mirror of https://github.com/explosion/spaCy.git
910 lines
29 KiB
Python
910 lines
29 KiB
Python
import pytest
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from mock import Mock
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from spacy.matcher import Matcher
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from spacy.tokens import Doc, Span, Token
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from ..doc.test_underscore import clean_underscore # noqa: F401
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@pytest.fixture
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def matcher(en_vocab):
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rules = {
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"JS": [[{"ORTH": "JavaScript"}]],
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"GoogleNow": [[{"ORTH": "Google"}, {"ORTH": "Now"}]],
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"Java": [[{"LOWER": "java"}]],
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}
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matcher = Matcher(en_vocab)
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for key, patterns in rules.items():
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matcher.add(key, patterns)
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return matcher
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def test_matcher_from_api_docs(en_vocab):
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matcher = Matcher(en_vocab)
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pattern = [{"ORTH": "test"}]
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assert len(matcher) == 0
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matcher.add("Rule", [pattern])
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assert len(matcher) == 1
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matcher.remove("Rule")
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assert "Rule" not in matcher
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matcher.add("Rule", [pattern])
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assert "Rule" in matcher
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on_match, patterns = matcher.get("Rule")
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assert len(patterns[0])
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def test_matcher_empty_patterns_warns(en_vocab):
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matcher = Matcher(en_vocab)
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assert len(matcher) == 0
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doc = Doc(en_vocab, words=["This", "is", "quite", "something"])
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with pytest.warns(UserWarning):
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matcher(doc)
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assert len(doc.ents) == 0
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def test_matcher_from_usage_docs(en_vocab):
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text = "Wow 😀 This is really cool! 😂 😂"
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doc = Doc(en_vocab, words=text.split(" "))
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pos_emoji = ["😀", "😃", "😂", "🤣", "😊", "😍"]
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pos_patterns = [[{"ORTH": emoji}] for emoji in pos_emoji]
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def label_sentiment(matcher, doc, i, matches):
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match_id, start, end = matches[i]
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if doc.vocab.strings[match_id] == "HAPPY":
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doc.sentiment += 0.1
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span = doc[start:end]
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with doc.retokenize() as retokenizer:
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retokenizer.merge(span)
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token = doc[start]
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token.vocab[token.text].norm_ = "happy emoji"
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matcher = Matcher(en_vocab)
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matcher.add("HAPPY", pos_patterns, on_match=label_sentiment)
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matcher(doc)
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assert doc.sentiment != 0
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assert doc[1].norm_ == "happy emoji"
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def test_matcher_len_contains(matcher):
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assert len(matcher) == 3
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matcher.add("TEST", [[{"ORTH": "test"}]])
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assert "TEST" in matcher
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assert "TEST2" not in matcher
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def test_matcher_add_new_api(en_vocab):
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doc = Doc(en_vocab, words=["a", "b"])
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patterns = [[{"TEXT": "a"}], [{"TEXT": "a"}, {"TEXT": "b"}]]
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matcher = Matcher(en_vocab)
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on_match = Mock()
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matcher = Matcher(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 = Matcher(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_matcher_no_match(matcher):
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doc = Doc(matcher.vocab, words=["I", "like", "cheese", "."])
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assert matcher(doc) == []
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def test_matcher_match_start(matcher):
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doc = Doc(matcher.vocab, words=["JavaScript", "is", "good"])
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assert matcher(doc) == [(matcher.vocab.strings["JS"], 0, 1)]
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def test_matcher_match_end(matcher):
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words = ["I", "like", "java"]
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doc = Doc(matcher.vocab, words=words)
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assert matcher(doc) == [(doc.vocab.strings["Java"], 2, 3)]
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def test_matcher_match_middle(matcher):
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words = ["I", "like", "Google", "Now", "best"]
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doc = Doc(matcher.vocab, words=words)
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assert matcher(doc) == [(doc.vocab.strings["GoogleNow"], 2, 4)]
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def test_matcher_match_multi(matcher):
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words = ["I", "like", "Google", "Now", "and", "java", "best"]
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doc = Doc(matcher.vocab, words=words)
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assert matcher(doc) == [
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(doc.vocab.strings["GoogleNow"], 2, 4),
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(doc.vocab.strings["Java"], 5, 6),
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]
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@pytest.mark.parametrize(
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"rules,match_locs",
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[
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(
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{
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"GoogleNow": [[{"ORTH": {"FUZZY": "Google"}}, {"ORTH": "Now"}]],
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},
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[(2, 4)],
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),
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(
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{
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"Java": [[{"LOWER": {"FUZZY": "java"}}]],
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},
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[(5, 6)],
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),
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(
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{
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"JS": [[{"ORTH": {"FUZZY": "JavaScript"}}]],
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"GoogleNow": [[{"ORTH": {"FUZZY": "Google"}}, {"ORTH": "Now"}]],
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"Java": [[{"LOWER": {"FUZZY": "java"}}]],
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},
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[(2, 4), (5, 6), (8, 9)],
