mirror of https://github.com/explosion/spaCy.git
510 lines
18 KiB
Python
510 lines
18 KiB
Python
import warnings
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import pytest
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import srsly
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from mock import Mock
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from spacy.lang.en import English
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from spacy.matcher import Matcher, PhraseMatcher
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from spacy.tokens import Doc, Span
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from spacy.vocab import Vocab
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from ..util import make_tempdir
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@pytest.mark.issue(3248)
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def test_issue3248_1():
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"""Test that the PhraseMatcher correctly reports its number of rules, not
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total number of patterns."""
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nlp = English()
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matcher = PhraseMatcher(nlp.vocab)
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matcher.add("TEST1", [nlp("a"), nlp("b"), nlp("c")])
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matcher.add("TEST2", [nlp("d")])
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assert len(matcher) == 2
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@pytest.mark.issue(3331)
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def test_issue3331(en_vocab):
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"""Test that duplicate patterns for different rules result in multiple
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matches, one per rule.
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"""
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matcher = PhraseMatcher(en_vocab)
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matcher.add("A", [Doc(en_vocab, words=["Barack", "Obama"])])
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matcher.add("B", [Doc(en_vocab, words=["Barack", "Obama"])])
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doc = Doc(en_vocab, words=["Barack", "Obama", "lifts", "America"])
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matches = matcher(doc)
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assert len(matches) == 2
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match_ids = [en_vocab.strings[matches[0][0]], en_vocab.strings[matches[1][0]]]
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assert sorted(match_ids) == ["A", "B"]
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@pytest.mark.issue(3972)
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def test_issue3972(en_vocab):
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"""Test that the PhraseMatcher returns duplicates for duplicate match IDs."""
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matcher = PhraseMatcher(en_vocab)
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matcher.add("A", [Doc(en_vocab, words=["New", "York"])])
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matcher.add("B", [Doc(en_vocab, words=["New", "York"])])
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doc = Doc(en_vocab, words=["I", "live", "in", "New", "York"])
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matches = matcher(doc)
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assert len(matches) == 2
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# We should have a match for each of the two rules
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found_ids = [en_vocab.strings[ent_id] for (ent_id, _, _) in matches]
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assert "A" in found_ids
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assert "B" in found_ids
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@pytest.mark.issue(4002)
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def test_issue4002(en_vocab):
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"""Test that the PhraseMatcher can match on overwritten NORM attributes."""
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matcher = PhraseMatcher(en_vocab, attr="NORM")
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pattern1 = Doc(en_vocab, words=["c", "d"])
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assert [t.norm_ for t in pattern1] == ["c", "d"]
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matcher.add("TEST", [pattern1])
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doc = Doc(en_vocab, words=["a", "b", "c", "d"])
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assert [t.norm_ for t in doc] == ["a", "b", "c", "d"]
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matches = matcher(doc)
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assert len(matches) == 1
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matcher = PhraseMatcher(en_vocab, attr="NORM")
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pattern2 = Doc(en_vocab, words=["1", "2"])
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pattern2[0].norm_ = "c"
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pattern2[1].norm_ = "d"
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assert [t.norm_ for t in pattern2] == ["c", "d"]
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matcher.add("TEST", [pattern2])
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matches = matcher(doc)
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assert len(matches) == 1
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@pytest.mark.issue(4373)
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def test_issue4373():
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"""Test that PhraseMatcher.vocab can be accessed (like Matcher.vocab)."""
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matcher = Matcher(Vocab())
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assert isinstance(matcher.vocab, Vocab)
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matcher = PhraseMatcher(Vocab())
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assert isinstance(matcher.vocab, Vocab)
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@pytest.mark.issue(4651)
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def test_issue4651_with_phrase_matcher_attr():
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"""Test that the EntityRuler PhraseMatcher is deserialized correctly using
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the method from_disk when the EntityRuler argument phrase_matcher_attr is
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specified.
