import pytest 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 EntityRuler PhraseMatcher is deserialized correctly using the method from_disk when the EntityRuler argument phrase_matcher_attr is specified. """ text = "Spacy is a python library for nlp" nlp = English() patterns = [{"label": "PYTHON_LIB", "pattern": "spacy", "id": "spaCy"}] ruler = nlp.add_pipe("entity_ruler", config={"phrase_matcher_attr": "LOWER"}) 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").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 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_add_new_api(en_vocab): doc = Doc(en_vocab, words=["a", "b"]) patterns = [Doc(en_vocab, words=["a"]), Doc(en_vocab, words=["a", "b"])] matcher = PhraseMatcher(en_vocab) matcher.add("OLD_API", None, *patterns) assert len(matcher(doc)) == 2 matcher = PhraseMatcher(en_vocab) on_match = Mock() matcher.add("OLD_API_CALLBACK", on_match, *patterns) assert len(matcher(doc)) == 2 assert on_match.call_count == 2 # New API: add(key: str, patterns: List[List[dict]], on_match: Callable) matcher = PhraseMatcher(en_vocab) matcher.add("NEW_API", patterns) assert len(matcher(doc)) == 2 matcher = PhraseMatcher(en_vocab) on_match = Mock() matcher.add("NEW_API_CALLBACK", patterns, on_match=on_match) assert len(matcher(doc)) == 2 assert on_match.call_count == 2 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 pytest.warns(None) as record: matcher.add("TEST3", [doc3]) assert not record.list matcher = PhraseMatcher(en_vocab, attr="POS", validate=True) with pytest.warns(None) as record: matcher.add("TEST4", [doc2]) assert not record.list 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) @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