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),
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# only the second pattern matches (check that predicate keys used for
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# caching don't collide)
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(
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{
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"A": [[{"ORTH": {"FUZZY": "Javascripts"}}]],
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"B": [[{"ORTH": {"FUZZY5": "Javascripts"}}]],
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},
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[(8, 9)],
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),
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],
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)
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def test_matcher_match_fuzzy(en_vocab, rules, match_locs):
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words = ["They", "like", "Goggle", "Now", "and", "Jav", "but", "not", "JvvaScrpt"]
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doc = Doc(en_vocab, words=words)
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matcher = Matcher(en_vocab)
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for key, patterns in rules.items():
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matcher.add(key, patterns)
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assert match_locs == [(start, end) for m_id, start, end in matcher(doc)]
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@pytest.mark.parametrize("set_op", ["IN", "NOT_IN"])
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def test_matcher_match_fuzzy_set_op_longest(en_vocab, set_op):
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rules = {
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"GoogleNow": [[{"ORTH": {"FUZZY": {set_op: ["Google", "Now"]}}, "OP": "+"}]]
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}
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matcher = Matcher(en_vocab)
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for key, patterns in rules.items():
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matcher.add(key, patterns, greedy="LONGEST")
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words = ["They", "like", "Goggle", "Noo"]
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doc = Doc(en_vocab, words=words)
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assert len(matcher(doc)) == 1
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def test_matcher_match_fuzzy_set_multiple(en_vocab):
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rules = {
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"GoogleNow": [
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[
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{
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"ORTH": {"FUZZY": {"IN": ["Google", "Now"]}, "NOT_IN": ["Goggle"]},
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"OP": "+",
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}
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]
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]
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}
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matcher = Matcher(en_vocab)
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for key, patterns in rules.items():
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matcher.add(key, patterns, greedy="LONGEST")
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words = ["They", "like", "Goggle", "Noo"]
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doc = Doc(matcher.vocab, words=words)
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assert matcher(doc) == [
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(doc.vocab.strings["GoogleNow"], 3, 4),
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]
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@pytest.mark.parametrize("fuzzyn", range(1, 10))
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def test_matcher_match_fuzzyn_all_insertions(en_vocab, fuzzyn):
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matcher = Matcher(en_vocab)
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matcher.add("GoogleNow", [[{"ORTH": {f"FUZZY{fuzzyn}": "GoogleNow"}}]])
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# words with increasing edit distance
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words = ["GoogleNow" + "a" * i for i in range(0, 10)]
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doc = Doc(en_vocab, words)
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assert len(matcher(doc)) == fuzzyn + 1
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@pytest.mark.parametrize("fuzzyn", range(1, 6))
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def test_matcher_match_fuzzyn_various_edits(en_vocab, fuzzyn):
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matcher = Matcher(en_vocab)
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matcher.add("GoogleNow", [[{"ORTH": {f"FUZZY{fuzzyn}": "GoogleNow"}}]])
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# words with increasing edit distance of different edit types
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words = [
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"GoogleNow",
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"GoogleNuw",
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"GoogleNuew",
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"GoogleNoweee",
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"GiggleNuw3",
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"gouggle5New",
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]
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doc = Doc(en_vocab, words)
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assert len(matcher(doc)) == fuzzyn + 1
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@pytest.mark.parametrize("greedy", ["FIRST", "LONGEST"])
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@pytest.mark.parametrize("set_op", ["IN", "NOT_IN"])
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def test_matcher_match_fuzzyn_set_op_longest(en_vocab, greedy, set_op):
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rules = {
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"GoogleNow": [[{"ORTH": {"FUZZY2": {set_op: ["Google", "Now"]}}, "OP": "+"}]]
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}
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matcher = Matcher(en_vocab)
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for key, patterns in rules.items():
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matcher.add(key, patterns, greedy=greedy)
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words = ["They", "like", "Goggle", "Noo"]
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doc = Doc(matcher.vocab, words=words)
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spans = matcher(doc, as_spans=True)
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assert len(spans) == 1
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if set_op == "IN":
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assert spans[0].text == "Goggle Noo"
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else:
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assert spans[0].text == "They like"
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def test_matcher_match_fuzzyn_set_multiple(en_vocab):
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rules = {
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"GoogleNow": [
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[
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{
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"ORTH": {"FUZZY1": {"IN": ["Google", "Now"]}, "NOT_IN": ["Goggle"]},
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"OP": "+",
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}
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]
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]
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}
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matcher = Matcher(en_vocab)
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for key, patterns in rules.items():
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matcher.add(key, patterns, greedy="LONGEST")
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words = ["They", "like", "Goggle", "Noo"]
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doc = Doc(matcher.vocab, words=words)
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assert matcher(doc) == [
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(doc.vocab.strings["GoogleNow"], 3, 4),
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]
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def test_matcher_empty_dict(en_vocab):
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"""Test matcher allows empty token specs, meaning match on any token."""