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"""
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text = "Spacy is a python library for nlp"
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nlp = English()
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patterns = [{"label": "PYTHON_LIB", "pattern": "spacy", "id": "spaCy"}]
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ruler = nlp.add_pipe("entity_ruler", config={"phrase_matcher_attr": "LOWER"})
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ruler.add_patterns(patterns)
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doc = nlp(text)
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res = [(ent.text, ent.label_, ent.ent_id_) for ent in doc.ents]
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nlp_reloaded = English()
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with make_tempdir() as d:
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file_path = d / "entityruler"
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ruler.to_disk(file_path)
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nlp_reloaded.add_pipe("entity_ruler").from_disk(file_path)
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doc_reloaded = nlp_reloaded(text)
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res_reloaded = [(ent.text, ent.label_, ent.ent_id_) for ent in doc_reloaded.ents]
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assert res == res_reloaded
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@pytest.mark.issue(6839)
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def test_issue6839(en_vocab):
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"""Ensure that PhraseMatcher accepts Span as input"""
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# fmt: off
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words = ["I", "like", "Spans", "and", "Docs", "in", "my", "input", ",", "and", "nothing", "else", "."]
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# fmt: on
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doc = Doc(en_vocab, words=words)
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span = doc[:8]
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pattern = Doc(en_vocab, words=["Spans", "and", "Docs"])
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matcher = PhraseMatcher(en_vocab)
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matcher.add("SPACY", [pattern])
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matches = matcher(span)
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assert matches
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@pytest.mark.issue(10643)
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def test_issue10643(en_vocab):
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"""Ensure overlapping terms can be removed from PhraseMatcher"""
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# fmt: off
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words = ["Only", "save", "out", "the", "binary", "data", "for", "the", "individual", "components", "."]
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# fmt: on
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doc = Doc(en_vocab, words=words)
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terms = {
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"0": Doc(en_vocab, words=["binary"]),
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"1": Doc(en_vocab, words=["binary", "data"]),
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}
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matcher = PhraseMatcher(en_vocab)
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for match_id, term in terms.items():
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matcher.add(match_id, [term])
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matches = matcher(doc)
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assert matches == [(en_vocab.strings["0"], 4, 5), (en_vocab.strings["1"], 4, 6)]
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matcher.remove("0")
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assert len(matcher) == 1
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new_matches = matcher(doc)
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assert new_matches == [(en_vocab.strings["1"], 4, 6)]
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matcher.remove("1")
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assert len(matcher) == 0
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no_matches = matcher(doc)
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assert not no_matches
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def test_matcher_phrase_matcher(en_vocab):
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doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
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# intermediate phrase
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pattern = Doc(en_vocab, words=["Google", "Now"])
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matcher = PhraseMatcher(en_vocab)
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matcher.add("COMPANY", [pattern])
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assert len(matcher(doc)) == 1
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# initial token
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pattern = Doc(en_vocab, words=["I"])
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matcher = PhraseMatcher(en_vocab)
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matcher.add("I", [pattern])
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assert len(matcher(doc)) == 1
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# initial phrase
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pattern = Doc(en_vocab, words=["I", "like"])
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matcher = PhraseMatcher(en_vocab)
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matcher.add("ILIKE", [pattern])
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assert len(matcher(doc)) == 1
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# final token
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pattern = Doc(en_vocab, words=["best"])
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matcher = PhraseMatcher(en_vocab)
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matcher.add("BEST", [pattern])
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assert len(matcher(doc)) == 1
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# final phrase
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pattern = Doc(en_vocab, words=["Now", "best"])
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matcher = PhraseMatcher(en_vocab)
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matcher.add("NOWBEST", [pattern])
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assert len(matcher(doc)) == 1
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def test_phrase_matcher_length(en_vocab):
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matcher = PhraseMatcher(en_vocab)
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assert len(matcher) == 0
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matcher.add("TEST", [Doc(en_vocab, words=["test"])])
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assert len(matcher) == 1
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matcher.add("TEST2", [Doc(en_vocab, words=["test2"])])
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assert len(matcher) == 2
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def test_phrase_matcher_contains(en_vocab):
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matcher = PhraseMatcher(en_vocab)
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matcher.add("TEST", [Doc(en_vocab, words=["test"])])
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assert "TEST" in matcher
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assert "TEST2" not in matcher
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def test_phrase_matcher_add_new_api(en_vocab):
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doc = Doc(en_vocab, words=["a", "b"])
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patterns = [Doc(en_vocab, words=["a"]), Doc(en_vocab, words=["a", "b"])]
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matcher = PhraseMatcher(en_vocab)
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matcher.add("OLD_API", None, *patterns)
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assert len(matcher(doc)) == 2
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matcher = PhraseMatcher(en_vocab)
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on_match = Mock()
