spaCy/spacy/tests/matcher/test_phrase_matcher.py
Adriane Boyd cae4589f5a
Replace EntityRuler with SpanRuler implementation (#11320)
* Replace EntityRuler with SpanRuler implementation

Remove `EntityRuler` and rename the `SpanRuler`-based
`future_entity_ruler` to `entity_ruler`.

Main changes:

* It is no longer possible to load patterns on init as with
`EntityRuler(patterns=)`.
* The older serialization formats (`patterns.jsonl`) are no longer
supported and the related tests are removed.
* The config settings are only stored in the config, not in the
serialized component (in particular the `phrase_matcher_attr` and
overwrite settings).

* Add migration guide to EntityRuler API docs

* docs update

* Minor edit

Co-authored-by: svlandeg <svlandeg@github.com>
2022-10-24 09:11:35 +02:00

496 lines
17 KiB
Python

import pytest
import warnings
import srsly
from mock import Mock
from spacy.lang.en import English
from spacy.matcher import PhraseMatcher, Matcher
from spacy.tokens import Doc, Span
from spacy.vocab import Vocab
from ..util import make_tempdir
@pytest.mark.issue(3248)
def test_issue3248_1():
"""Test that the PhraseMatcher correctly reports its number of rules, not
total number of patterns."""
nlp = English()
matcher = PhraseMatcher(nlp.vocab)
matcher.add("TEST1", [nlp("a"), nlp("b"), nlp("c")])
matcher.add("TEST2", [nlp("d")])
assert len(matcher) == 2
@pytest.mark.issue(3331)
def test_issue3331(en_vocab):
"""Test that duplicate patterns for different rules result in multiple
matches, one per rule.
"""
matcher = PhraseMatcher(en_vocab)
matcher.add("A", [Doc(en_vocab, words=["Barack", "Obama"])])
matcher.add("B", [Doc(en_vocab, words=["Barack", "Obama"])])
doc = Doc(en_vocab, words=["Barack", "Obama", "lifts", "America"])
matches = matcher(doc)
assert len(matches) == 2
match_ids = [en_vocab.strings[matches[0][0]], en_vocab.strings[matches[1][0]]]
assert sorted(match_ids) == ["A", "B"]
@pytest.mark.issue(3972)
def test_issue3972(en_vocab):
"""Test that the PhraseMatcher returns duplicates for duplicate match IDs."""
matcher = PhraseMatcher(en_vocab)
matcher.add("A", [Doc(en_vocab, words=["New", "York"])])
matcher.add("B", [Doc(en_vocab, words=["New", "York"])])
doc = Doc(en_vocab, words=["I", "live", "in", "New", "York"])
matches = matcher(doc)
assert len(matches) == 2
# We should have a match for each of the two rules
found_ids = [en_vocab.strings[ent_id] for (ent_id, _, _) in matches]
assert "A" in found_ids
assert "B" in found_ids
@pytest.mark.issue(4002)
def test_issue4002(en_vocab):
"""Test that the PhraseMatcher can match on overwritten NORM attributes."""
matcher = PhraseMatcher(en_vocab, attr="NORM")
pattern1 = Doc(en_vocab, words=["c", "d"])
assert [t.norm_ for t in pattern1] == ["c", "d"]
matcher.add("TEST", [pattern1])
doc = Doc(en_vocab, words=["a", "b", "c", "d"])
assert [t.norm_ for t in doc] == ["a", "b", "c", "d"]
matches = matcher(doc)
assert len(matches) == 1
matcher = PhraseMatcher(en_vocab, attr="NORM")
pattern2 = Doc(en_vocab, words=["1", "2"])
pattern2[0].norm_ = "c"
pattern2[1].norm_ = "d"
assert [t.norm_ for t in pattern2] == ["c", "d"]
matcher.add("TEST", [pattern2])
matches = matcher(doc)
assert len(matches) == 1
@pytest.mark.issue(4373)
def test_issue4373():
"""Test that PhraseMatcher.vocab can be accessed (like Matcher.vocab)."""
matcher = Matcher(Vocab())
assert isinstance(matcher.vocab, Vocab)