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matcher = Matcher(en_vocab)
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doc = Doc(matcher.vocab, words=["a", "b", "c"])
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matcher.add("A.C", [[{"ORTH": "a"}, {}, {"ORTH": "c"}]])
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matches = matcher(doc)
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assert len(matches) == 1
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assert matches[0][1:] == (0, 3)
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matcher = Matcher(en_vocab)
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matcher.add("A.", [[{"ORTH": "a"}, {}]])
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matches = matcher(doc)
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assert matches[0][1:] == (0, 2)
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def test_matcher_operator_shadow(en_vocab):
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matcher = Matcher(en_vocab)
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doc = Doc(matcher.vocab, words=["a", "b", "c"])
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pattern = [{"ORTH": "a"}, {"IS_ALPHA": True, "OP": "+"}, {"ORTH": "c"}]
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matcher.add("A.C", [pattern])
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matches = matcher(doc)
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assert len(matches) == 1
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assert matches[0][1:] == (0, 3)
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def test_matcher_match_zero(matcher):
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words1 = 'He said , " some words " ...'.split()
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words2 = 'He said , " some three words " ...'.split()
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pattern1 = [
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{"ORTH": '"'},
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{"OP": "!", "IS_PUNCT": True},
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{"OP": "!", "IS_PUNCT": True},
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{"ORTH": '"'},
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]
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pattern2 = [
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{"ORTH": '"'},
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{"IS_PUNCT": True},
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{"IS_PUNCT": True},
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{"IS_PUNCT": True},
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{"ORTH": '"'},
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]
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matcher.add("Quote", [pattern1])
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doc = Doc(matcher.vocab, words=words1)
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assert len(matcher(doc)) == 1
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doc = Doc(matcher.vocab, words=words2)
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assert len(matcher(doc)) == 0
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matcher.add("Quote", [pattern2])
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assert len(matcher(doc)) == 0
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def test_matcher_match_zero_plus(matcher):
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words = 'He said , " some words " ...'.split()
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pattern = [{"ORTH": '"'}, {"OP": "*", "IS_PUNCT": False}, {"ORTH": '"'}]
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matcher = Matcher(matcher.vocab)
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matcher.add("Quote", [pattern])
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doc = Doc(matcher.vocab, words=words)
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assert len(matcher(doc)) == 1
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def test_matcher_match_one_plus(matcher):
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control = Matcher(matcher.vocab)
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control.add("BasicPhilippe", [[{"ORTH": "Philippe"}]])
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doc = Doc(control.vocab, words=["Philippe", "Philippe"])
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m = control(doc)
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assert len(m) == 2
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pattern = [{"ORTH": "Philippe"}, {"ORTH": "Philippe", "OP": "+"}]
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matcher.add("KleenePhilippe", [pattern])
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m = matcher(doc)
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assert len(m) == 1
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def test_matcher_any_token_operator(en_vocab):
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"""Test that patterns with "any token" {} work with operators."""
