spaCy/spacy/tests/matcher/test_matcher_logic.py
Ines Montani 33a2682d60
Add better schemas and validation using Pydantic (#4831)
* Remove unicode declarations

* Remove Python 3.5 and 2.7 from CI

* Don't require pathlib

* Replace compat helpers

* Remove OrderedDict

* Use f-strings

* Set Cython compiler language level

* Fix typo

* Re-add OrderedDict for Table

* Update setup.cfg

* Revert CONTRIBUTING.md

* Add better schemas and validation using Pydantic

* Revert lookups.md

* Remove unused import

* Update spacy/schemas.py

Co-Authored-By: Sebastián Ramírez <tiangolo@gmail.com>

* Various small fixes

* Fix docstring

Co-authored-by: Sebastián Ramírez <tiangolo@gmail.com>
2019-12-25 12:39:49 +01:00

171 lines
4.8 KiB
Python

import pytest
import re
from spacy.lang.en import English
from spacy.matcher import Matcher
from spacy.tokens import Doc, Span
pattern1 = [{"ORTH": "A"}, {"ORTH": "A", "OP": "*"}]
pattern2 = [{"ORTH": "A"}, {"ORTH": "A"}]
pattern3 = [{"ORTH": "A"}, {"ORTH": "A"}]
pattern4 = [
{"ORTH": "B"},
{"ORTH": "A", "OP": "*"},
{"ORTH": "B"},
]
pattern5 = [
{"ORTH": "B", "OP": "*"},
{"ORTH": "A", "OP": "*"},
{"ORTH": "B"},
]
re_pattern1 = "AA*"
re_pattern2 = "A*A"
re_pattern3 = "AA"
re_pattern4 = "BA*B"
re_pattern5 = "B*A*B"
@pytest.fixture
def text():
return "(ABBAAAAAB)."
@pytest.fixture
def doc(en_tokenizer, text):
doc = en_tokenizer(" ".join(text))
return doc
@pytest.mark.parametrize(
"pattern,re_pattern",
[
pytest.param(pattern1, re_pattern1, marks=pytest.mark.xfail()),
pytest.param(pattern2, re_pattern2, marks=pytest.mark.xfail()),
pytest.param(pattern3, re_pattern3, marks=pytest.mark.xfail()),
(pattern4, re_pattern4),
pytest.param(pattern5, re_pattern5, marks=pytest.mark.xfail()),
],
)
def test_greedy_matching(doc, text, pattern, re_pattern):
"""Test that the greedy matching behavior of the * op is consistant with
other re implementations."""
matcher = Matcher(doc.vocab)
matcher.add(re_pattern, [pattern])
matches = matcher(doc)
re_matches = [m.span() for m in re.finditer(re_pattern, text)]
for match, re_match in zip(matches, re_matches):
assert match[1:] == re_match
@pytest.mark.xfail
@pytest.mark.parametrize(
"pattern,re_pattern",
[
(pattern1, re_pattern1),
(pattern2, re_pattern2),
(pattern3, re_pattern3),
(pattern4, re_pattern4),
(pattern5, re_pattern5),
],
)
def test_match_consuming(doc, text, pattern, re_pattern):
"""Test that matcher.__call__ consumes tokens on a match similar to
re.findall."""
matcher = Matcher(doc.vocab)
matcher.add(re_pattern, [pattern])
matches = matcher(doc)
re_matches = [m.span() for m in re.finditer(re_pattern, text)]
assert len(matches) == len(re_matches)
def test_operator_combos(en_vocab):
cases = [
("aaab", "a a a b", True),
("aaab", "a+ b", True),
("aaab", "a+ a+ b", True),
("aaab", "a+ a+ a b", True),
("aaab", "a+ a+ a+ b", True),
("aaab", "a+ a a b", True),
("aaab", "a+ a a", True),
("aaab", "a+", True),
("aaa", "a+ b", False),
("aaa", "a+ a+ b", False),
("aaa", "a+ a+ a+ b", False),
("aaa", "a+ a b", False),
("aaa", "a+ a a b", False),
("aaab", "a+ a a", True),
("aaab", "a+", True),
("aaab", "a+ a b", True),
]
for string, pattern_str, result in cases:
matcher = Matcher(en_vocab)
doc = Doc(matcher.vocab, words=list(string))
pattern = []
for part in pattern_str.split():
if part.endswith("+"):
pattern.append({"ORTH": part[0], "OP": "+"})
else:
pattern.append({"ORTH": part})
matcher.add("PATTERN", [pattern])
matches = matcher(doc)
if result:
assert matches, (string, pattern_str)
else:
assert not matches, (string, pattern_str)
def test_matcher_end_zero_plus(en_vocab):
"""Test matcher works when patterns end with * operator. (issue 1450)"""
matcher = Matcher(en_vocab)
pattern = [{"ORTH": "a"}, {"ORTH": "b", "OP": "*"}]
matcher.add("TSTEND", [pattern])
nlp = lambda string: Doc(matcher.vocab, words=string.split())
assert len(matcher(nlp("a"))) == 1
assert len(matcher(nlp("a b"))) == 2
assert len(matcher(nlp("a c"))) == 1
assert len(matcher(nlp("a b c"))) == 2
assert len(matcher(nlp("a b b c"))) == 3
assert len(matcher(nlp("a b b"))) == 3
def test_matcher_sets_return_correct_tokens(en_vocab):
matcher = Matcher(en_vocab)
patterns = [
[{"LOWER": {"IN": ["zero"]}}],
[{"LOWER": {"IN": ["one"]}}],
[{"LOWER": {"IN": ["two"]}}],
]
matcher.add("TEST", patterns)
doc = Doc(en_vocab, words="zero one two three".split())
matches = matcher(doc)
texts = [Span(doc, s, e, label=L).text for L, s, e in matches]
assert texts == ["zero", "one", "two"]
def test_matcher_remove():
nlp = English()
matcher = Matcher(nlp.vocab)
text = "This is a test case."
pattern = [{"ORTH": "test"}, {"OP": "?"}]
assert len(matcher) == 0
matcher.add("Rule", [pattern])
assert "Rule" in matcher
# should give two matches
results1 = matcher(nlp(text))
assert len(results1) == 2
# removing once should work
matcher.remove("Rule")
# should not return any maches anymore
results2 = matcher(nlp(text))
assert len(results2) == 0
# removing again should throw an error
with pytest.raises(ValueError):
matcher.remove("Rule")