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matcher.add("OLD_API_CALLBACK", on_match, *patterns)
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assert len(matcher(doc)) == 2
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assert on_match.call_count == 2
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# New API: add(key: str, patterns: List[List[dict]], on_match: Callable)
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matcher = PhraseMatcher(en_vocab)
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matcher.add("NEW_API", patterns)
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assert len(matcher(doc)) == 2
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matcher = PhraseMatcher(en_vocab)
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on_match = Mock()
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matcher.add("NEW_API_CALLBACK", patterns, on_match=on_match)
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assert len(matcher(doc)) == 2
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assert on_match.call_count == 2
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def test_phrase_matcher_repeated_add(en_vocab):
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matcher = PhraseMatcher(en_vocab)
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# match ID only gets added once
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matcher.add("TEST", [Doc(en_vocab, words=["like"])])
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matcher.add("TEST", [Doc(en_vocab, words=["like"])])
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matcher.add("TEST", [Doc(en_vocab, words=["like"])])
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matcher.add("TEST", [Doc(en_vocab, words=["like"])])
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doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
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assert "TEST" in matcher
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assert "TEST2" not in matcher
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assert len(matcher(doc)) == 1
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def test_phrase_matcher_remove(en_vocab):
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matcher = PhraseMatcher(en_vocab)
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matcher.add("TEST1", [Doc(en_vocab, words=["like"])])
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matcher.add("TEST2", [Doc(en_vocab, words=["best"])])
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doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
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assert "TEST1" in matcher
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assert "TEST2" in matcher
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assert "TEST3" not in matcher
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assert len(matcher(doc)) == 2
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matcher.remove("TEST1")
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assert "TEST1" not in matcher
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assert "TEST2" in matcher
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assert "TEST3" not in matcher
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assert len(matcher(doc)) == 1
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matcher.remove("TEST2")
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assert "TEST1" not in matcher
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assert "TEST2" not in matcher
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assert "TEST3" not in matcher
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assert len(matcher(doc)) == 0
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with pytest.raises(KeyError):
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matcher.remove("TEST3")
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assert "TEST1" not in matcher
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assert "TEST2" not in matcher
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assert "TEST3" not in matcher
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assert len(matcher(doc)) == 0
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def test_phrase_matcher_overlapping_with_remove(en_vocab):
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matcher = PhraseMatcher(en_vocab)
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matcher.add("TEST", [Doc(en_vocab, words=["like"])])
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# TEST2 is added alongside TEST
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matcher.add("TEST2", [Doc(en_vocab, words=["like"])])
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doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
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assert "TEST" in matcher
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assert len(matcher) == 2
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assert len(matcher(doc)) == 2
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# removing TEST does not remove the entry for TEST2
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matcher.remove("TEST")
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assert "TEST" not in matcher
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assert len(matcher) == 1
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assert len(matcher(doc)) == 1
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assert matcher(doc)[0][0] == en_vocab.strings["TEST2"]
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# removing TEST2 removes all
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matcher.remove("TEST2")
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assert "TEST2" not in matcher
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assert len(matcher) == 0
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assert len(matcher(doc)) == 0
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def test_phrase_matcher_string_attrs(en_vocab):
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words1 = ["I", "like", "cats"]
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pos1 = ["PRON", "VERB", "NOUN"]
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words2 = ["Yes", ",", "you", "hate", "dogs", "very", "much"]
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pos2 = ["INTJ", "PUNCT", "PRON", "VERB", "NOUN", "ADV", "ADV"]
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pattern = Doc(en_vocab, words=words1, pos=pos1)
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matcher = PhraseMatcher(en_vocab, attr="POS")
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matcher.add("TEST", [pattern])
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doc = Doc(en_vocab, words=words2, pos=pos2)
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matches = matcher(doc)
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assert len(matches) == 1
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match_id, start, end = matches[0]
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assert match_id == en_vocab.strings["TEST"]
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assert start == 2
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assert end == 5
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def test_phrase_matcher_string_attrs_negative(en_vocab):
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"""Test that token with the control codes as ORTH are *not* matched."""
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words1 = ["I", "like", "cats"]
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pos1 = ["PRON", "VERB", "NOUN"]
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words2 = ["matcher:POS-PRON", "matcher:POS-VERB", "matcher:POS-NOUN"]
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pos2 = ["X", "X", "X"]
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pattern = Doc(en_vocab, words=words1, pos=pos1)
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matcher = PhraseMatcher(en_vocab, attr="POS")
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matcher.add("TEST", [pattern])
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doc = Doc(en_vocab, words=words2, pos=pos2)
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matches = matcher(doc)
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assert len(matches) == 0
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def test_phrase_matcher_bool_attrs(en_vocab):
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words1 = ["Hello", "world", "!"]