matcher = PhraseMatcher(Vocab())
assert isinstance(matcher.vocab, Vocab)
@pytest.mark.issue(4651)
def test_issue4651_with_phrase_matcher_attr():
"""Test that the entity_ruler PhraseMatcher is deserialized correctly using
the method from_disk when the entity_ruler argument phrase_matcher_attr is
specified.
"""
text = "Spacy is a python library for nlp"
nlp = English()
patterns = [{"label": "PYTHON_LIB", "pattern": "spacy", "id": "spaCy"}]
config = {"phrase_matcher_attr": "LOWER"}
ruler = nlp.add_pipe("entity_ruler", config=config)
ruler.add_patterns(patterns)
doc = nlp(text)
res = [(ent.text, ent.label_, ent.ent_id_) for ent in doc.ents]
nlp_reloaded = English()
with make_tempdir() as d:
file_path = d / "entityruler"
ruler.to_disk(file_path)
nlp_reloaded.add_pipe("entity_ruler", config=config).from_disk(file_path)
doc_reloaded = nlp_reloaded(text)
res_reloaded = [(ent.text, ent.label_, ent.ent_id_) for ent in doc_reloaded.ents]
assert res == res_reloaded
@pytest.mark.issue(6839)
def test_issue6839(en_vocab):
"""Ensure that PhraseMatcher accepts Span 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 = matcher(span)
assert matches
@pytest.mark.issue(10643)
def test_issue10643(en_vocab):
"""Ensure overlapping terms can be removed from PhraseMatcher"""
# fmt: off
words = ["Only", "save", "out", "the", "binary", "data", "for", "the", "individual", "components", "."]
# fmt: on
doc = Doc(en_vocab, words=words)
terms = {
"0": Doc(en_vocab, words=["binary"]),
"1": Doc(en_vocab, words=["binary", "data"]),
}
matcher = PhraseMatcher(en_vocab)
for match_id, term in terms.items():
matcher.add(match_id, [term])
matches = matcher(doc)
assert matches == [(en_vocab.strings["0"], 4, 5), (en_vocab.strings["1"], 4, 6)]
matcher.remove("0")
assert len(matcher) == 1
new_matches = matcher(doc)
assert new_matches == [(en_vocab.strings["1"], 4, 6)]
matcher.remove("1")
assert len(matcher) == 0
no_matches = matcher(doc)
assert not no_matches
def test_matcher_phrase_matcher(en_vocab):
doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
# intermediate phrase
pattern = Doc(en_vocab, words=["Google", "Now"])
matcher = PhraseMatcher(en_vocab)
matcher.add("COMPANY", [pattern])
assert len(matcher(doc)) == 1
# initial token
pattern = Doc(en_vocab, words=["I"])
matcher = PhraseMatcher(en_vocab)
matcher.add("I", [pattern])
assert len(matcher(doc)) == 1
# initial phrase
pattern = Doc(en_vocab, words=["I", "like"])
matcher = PhraseMatcher(en_vocab)
matcher.add("ILIKE", [pattern])
assert len(matcher(doc)) == 1
# final token
pattern = Doc(en_vocab, words=["best"])
matcher = PhraseMatcher(en_vocab)
matcher.add("BEST", [pattern])
assert len(matcher(doc)) == 1
# final phrase
pattern = Doc(en_vocab, words=["Now", "best"])
matcher = PhraseMatcher(en_vocab)
matcher.add("NOWBEST", [pattern])
assert len(matcher(doc)) == 1
def test_phrase_matcher_length(en_vocab):
matcher = PhraseMatcher(en_vocab)
assert len(matcher) == 0
matcher.add("TEST", [Doc(en_vocab, words=["test"])])
assert len(matcher) == 1
matcher.add("TEST2", [Doc(en_vocab, words=["test2"])])
assert len(matcher) == 2
def test_phrase_matcher_contains(en_vocab):
matcher = PhraseMatcher(en_vocab)
matcher.add("TEST", [Doc(en_vocab, words=["test"])])
assert "TEST" in matcher
assert "TEST2" not in matcher
def test_phrase_matcher_repeated_add(en_vocab):
matcher = PhraseMatcher(en_vocab)