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matcher = Matcher(en_vocab)
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matcher.add("TEST", [[{"ORTH": "test"}, {"OP": "*"}]])
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doc = Doc(en_vocab, words=["test", "hello", "world"])
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matches = [doc[start:end].text for _, start, end in matcher(doc)]
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assert len(matches) == 3
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assert matches[0] == "test"
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assert matches[1] == "test hello"
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assert matches[2] == "test hello world"
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@pytest.mark.usefixtures("clean_underscore")
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def test_matcher_extension_attribute(en_vocab):
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matcher = Matcher(en_vocab)
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get_is_fruit = lambda token: token.text in ("apple", "banana")
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Token.set_extension("is_fruit", getter=get_is_fruit, force=True)
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pattern = [{"ORTH": "an"}, {"_": {"is_fruit": True}}]
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matcher.add("HAVING_FRUIT", [pattern])
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doc = Doc(en_vocab, words=["an", "apple"])
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matches = matcher(doc)
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assert len(matches) == 1
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doc = Doc(en_vocab, words=["an", "aardvark"])
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matches = matcher(doc)
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assert len(matches) == 0
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def test_matcher_set_value(en_vocab):
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matcher = Matcher(en_vocab)
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pattern = [{"ORTH": {"IN": ["an", "a"]}}]
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matcher.add("A_OR_AN", [pattern])
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doc = Doc(en_vocab, words=["an", "a", "apple"])
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matches = matcher(doc)
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assert len(matches) == 2
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doc = Doc(en_vocab, words=["aardvark"])
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matches = matcher(doc)
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assert len(matches) == 0
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def test_matcher_set_value_operator(en_vocab):
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matcher = Matcher(en_vocab)
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pattern = [{"ORTH": {"IN": ["a", "the"]}, "OP": "?"}, {"ORTH": "house"}]
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matcher.add("DET_HOUSE", [pattern])
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doc = Doc(en_vocab, words=["In", "a", "house"])
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matches = matcher(doc)
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assert len(matches) == 2
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doc = Doc(en_vocab, words=["my", "house"])
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matches = matcher(doc)
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assert len(matches) == 1
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def test_matcher_subset_value_operator(en_vocab):
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matcher = Matcher(en_vocab)
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pattern = [{"MORPH": {"IS_SUBSET": ["Feat=Val", "Feat2=Val2"]}}]
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matcher.add("M", [pattern])
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doc = Doc(en_vocab, words=["a", "b", "c"])
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assert len(matcher(doc)) == 3
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doc[0].set_morph("Feat=Val")
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assert len(matcher(doc)) == 3
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doc[0].set_morph("Feat=Val|Feat2=Val2")
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assert len(matcher(doc)) == 3
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doc[0].set_morph("Feat=Val|Feat2=Val2|Feat3=Val3")
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assert len(matcher(doc)) == 2
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doc[0].set_morph("Feat=Val|Feat2=Val2|Feat3=Val3|Feat4=Val4")
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assert len(matcher(doc)) == 2
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# IS_SUBSET acts like "IN" for attrs other than MORPH
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matcher = Matcher(en_vocab)
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pattern = [{"TAG": {"IS_SUBSET": ["A", "B"]}}]