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words2 = ["No", "problem", ",", "he", "said", "."]
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pattern = Doc(en_vocab, words=words1)
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matcher = PhraseMatcher(en_vocab, attr="IS_PUNCT")
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matcher.add("TEST", [pattern])
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doc = Doc(en_vocab, words=words2)
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matches = matcher(doc)
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assert len(matches) == 2
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match_id1, start1, end1 = matches[0]
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match_id2, start2, end2 = matches[1]
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assert match_id1 == en_vocab.strings["TEST"]
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assert match_id2 == en_vocab.strings["TEST"]
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assert start1 == 0
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assert end1 == 3
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assert start2 == 3
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assert end2 == 6
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def test_phrase_matcher_validation(en_vocab):
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doc1 = Doc(en_vocab, words=["Test"])
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doc1[0].dep_ = "ROOT"
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doc2 = Doc(en_vocab, words=["Test"])
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doc2[0].tag_ = "TAG"
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doc2[0].pos_ = "X"
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doc2[0].set_morph("Feat=Val")
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doc3 = Doc(en_vocab, words=["Test"])
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matcher = PhraseMatcher(en_vocab, validate=True)
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with pytest.warns(UserWarning):
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matcher.add("TEST1", [doc1])
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with pytest.warns(UserWarning):
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matcher.add("TEST2", [doc2])
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with warnings.catch_warnings():
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warnings.simplefilter("error")
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matcher.add("TEST3", [doc3])
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matcher = PhraseMatcher(en_vocab, attr="POS", validate=True)
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with warnings.catch_warnings():
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warnings.simplefilter("error")
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matcher.add("TEST4", [doc2])
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def test_attr_validation(en_vocab):
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with pytest.raises(ValueError):
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PhraseMatcher(en_vocab, attr="UNSUPPORTED")
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def test_attr_pipeline_checks(en_vocab):
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doc1 = Doc(en_vocab, words=["Test"])
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doc1[0].dep_ = "ROOT"
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doc2 = Doc(en_vocab, words=["Test"])
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doc2[0].tag_ = "TAG"
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doc2[0].pos_ = "X"
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doc2[0].set_morph("Feat=Val")
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doc2[0].lemma_ = "LEMMA"
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doc3 = Doc(en_vocab, words=["Test"])
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# DEP requires DEP
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matcher = PhraseMatcher(en_vocab, attr="DEP")
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matcher.add("TEST1", [doc1])
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with pytest.raises(ValueError):
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matcher.add("TEST2", [doc2])
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with pytest.raises(ValueError):
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matcher.add("TEST3", [doc3])
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# TAG, POS, LEMMA require those values
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for attr in ("TAG", "POS", "LEMMA"):
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matcher = PhraseMatcher(en_vocab, attr=attr)
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matcher.add("TEST2", [doc2])
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with pytest.raises(ValueError):
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matcher.add("TEST1", [doc1])
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with pytest.raises(ValueError):
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matcher.add("TEST3", [doc3])
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# TEXT/ORTH only require tokens
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matcher = PhraseMatcher(en_vocab, attr="ORTH")
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matcher.add("TEST3", [doc3])
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matcher = PhraseMatcher(en_vocab, attr="TEXT")
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matcher.add("TEST3", [doc3])