# match ID only gets added once
matcher.add("TEST", [Doc(en_vocab, words=["like"])])
matcher.add("TEST", [Doc(en_vocab, words=["like"])])
matcher.add("TEST", [Doc(en_vocab, words=["like"])])
matcher.add("TEST", [Doc(en_vocab, words=["like"])])
doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
assert "TEST" in matcher
assert "TEST2" not in matcher
assert len(matcher(doc)) == 1
def test_phrase_matcher_remove(en_vocab):
matcher = PhraseMatcher(en_vocab)
matcher.add("TEST1", [Doc(en_vocab, words=["like"])])
matcher.add("TEST2", [Doc(en_vocab, words=["best"])])
doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
assert "TEST1" in matcher
assert "TEST2" in matcher
assert "TEST3" not in matcher
assert len(matcher(doc)) == 2
matcher.remove("TEST1")
assert "TEST1" not in matcher
assert "TEST2" in matcher
assert "TEST3" not in matcher
assert len(matcher(doc)) == 1
matcher.remove("TEST2")
assert "TEST1" not in matcher
assert "TEST2" not in matcher
assert "TEST3" not in matcher
assert len(matcher(doc)) == 0
with pytest.raises(KeyError):
matcher.remove("TEST3")
assert "TEST1" not in matcher
assert "TEST2" not in matcher
assert "TEST3" not in matcher
assert len(matcher(doc)) == 0
def test_phrase_matcher_overlapping_with_remove(en_vocab):
matcher = PhraseMatcher(en_vocab)
matcher.add("TEST", [Doc(en_vocab, words=["like"])])
# TEST2 is added alongside TEST
matcher.add("TEST2", [Doc(en_vocab, words=["like"])])
doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
assert "TEST" in matcher
assert len(matcher) == 2
assert len(matcher(doc)) == 2
# removing TEST does not remove the entry for TEST2
matcher.remove("TEST")
assert "TEST" not in matcher
assert len(matcher) == 1
assert len(matcher(doc)) == 1
assert matcher(doc)[0][0] == en_vocab.strings["TEST2"]
# removing TEST2 removes all
matcher.remove("TEST2")
assert "TEST2" not in matcher
assert len(matcher) == 0
assert len(matcher(doc)) == 0
def test_phrase_matcher_string_attrs(en_vocab):
words1 = ["I", "like", "cats"]
pos1 = ["PRON", "VERB", "NOUN"]
words2 = ["Yes", ",", "you", "hate", "dogs", "very", "much"]
pos2 = ["INTJ", "PUNCT", "PRON", "VERB", "NOUN", "ADV", "ADV"]
pattern = Doc(en_vocab, words=words1, pos=pos1)
matcher = PhraseMatcher(en_vocab, attr="POS")
matcher.add("TEST", [pattern])
doc = Doc(en_vocab, words=words2, pos=pos2)
matches = matcher(doc)
assert len(matches) == 1
match_id, start, end = matches[0]
assert match_id == en_vocab.strings["TEST"]
assert start == 2
assert end == 5
def test_phrase_matcher_string_attrs_negative(en_vocab):
"""Test that token with the control codes as ORTH are *not* matched."""
words1 = ["I", "like", "cats"]
pos1 = ["PRON", "VERB", "NOUN"]
words2 = ["matcher:POS-PRON", "matcher:POS-VERB", "matcher:POS-NOUN"]
pos2 = ["X", "X", "X"]
pattern = Doc(en_vocab, words=words1, pos=pos1)
matcher = PhraseMatcher(en_vocab, attr="POS")
matcher.add("TEST", [pattern])
doc = Doc(en_vocab, words=words2, pos=pos2)
matches = matcher(doc)
assert len(matches) == 0
def test_phrase_matcher_bool_attrs(en_vocab):
words1 = ["Hello", "world", "!"]
words2 = ["No", "problem", ",", "he", "said", "."]
pattern = Doc(en_vocab, words=words1)
matcher = PhraseMatcher(en_vocab, attr="IS_PUNCT")
matcher.add("TEST", [pattern])
doc = Doc(en_vocab, words=words2)
matches = matcher(doc)
assert len(matches) == 2
match_id1, start1, end1 = matches[0]
match_id2, start2, end2 = matches[1]