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matcher.add("M", [pattern])
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doc = Doc(en_vocab, words=["a", "b", "c"])
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doc[0].tag_ = "A"
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assert len(matcher(doc)) == 1
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# IS_SUBSET with an empty list matches nothing
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matcher = Matcher(en_vocab)
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pattern = [{"TAG": {"IS_SUBSET": []}}]
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matcher.add("M", [pattern])
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doc = Doc(en_vocab, words=["a", "b", "c"])
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doc[0].tag_ = "A"
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assert len(matcher(doc)) == 0
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# IS_SUBSET with a list value
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Token.set_extension("ext", default=[])
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matcher = Matcher(en_vocab)
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pattern = [{"_": {"ext": {"IS_SUBSET": ["A", "B"]}}}]
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matcher.add("M", [pattern])
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doc = Doc(en_vocab, words=["a", "b", "c"])
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doc[0]._.ext = ["A"]
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doc[1]._.ext = ["C", "D"]
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assert len(matcher(doc)) == 2
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def test_matcher_superset_value_operator(en_vocab):
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matcher = Matcher(en_vocab)
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pattern = [{"MORPH": {"IS_SUPERSET": ["Feat=Val", "Feat2=Val2", "Feat3=Val3"]}}]
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matcher.add("M", [pattern])
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doc = Doc(en_vocab, words=["a", "b", "c"])
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assert len(matcher(doc)) == 0
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doc[0].set_morph("Feat=Val|Feat2=Val2")
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assert len(matcher(doc)) == 0
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doc[0].set_morph("Feat=Val|Feat2=Val2|Feat3=Val3")
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assert len(matcher(doc)) == 1
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doc[0].set_morph("Feat=Val|Feat2=Val2|Feat3=Val3|Feat4=Val4")
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assert len(matcher(doc)) == 1
|
|
|
|
# IS_SUPERSET with more than one value only matches for MORPH
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"TAG": {"IS_SUPERSET": ["A", "B"]}}]
|
|
matcher.add("M", [pattern])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
doc[0].tag_ = "A"
|
|
assert len(matcher(doc)) == 0
|
|
|
|
# IS_SUPERSET with one value is the same as ==
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"TAG": {"IS_SUPERSET": ["A"]}}]
|
|
matcher.add("M", [pattern])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
doc[0].tag_ = "A"
|
|
assert len(matcher(doc)) == 1
|
|
|
|
# IS_SUPERSET with an empty value matches everything
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"TAG": {"IS_SUPERSET": []}}]
|
|
matcher.add("M", [pattern])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
doc[0].tag_ = "A"
|
|
assert len(matcher(doc)) == 3
|
|
|
|
# IS_SUPERSET with a list value
|
|
Token.set_extension("ext", default=[])
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"_": {"ext": {"IS_SUPERSET": ["A"]}}}]
|
|
matcher.add("M", [pattern])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
doc[0]._.ext = ["A", "B"]
|
|
assert len(matcher(doc)) == 1
|
|
|
|
|
|
def test_matcher_intersect_value_operator(en_vocab):
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"MORPH": {"INTERSECTS": ["Feat=Val", "Feat2=Val2", "Feat3=Val3"]}}]
|
|
matcher.add("M", [pattern])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
assert len(matcher(doc)) == 0
|
|
doc[0].set_morph("Feat=Val")
|
|
assert len(matcher(doc)) == 1
|
|
doc[0].set_morph("Feat=Val|Feat2=Val2")
|
|
assert len(matcher(doc)) == 1
|
|
doc[0].set_morph("Feat=Val|Feat2=Val2|Feat3=Val3")
|
|
assert len(matcher(doc)) == 1
|
|
doc[0].set_morph("Feat=Val|Feat2=Val2|Feat3=Val3|Feat4=Val4")
|
|
assert len(matcher(doc)) == 1
|
|
|
|
# INTERSECTS with a single value is the same as IN
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"TAG": {"INTERSECTS": ["A", "B"]}}]
|
|
matcher.add("M", [pattern])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
doc[0].tag_ = "A"
|
|
assert len(matcher(doc)) == 1
|
|
|
|
# INTERSECTS with an empty pattern list matches nothing
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"TAG": {"INTERSECTS": []}}]
|
|
matcher.add("M", [pattern])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
doc[0].tag_ = "A"
|
|
assert len(matcher(doc)) == 0
|
|
|
|
# INTERSECTS with a list value
|
|
Token.set_extension("ext", default=[])
