 | 
						|
    else:
 | 
						|
        ruler.remove_by_id("dina")
 | 
						|
    assert len(ruler.patterns) == 2
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        ruler.remove("acme")
 | 
						|
    else:
 | 
						|
        ruler.remove_by_id("acme")
 | 
						|
    assert len(ruler.patterns) == 1
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        ruler.remove("bday")
 | 
						|
    else:
 | 
						|
        ruler.remove_by_id("bday")
 | 
						|
    assert len(ruler.patterns) == 0
 | 
						|
    with pytest.warns(UserWarning):
 | 
						|
        doc = nlp("Dina founded her company ACME on her birthday")
 | 
						|
        assert len(doc.ents) == 0
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
 | 
						|
def test_entity_ruler_remove_and_add(nlp, entity_ruler_factory):
 | 
						|
    ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
 | 
						|
    patterns = [{"label": "DATE", "pattern": "last time"}]
 | 
						|
    ruler.add_patterns(patterns)
 | 
						|
    doc = ruler(
 | 
						|
        nlp.make_doc("I saw him last time we met, this time he brought some flowers")
 | 
						|
    )
 | 
						|
    assert len(ruler.patterns) == 1
 | 
						|
    assert len(doc.ents) == 1
 | 
						|
    assert doc.ents[0].label_ == "DATE"
 | 
						|
    assert doc.ents[0].text == "last time"
 | 
						|
    patterns1 = [{"label": "DATE", "pattern": "this time", "id": "ttime"}]
 | 
						|
    ruler.add_patterns(patterns1)
 | 
						|
    doc = ruler(
 | 
						|
        nlp.make_doc("I saw him last time we met, this time he brought some flowers")
 | 
						|
    )
 | 
						|
    assert len(ruler.patterns) == 2
 | 
						|
    assert len(doc.ents) == 2
 | 
						|
    assert doc.ents[0].label_ == "DATE"
 | 
						|
    assert doc.ents[0].text == "last time"
 | 
						|
    assert doc.ents[1].label_ == "DATE"
 | 
						|
    assert doc.ents[1].text == "this time"
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        ruler.remove("ttime")
 | 
						|
    else:
 | 
						|
        ruler.remove_by_id("ttime")
 | 
						|
    doc = ruler(
 | 
						|
        nlp.make_doc("I saw him last time we met, this time he brought some flowers")
 | 
						|
    )
 | 
						|
    assert len(ruler.patterns) == 1
 | 
						|
    assert len(doc.ents) == 1
 | 
						|
    assert doc.ents[0].label_ == "DATE"
 | 
						|
    assert doc.ents[0].text == "last time"
 | 
						|
    ruler.add_patterns(patterns1)
 | 
						|
    doc = ruler(
 | 
						|
        nlp.make_doc("I saw him last time we met, this time he brought some flowers")
 | 
						|
    )
 | 
						|
    assert len(ruler.patterns) == 2
 | 
						|
    assert len(doc.ents) == 2
 | 
						|
    patterns2 = [{"label": "DATE", "pattern": "another time", "id": "ttime"}]
 | 
						|
    ruler.add_patterns(patterns2)
 | 
						|
    doc = ruler(
 | 
						|
        nlp.make_doc(
 | 
						|
            "I saw him last time we met, this time he brought some flowers, another time some chocolate."
 | 
						|
        )
 | 
						|
    )
 | 
						|
    assert len(ruler.patterns) == 3
 | 
						|
    assert len(doc.ents) == 3
 | 
						|
    if isinstance(ruler, EntityRuler):
 | 
						|
        ruler.remove("ttime")
 | 
						|
    else:
 | 
						|
        ruler.remove_by_id("ttime")
 | 
						|
    doc = ruler(
 | 
						|
        nlp.make_doc(
 | 
						|
            "I saw him last time we met, this time he brought some flowers, another time some chocolate."
 | 
						|
        )
 | 
						|
    )
 | 
						|
    assert len(ruler.patterns) == 1
 | 
						|
    assert len(doc.ents) == 1
 |