assert match_id1 == en_vocab.strings["TEST"]
assert match_id2 == en_vocab.strings["TEST"]
assert start1 == 0
assert end1 == 3
assert start2 == 3
assert end2 == 6
def test_phrase_matcher_validation(en_vocab):
doc1 = Doc(en_vocab, words=["Test"])
doc1[0].dep_ = "ROOT"
doc2 = Doc(en_vocab, words=["Test"])
doc2[0].tag_ = "TAG"
doc2[0].pos_ = "X"
doc2[0].set_morph("Feat=Val")
doc3 = Doc(en_vocab, words=["Test"])
matcher = PhraseMatcher(en_vocab, validate=True)
with pytest.warns(UserWarning):
matcher.add("TEST1", [doc1])
with pytest.warns(UserWarning):
matcher.add("TEST2", [doc2])
with warnings.catch_warnings():
warnings.simplefilter("error")
matcher.add("TEST3", [doc3])
matcher = PhraseMatcher(en_vocab, attr="POS", validate=True)
with warnings.catch_warnings():
warnings.simplefilter("error")
matcher.add("TEST4", [doc2])
def test_attr_validation(en_vocab):
with pytest.raises(ValueError):
PhraseMatcher(en_vocab, attr="UNSUPPORTED")
def test_attr_pipeline_checks(en_vocab):
doc1 = Doc(en_vocab, words=["Test"])
doc1[0].dep_ = "ROOT"
doc2 = Doc(en_vocab, words=["Test"])
doc2[0].tag_ = "TAG"
doc2[0].pos_ = "X"
doc2[0].set_morph("Feat=Val")
doc2[0].lemma_ = "LEMMA"
doc3 = Doc(en_vocab, words=["Test"])
# DEP requires DEP
matcher = PhraseMatcher(en_vocab, attr="DEP")
matcher.add("TEST1", [doc1])
with pytest.raises(ValueError):
matcher.add("TEST2", [doc2])
with pytest.raises(ValueError):
matcher.add("TEST3", [doc3])
# TAG, POS, LEMMA require those values
for attr in ("TAG", "POS", "LEMMA"):
matcher = PhraseMatcher(en_vocab, attr=attr)
matcher.add("TEST2", [doc2])
with pytest.raises(ValueError):
matcher.add("TEST1", [doc1])
with pytest.raises(ValueError):
matcher.add("TEST3", [doc3])
# TEXT/ORTH only require tokens
matcher = PhraseMatcher(en_vocab, attr="ORTH")
matcher.add("TEST3", [doc3])
matcher = PhraseMatcher(en_vocab, attr="TEXT")
matcher.add("TEST3", [doc3])
def test_phrase_matcher_callback(en_vocab):
mock = Mock()
doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
pattern = Doc(en_vocab, words=["Google", "Now"])
matcher = PhraseMatcher(en_vocab)
matcher.add("COMPANY", [pattern], on_match=mock)
matches = matcher(doc)
mock.assert_called_once_with(matcher, doc, 0, matches)
def test_phrase_matcher_remove_overlapping_patterns(en_vocab):
matcher = PhraseMatcher(en_vocab)
pattern1 = Doc(en_vocab, words=["this"])
pattern2 = Doc(en_vocab, words=["this", "is"])
pattern3 = Doc(en_vocab, words=["this", "is", "a"])
pattern4 = Doc(en_vocab, words=["this", "is", "a", "word"])
matcher.add("THIS", [pattern1, pattern2, pattern3, pattern4])
matcher.remove("THIS")
def test_phrase_matcher_basic_check(en_vocab):
matcher = PhraseMatcher(en_vocab)
# Potential mistake: pass in pattern instead of list of patterns
pattern = Doc(en_vocab, words=["hello", "world"])
with pytest.raises(ValueError):
matcher.add("TEST", pattern)
def test_phrase_matcher_pickle(en_vocab):
matcher = PhraseMatcher(en_vocab)
mock = Mock()
matcher.add("TEST", [Doc(en_vocab, words=["test"])])
matcher.add("TEST2", [Doc(en_vocab, words=["test2"])], on_match=mock)
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)
def test_phrase_matcher_non_doc(en_vocab):
matcher = PhraseMatcher(en_vocab)
doc = Doc(en_vocab, words=["hello", "world"])
with pytest.raises(ValueError):
matcher.add("TEST", [doc, "junk"])
@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