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"_": {"ext": {"INTERSECTS": ["A", "C"]}}}]
|
|
matcher.add("M", [pattern])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
doc[0]._.ext = ["A", "B"]
|
|
assert len(matcher(doc)) == 1
|
|
|
|
# INTERSECTS matches nothing for iterables that aren't all str or int
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"_": {"ext": {"INTERSECTS": ["Abx", "C"]}}}]
|
|
matcher.add("M", [pattern])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
doc[0]._.ext = [["Abx"], "B"]
|
|
assert len(matcher(doc)) == 0
|
|
doc[0]._.ext = ["Abx", "B"]
|
|
assert len(matcher(doc)) == 1
|
|
|
|
# INTERSECTS with an empty pattern list matches nothing
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"_": {"ext": {"INTERSECTS": []}}}]
|
|
matcher.add("M", [pattern])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
doc[0]._.ext = ["A", "B"]
|
|
assert len(matcher(doc)) == 0
|
|
|
|
# INTERSECTS with an empty value matches nothing
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"_": {"ext": {"INTERSECTS": ["A", "B"]}}}]
|
|
matcher.add("M", [pattern])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
doc[0]._.ext = []
|
|
assert len(matcher(doc)) == 0
|
|
|
|
|
|
def test_matcher_morph_handling(en_vocab):
|
|
# order of features in pattern doesn't matter
|
|
matcher = Matcher(en_vocab)
|
|
pattern1 = [{"MORPH": {"IN": ["Feat1=Val1|Feat2=Val2"]}}]
|
|
pattern2 = [{"MORPH": {"IN": ["Feat2=Val2|Feat1=Val1"]}}]
|
|
matcher.add("M", [pattern1])
|
|
matcher.add("N", [pattern2])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
assert len(matcher(doc)) == 0
|
|
|
|
doc[0].set_morph("Feat2=Val2|Feat1=Val1")
|
|
assert len(matcher(doc)) == 2
|
|
doc[0].set_morph("Feat1=Val1|Feat2=Val2")
|
|
assert len(matcher(doc)) == 2
|
|
|
|
# multiple values are split
|
|
matcher = Matcher(en_vocab)
|
|
pattern1 = [{"MORPH": {"IS_SUPERSET": ["Feat1=Val1", "Feat2=Val2"]}}]
|
|
pattern2 = [{"MORPH": {"IS_SUPERSET": ["Feat1=Val1", "Feat1=Val3", "Feat2=Val2"]}}]
|
|
matcher.add("M", [pattern1])
|
|
matcher.add("N", [pattern2])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
assert len(matcher(doc)) == 0
|
|
|
|
doc[0].set_morph("Feat2=Val2,Val3|Feat1=Val1")
|
|
assert len(matcher(doc)) == 1
|
|
doc[0].set_morph("Feat1=Val1,Val3|Feat2=Val2")
|
|
assert len(matcher(doc)) == 2
|
|
|
|
|
|
def test_matcher_regex(en_vocab):
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"ORTH": {"REGEX": r"(?:a|an)"}}]
|
|
matcher.add("A_OR_AN", [pattern])
|
|
doc = Doc(en_vocab, words=["an", "a", "hi"])
|
|
matches = matcher(doc)
|
|
assert len(matches) == 2
|
|
doc = Doc(en_vocab, words=["bye"])
|
|
matches = matcher(doc)
|
|
assert len(matches) == 0
|
|
|
|
|
|
def test_matcher_regex_set_in(en_vocab):
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"ORTH": {"REGEX": {"IN": [r"(?:a)", r"(?:an)"]}}}]
|
|
matcher.add("A_OR_AN", [pattern])
|
|
doc = Doc(en_vocab, words=["an", "a", "hi"])
|
|
matches = matcher(doc)
|
|
assert len(matches) == 2
|
|
doc = Doc(en_vocab, words=["bye"])
|
|
matches = matcher(doc)
|
|
assert len(matches) == 0
|
|
|
|
|
|
def test_matcher_regex_set_not_in(en_vocab):
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"ORTH": {"REGEX": {"NOT_IN": [r"(?:a)", r"(?:an)"]}}}]
|
|
matcher.add("A_OR_AN", [pattern])
|
|
doc = Doc(en_vocab, words=["an", "a", "hi"])
|
|
matches = matcher(doc)
|
|
assert len(matches) == 1
|
|
doc = Doc(en_vocab, words=["bye"])
|
|
matches = matcher(doc)
|
|
assert len(matches) == 1
|
|
|
|
|
|
def test_matcher_regex_shape(en_vocab):
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"SHAPE": {"REGEX": r"^[^x]+$"}}]
|
|
matcher.add("NON_ALPHA", [pattern])
|
|
doc = Doc(en_vocab, words=["99", "problems", "!"])
|
|
matches = matcher(doc)
|
|
assert len(matches) == 2
|
|
doc = Doc(en_vocab, words=["bye"])
|
|
matches = matcher(doc)
|
|
assert len(matches) == 0
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"cmp, bad",
|
|
[
|
|
("==", ["a", "aaa"]),
|
|
("!=", ["aa"]),
|
|
(">=", ["a"]),
|
|
("<=", ["aaa"]),
|
|
(">", ["a", "aa"]),
|
|
("<", ["aa", "aaa"]),
|
|
],
|
|
)
|
|
def test_matcher_compare_length(en_vocab, cmp, bad):
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"LENGTH": {cmp: 2}}]
|
|
matcher.add("LENGTH_COMPARE", [pattern])
|
|
doc = Doc(en_vocab, words=["a", "aa", "aaa"])
|
|
matches = matcher(doc)
|
|
assert len(matches) == len(doc) - len(bad)
|
|
doc = Doc(en_vocab, words=bad)
|
|
matches = matcher(doc)
|
|
assert len(matches) == 0
|
|
|
|
|
|
def test_matcher_extension_set_membership(en_vocab):
|
|
matcher = Matcher(en_vocab)
|
|
get_reversed = lambda token: "".join(reversed(token.text))
|
|
Token.set_extension("reversed", getter=get_reversed, force=True)
|
|
pattern = [{"_": {"reversed": {"IN": ["eyb", "ih"]}}}]
|
|
matcher.add("REVERSED", [pattern])
|
|
doc = Doc(en_vocab, words=["hi", "bye", "hello"])
|
|
matches = matcher(doc)
|
|
assert len(matches) == 2
|
|
doc = Doc(en_vocab, words=["aardvark"])
|
|
matches = matcher(doc)
|
|
assert len(matches) == 0
|
|
|
|
|
|
def test_matcher_extension_in_set_predicate(en_vocab):
|
|
matcher = Matcher(en_vocab)
|
|
Token.set_extension("ext", default=[])
|
|
pattern = [{"_": {"ext": {"IN": ["A", "C"]}}}]
|
|
matcher.add("M", [pattern])
|
|
doc = Doc(en_vocab, words=["a", "b", "c"])
