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71 lines
2.7 KiB
Python
71 lines
2.7 KiB
Python
import pytest
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from spacy.matcher import Matcher
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from spacy.errors import MatchPatternError
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from spacy.schemas import validate_token_pattern
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# (pattern, num errors with validation, num errors identified with minimal
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# checks)
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TEST_PATTERNS = [
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# Bad patterns flagged in all cases
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([{"XX": "foo"}], 1, 1),
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([{"IS_ALPHA": {"==": True}}, {"LIKE_NUM": None}], 2, 1),
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([{"IS_PUNCT": True, "OP": "$"}], 1, 1),
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([{"_": "foo"}], 1, 1),
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('[{"TEXT": "foo"}, {"LOWER": "bar"}]', 1, 1),
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([1, 2, 3], 3, 1),
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# Bad patterns flagged outside of Matcher
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([{"_": {"foo": "bar", "baz": {"IN": "foo"}}}], 2, 0), # prev: (1, 0)
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# Bad patterns not flagged with minimal checks
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([{"LENGTH": "2", "TEXT": 2}, {"LOWER": "test"}], 2, 0),
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([{"LENGTH": {"IN": [1, 2, "3"]}}, {"POS": {"IN": "VERB"}}], 4, 0), # prev: (2, 0)
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([{"LENGTH": {"VALUE": 5}}], 2, 0), # prev: (1, 0)
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([{"TEXT": {"VALUE": "foo"}}], 2, 0), # prev: (1, 0)
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([{"IS_DIGIT": -1}], 1, 0),
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([{"ORTH": -1}], 1, 0),
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# Good patterns
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([{"TEXT": "foo"}, {"LOWER": "bar"}], 0, 0),
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([{"LEMMA": {"IN": ["love", "like"]}}, {"POS": "DET", "OP": "?"}], 0, 0),
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([{"LIKE_NUM": True, "LENGTH": {">=": 5}}], 0, 0),
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([{"LENGTH": 2}], 0, 0),
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([{"LOWER": {"REGEX": "^X", "NOT_IN": ["XXX", "XY"]}}], 0, 0),
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([{"NORM": "a"}, {"POS": {"IN": ["NOUN"]}}], 0, 0),
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([{"_": {"foo": {"NOT_IN": ["bar", "baz"]}, "a": 5, "b": {">": 10}}}], 0, 0),
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([{"orth": "foo"}], 0, 0), # prev: xfail
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([{"IS_SENT_START": True}], 0, 0),
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([{"SENT_START": True}], 0, 0),
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]
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@pytest.mark.parametrize(
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"pattern", [[{"XX": "y"}, {"LENGTH": "2"}, {"TEXT": {"IN": 5}}]]
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)
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def test_matcher_pattern_validation(en_vocab, pattern):
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matcher = Matcher(en_vocab, validate=True)
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with pytest.raises(MatchPatternError):
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matcher.add("TEST", [pattern])
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@pytest.mark.parametrize("pattern,n_errors,_", TEST_PATTERNS)
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def test_pattern_validation(pattern, n_errors, _):
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errors = validate_token_pattern(pattern)
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assert len(errors) == n_errors
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@pytest.mark.parametrize("pattern,n_errors,n_min_errors", TEST_PATTERNS)
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def test_minimal_pattern_validation(en_vocab, pattern, n_errors, n_min_errors):
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matcher = Matcher(en_vocab)
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if n_min_errors > 0:
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with pytest.raises(ValueError):
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matcher.add("TEST", [pattern])
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elif n_errors == 0:
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matcher.add("TEST", [pattern])
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def test_pattern_errors(en_vocab):
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matcher = Matcher(en_vocab)
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# normalize "regex" to upper like "text"
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matcher.add("TEST1", [[{"text": {"regex": "regex"}}]])
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# error if subpattern attribute isn't recognized and processed
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with pytest.raises(MatchPatternError):
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matcher.add("TEST2", [[{"TEXT": {"XX": "xx"}}]])
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