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def test_phrase_matcher_callback(en_vocab):
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mock = Mock()
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doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
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pattern = Doc(en_vocab, words=["Google", "Now"])
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matcher = PhraseMatcher(en_vocab)
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matcher.add("COMPANY", [pattern], on_match=mock)
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matches = matcher(doc)
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mock.assert_called_once_with(matcher, doc, 0, matches)
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def test_phrase_matcher_remove_overlapping_patterns(en_vocab):
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matcher = PhraseMatcher(en_vocab)
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pattern1 = Doc(en_vocab, words=["this"])
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pattern2 = Doc(en_vocab, words=["this", "is"])
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pattern3 = Doc(en_vocab, words=["this", "is", "a"])
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pattern4 = Doc(en_vocab, words=["this", "is", "a", "word"])
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matcher.add("THIS", [pattern1, pattern2, pattern3, pattern4])
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matcher.remove("THIS")
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def test_phrase_matcher_basic_check(en_vocab):
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matcher = PhraseMatcher(en_vocab)
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# Potential mistake: pass in pattern instead of list of patterns
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pattern = Doc(en_vocab, words=["hello", "world"])
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with pytest.raises(ValueError):
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matcher.add("TEST", pattern)
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def test_phrase_matcher_pickle(en_vocab):
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matcher = PhraseMatcher(en_vocab)
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mock = Mock()
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matcher.add("TEST", [Doc(en_vocab, words=["test"])])
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matcher.add("TEST2", [Doc(en_vocab, words=["test2"])], on_match=mock)
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doc = Doc(en_vocab, words=["these", "are", "tests", ":", "test", "test2"])
|
|
assert len(matcher) == 2
|
|
|
|
b = srsly.pickle_dumps(matcher)
|
|
matcher_unpickled = srsly.pickle_loads(b)
|
|
|
|
# call after pickling to avoid recursion error related to mock
|
|
matches = matcher(doc)
|
|
matches_unpickled = matcher_unpickled(doc)
|
|
|
|
assert len(matcher) == len(matcher_unpickled)
|
|
assert matches == matches_unpickled
|
|
|
|
# clunky way to vaguely check that callback is unpickled
|
|
(vocab, docs, callbacks, attr) = matcher_unpickled.__reduce__()[1]
|
|
assert isinstance(callbacks.get("TEST2"), Mock)
|
|
|
|
|
|
def test_phrase_matcher_as_spans(en_vocab):
|
|
"""Test the new as_spans=True API."""
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("A", [Doc(en_vocab, words=["hello", "world"])])
|
|
matcher.add("B", [Doc(en_vocab, words=["test"])])
|
|
doc = Doc(en_vocab, words=["...", "hello", "world", "this", "is", "a", "test"])
|
|
matches = matcher(doc, as_spans=True)
|
|
assert len(matches) == 2
|
|
assert isinstance(matches[0], Span)
|
|
assert matches[0].text == "hello world"
|
|
assert matches[0].label_ == "A"
|
|
assert isinstance(matches[1], Span)
|
|
assert matches[1].text == "test"
|
|
assert matches[1].label_ == "B"
|
|
|
|
|
|
def test_phrase_matcher_deprecated(en_vocab):
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("TEST", [Doc(en_vocab, words=["helllo"])])
|
|
doc = Doc(en_vocab, words=["hello", "world"])
|
|
with pytest.warns(DeprecationWarning) as record:
|
|
for _ in matcher.pipe([doc]):
|
|
pass
|
|
assert record.list
|
|
assert "spaCy v3.0" in str(record.list[0].message)
|
|
|
|
|
|
@pytest.mark.parametrize("attr", ["SENT_START", "IS_SENT_START"])
|
|
def test_phrase_matcher_sent_start(en_vocab, attr):
|
|
_ = PhraseMatcher(en_vocab, attr=attr) # noqa: F841
|
|
|
|
|
|
def test_span_in_phrasematcher(en_vocab):
|
|
"""Ensure that PhraseMatcher accepts Span and Doc as input"""
|
|
# fmt: off
|
|
words = ["I", "like", "Spans", "and", "Docs", "in", "my", "input", ",", "and", "nothing", "else", "."]
|
|
# fmt: on
|
|
doc = Doc(en_vocab, words=words)
|
|
span = doc[:8]
|
|
pattern = Doc(en_vocab, words=["Spans", "and", "Docs"])
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("SPACY", [pattern])
|
|
matches_doc = matcher(doc)
|
|
matches_span = matcher(span)
|
|
assert len(matches_doc) == 1
|
|
assert len(matches_span) == 1
|
|
|
|
|
|
def test_span_v_doc_in_phrasematcher(en_vocab):
|
|
"""Ensure that PhraseMatcher only returns matches in input Span and not in entire Doc"""
|
|
# fmt: off
|
|
words = [
|
|
"I", "like", "Spans", "and", "Docs", "in", "my", "input", ",", "Spans",
|
|
"and", "Docs", "in", "my", "matchers", "," "and", "Spans", "and", "Docs",
|
|
"everywhere", "."
|
|
]
|
|
# fmt: on
|
|
doc = Doc(en_vocab, words=words)
|
|
span = doc[9:15] # second clause
|
|
pattern = Doc(en_vocab, words=["Spans", "and", "Docs"])
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("SPACY", [pattern])
|
|
matches_doc = matcher(doc)
|
|
matches_span = matcher(span)
|
|
assert len(matches_doc) == 3
|
|
assert len(matches_span) == 1
|