|
|
|
|
# The IN predicate expects an exact match between the
|
|
# extension value and one of the pattern's values.
|
|
doc[0]._.ext = ["A", "B"]
|
|
assert len(matcher(doc)) == 0
|
|
|
|
doc[0]._.ext = ["A"]
|
|
assert len(matcher(doc)) == 0
|
|
|
|
doc[0]._.ext = "A"
|
|
assert len(matcher(doc)) == 1
|
|
|
|
|
|
def test_matcher_basic_check(en_vocab):
|
|
matcher = Matcher(en_vocab)
|
|
# Potential mistake: pass in pattern instead of list of patterns
|
|
pattern = [{"TEXT": "hello"}, {"TEXT": "world"}]
|
|
with pytest.raises(ValueError):
|
|
matcher.add("TEST", pattern)
|
|
|
|
|
|
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 = Matcher(en_vocab)
|
|
matcher.add("TEST", [[{"DEP": "a"}]])
|
|
matcher(doc1)
|
|
with pytest.raises(ValueError):
|
|
matcher(doc2)
|
|
with pytest.raises(ValueError):
|
|
matcher(doc3)
|
|
# errors can be suppressed if desired
|
|
matcher(doc2, allow_missing=True)
|
|
matcher(doc3, allow_missing=True)
|
|
# TAG, POS, LEMMA require those values
|
|
for attr in ("TAG", "POS", "LEMMA"):
|
|
matcher = Matcher(en_vocab)
|
|
matcher.add("TEST", [[{attr: "a"}]])
|
|
matcher(doc2)
|
|
with pytest.raises(ValueError):
|
|
matcher(doc1)
|
|
with pytest.raises(ValueError):
|
|
matcher(doc3)
|
|
# TEXT/ORTH only require tokens
|
|
matcher = Matcher(en_vocab)
|
|
matcher.add("TEST", [[{"ORTH": "a"}]])
|
|
matcher(doc1)
|
|
matcher(doc2)
|
|
matcher(doc3)
|
|
matcher = Matcher(en_vocab)
|
|
matcher.add("TEST", [[{"TEXT": "a"}]])
|
|
matcher(doc1)
|
|
matcher(doc2)
|
|
matcher(doc3)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"pattern,text",
|
|
[
|
|
([{"IS_ALPHA": True}], "a"),
|
|
([{"IS_ASCII": True}], "a"),
|
|
([{"IS_DIGIT": True}], "1"),
|
|
([{"IS_LOWER": True}], "a"),
|
|
([{"IS_UPPER": True}], "A"),
|
|
([{"IS_TITLE": True}], "Aaaa"),
|
|
([{"IS_PUNCT": True}], "."),
|
|
([{"IS_SPACE": True}], "\n"),
|
|
([{"IS_BRACKET": True}], "["),
|
|
([{"IS_QUOTE": True}], '"'),
|
|
([{"IS_LEFT_PUNCT": True}], "``"),
|
|
([{"IS_RIGHT_PUNCT": True}], "''"),
|
|
([{"IS_STOP": True}], "the"),
|
|
([{"SPACY": True}], "the"),
|
|
([{"LIKE_NUM": True}], "1"),
|
|
([{"LIKE_URL": True}], "http://example.com"),
|
|
([{"LIKE_EMAIL": True}], "mail@example.com"),
|
|
],
|
|
)
|
|
def test_matcher_schema_token_attributes(en_vocab, pattern, text):
|
|
matcher = Matcher(en_vocab)
|
|
doc = Doc(en_vocab, words=text.split(" "))
|
|
matcher.add("Rule", [pattern])
|
|
assert len(matcher) == 1
|
|
matches = matcher(doc)
|
|
assert len(matches) == 1
|
|
|
|
|
|
@pytest.mark.filterwarnings("ignore:\\[W036")
|
|
def test_matcher_valid_callback(en_vocab):
|
|
"""Test that on_match can only be None or callable."""
|
|
matcher = Matcher(en_vocab)
|
|
with pytest.raises(ValueError):
|
|
matcher.add("TEST", [[{"TEXT": "test"}]], on_match=[])
|
|
matcher(Doc(en_vocab, words=["test"]))
|
|
|
|
|
|
def test_matcher_callback(en_vocab):
|
|
mock = Mock()
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"ORTH": "test"}]
|
|
matcher.add("Rule", [pattern], on_match=mock)
|
|
doc = Doc(en_vocab, words=["This", "is", "a", "test", "."])
|
|
matches = matcher(doc)
|
|
mock.assert_called_once_with(matcher, doc, 0, matches)
|
|
|
|
|
|
def test_matcher_callback_with_alignments(en_vocab):
|
|
mock = Mock()
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"ORTH": "test"}]
|
|
matcher.add("Rule", [pattern], on_match=mock)
|
|
doc = Doc(en_vocab, words=["This", "is", "a", "test", "."])
|
|
matches = matcher(doc, with_alignments=True)
|
|
mock.assert_called_once_with(matcher, doc, 0, matches)
|
|
|
|
|
|
def test_matcher_span(matcher):
|
|
text = "JavaScript is good but Java is better"
|
|
doc = Doc(matcher.vocab, words=text.split())
|
|
span_js = doc[:3]
|
|
span_java = doc[4:]
|
|
assert len(matcher(doc)) == 2
|
|
assert len(matcher(span_js)) == 1
|
|
assert len(matcher(span_java)) == 1
|
|
|
|
|
|
def test_matcher_as_spans(matcher):
|
|
"""Test the new as_spans=True API."""
|
|
text = "JavaScript is good but Java is better"
|
|
doc = Doc(matcher.vocab, words=text.split())
|
|
matches = matcher(doc, as_spans=True)
|
|
assert len(matches) == 2
|
|
assert isinstance(matches[0], Span)
|
|
assert matches[0].text == "JavaScript"
|
|
assert matches[0].label_ == "JS"
|
|
assert isinstance(matches[1], Span)
|
|
assert matches[1].text == "Java"
|
|
assert matches[1].label_ == "Java"
|
|
|
|
matches = matcher(doc[1:], as_spans=True)
|
|
assert len(matches) == 1
|
|
assert isinstance(matches[0], Span)
|
|
assert matches[0].text == "Java"
|
|
assert matches[0].label_ == "Java"
|
|
|
|
|
|
def test_matcher_deprecated(matcher):
|
|
doc = Doc(matcher.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_matcher_remove_zero_operator(en_vocab):
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"OP": "!"}]
|
|
matcher.add("Rule", [pattern])
|
|
doc = Doc(en_vocab, words=["This", "is", "a", "test", "."])
|
|
matches = matcher(doc)
|
|
assert len(matches) == 0
|
|
assert "Rule" in matcher
|
|
matcher.remove("Rule")
|
|
assert "Rule" not in matcher
|
|
|
|
|
|
def test_matcher_no_zero_length(en_vocab):
|
|
doc = Doc(en_vocab, words=["a", "b"], tags=["A", "B"])
|
|
matcher = Matcher(en_vocab)
|
|
matcher.add("TEST", [[{"TAG": "C", "OP": "?"}]])
|
|
assert len(matcher(doc)) == 0
|
|
|
|
|
|
def test_matcher_ent_iob_key(en_vocab):
|
|
"""Test that patterns with ent_iob works correctly."""
|
|
matcher = Matcher(en_vocab)
|
|
matcher.add("Rule", [[{"ENT_IOB": "I"}]])
|
|
doc1 = Doc(en_vocab, words=["I", "visited", "New", "York", "and", "California"])
|
|
doc1.ents = [Span(doc1, 2, 4, label="GPE"), Span(doc1, 5, 6, label="GPE")]
|
|
doc2 = Doc(en_vocab, words=["I", "visited", "my", "friend", "Alicia"])
|
|
doc2.ents = [Span(doc2, 4, 5, label="PERSON")]
|
|
matches1 = [doc1[start:end].text for _, start, end in matcher(doc1)]
|
|
matches2 = [doc2[start:end].text for _, start, end in matcher(doc2)]
|
|
assert len(matches1) == 1
|
|
assert matches1[0] == "York"
|
|
assert len(matches2) == 0
|
|
|
|
matcher = Matcher(en_vocab) # Test iob pattern with operators
|
|
matcher.add("Rule", [[{"ENT_IOB": "I", "OP": "+"}]])
|
|
doc = Doc(
|
|
en_vocab, words=["I", "visited", "my", "friend", "Anna", "Maria", "Esperanza"]
|
|
)
|
|
doc.ents = [Span(doc, 4, 7, label="PERSON")]
|
|
matches = [doc[start:end].text for _, start, end in matcher(doc)]
|
|
assert len(matches) == 3
|
|
assert matches[0] == "Maria"
|
|
assert matches[1] == "Maria Esperanza"
|
|
assert matches[2] == "Esperanza"
|
|
|
|
|
|
def test_matcher_min_max_operator(en_vocab):
|
|
# Exactly n matches {n}
|
|
doc = Doc(
|
|
en_vocab,
|
|
words=["foo", "bar", "foo", "foo", "bar", "foo", "foo", "foo", "bar", "bar"],
|
|
)
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"ORTH": "foo", "OP": "{3}"}]
|
|
matcher.add("TEST", [pattern])
|
|
|
|
matches1 = [doc[start:end].text for _, start, end in matcher(doc)]
|
|
assert len(matches1) == 1
|
|
|
|
# At least n matches {n,}
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"ORTH": "foo", "OP": "{2,}"}]
|
|
matcher.add("TEST", [pattern])
|
|
matches2 = [doc[start:end].text for _, start, end in matcher(doc)]
|
|
assert len(matches2) == 4
|
|
|
|
# At most m matches {,m}
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"ORTH": "foo", "OP": "{,2}"}]
|
|
matcher.add("TEST", [pattern])
|
|
matches3 = [doc[start:end].text for _, start, end in matcher(doc)]
|
|
assert len(matches3) == 9
|
|
|
|
# At least n matches and most m matches {n,m}
|
|
matcher = Matcher(en_vocab)
|
|
pattern = [{"ORTH": "foo", "OP": "{2,3}"}]
|
|
matcher.add("TEST", [pattern])
|
|
matches4 = [doc[start:end].text for _, start, end in matcher(doc)]
|
|
assert len(matches4) == 4
|