spaCy/spacy/tests/matcher/test_matcher_api.py

215 lines
7.1 KiB
Python

# coding: utf-8
from __future__ import unicode_literals
import pytest
import re
from spacy.matcher import Matcher, DependencyTreeMatcher
from spacy.tokens import Doc
from ..util import get_doc
@pytest.fixture
def matcher(en_vocab):
rules = {'JS': [[{'ORTH': 'JavaScript'}]],
'GoogleNow': [[{'ORTH': 'Google'}, {'ORTH': 'Now'}]],
'Java': [[{'LOWER': 'java'}]]}
matcher = Matcher(en_vocab)
for key, patterns in rules.items():
matcher.add(key, None, *patterns)
return matcher
def test_matcher_from_api_docs(en_vocab):
matcher = Matcher(en_vocab)
pattern = [{'ORTH': 'test'}]
assert len(matcher) == 0
matcher.add('Rule', None, pattern)
assert len(matcher) == 1
matcher.remove('Rule')
assert 'Rule' not in matcher
matcher.add('Rule', None, pattern)
assert 'Rule' in matcher
on_match, patterns = matcher.get('Rule')
assert len(patterns[0])
def test_matcher_from_usage_docs(en_vocab):
text = "Wow 😀 This is really cool! 😂 😂"
doc = Doc(en_vocab, words=text.split(' '))
pos_emoji = ['😀', '😃', '😂', '🤣', '😊', '😍']
pos_patterns = [[{'ORTH': emoji}] for emoji in pos_emoji]
def label_sentiment(matcher, doc, i, matches):
match_id, start, end = matches[i]
if doc.vocab.strings[match_id] == 'HAPPY':
doc.sentiment += 0.1
span = doc[start : end]
token = span.merge()
token.vocab[token.text].norm_ = 'happy emoji'
matcher = Matcher(en_vocab)
matcher.add('HAPPY', label_sentiment, *pos_patterns)
matches = matcher(doc)
assert doc.sentiment != 0
assert doc[1].norm_ == 'happy emoji'
def test_matcher_len_contains(matcher):
assert len(matcher) == 3
matcher.add('TEST', None, [{'ORTH': 'test'}])
assert 'TEST' in matcher
assert 'TEST2' not in matcher
def test_matcher_no_match(matcher):
doc = Doc(matcher.vocab, words=["I", "like", "cheese", "."])
assert matcher(doc) == []
def test_matcher_match_start(matcher):
doc = Doc(matcher.vocab, words=["JavaScript", "is", "good"])
assert matcher(doc) == [(matcher.vocab.strings['JS'], 0, 1)]
def test_matcher_match_end(matcher):
words = ["I", "like", "java"]
doc = Doc(matcher.vocab, words=words)
assert matcher(doc) == [(doc.vocab.strings['Java'], 2, 3)]
def test_matcher_match_middle(matcher):
words = ["I", "like", "Google", "Now", "best"]
doc = Doc(matcher.vocab, words=words)
assert matcher(doc) == [(doc.vocab.strings['GoogleNow'], 2, 4)]
def test_matcher_match_multi(matcher):
words = ["I", "like", "Google", "Now", "and", "java", "best"]
doc = Doc(matcher.vocab, words=words)
assert matcher(doc) == [(doc.vocab.strings['GoogleNow'], 2, 4),
(doc.vocab.strings['Java'], 5, 6)]
def test_matcher_empty_dict(en_vocab):
"""Test matcher allows empty token specs, meaning match on any token."""
matcher = Matcher(en_vocab)
doc = Doc(matcher.vocab, words=["a", "b", "c"])
matcher.add('A.C', None, [{'ORTH': 'a'}, {}, {'ORTH': 'c'}])
matches = matcher(doc)
assert len(matches) == 1
assert matches[0][1:] == (0, 3)
matcher = Matcher(en_vocab)
matcher.add('A.', None, [{'ORTH': 'a'}, {}])
matches = matcher(doc)
assert matches[0][1:] == (0, 2)
def test_matcher_operator_shadow(en_vocab):
matcher = Matcher(en_vocab)
doc = Doc(matcher.vocab, words=["a", "b", "c"])
pattern = [{'ORTH': 'a'}, {"IS_ALPHA": True, "OP": "+"}, {'ORTH': 'c'}]
matcher.add('A.C', None, pattern)
matches = matcher(doc)
assert len(matches) == 1
assert matches[0][1:] == (0, 3)
def test_matcher_match_zero(matcher):
words1 = 'He said , " some words " ...'.split()
words2 = 'He said , " some three words " ...'.split()
pattern1 = [{'ORTH': '"'},
{'OP': '!', 'IS_PUNCT': True},
{'OP': '!', 'IS_PUNCT': True},
{'ORTH': '"'}]
pattern2 = [{'ORTH': '"'},
{'IS_PUNCT': True},
{'IS_PUNCT': True},
{'IS_PUNCT': True},
{'ORTH': '"'}]
matcher.add('Quote', None, pattern1)
doc = Doc(matcher.vocab, words=words1)
assert len(matcher(doc)) == 1
doc = Doc(matcher.vocab, words=words2)
assert len(matcher(doc)) == 0
matcher.add('Quote', None, pattern2)
assert len(matcher(doc)) == 0
def test_matcher_match_zero_plus(matcher):
words = 'He said , " some words " ...'.split()
pattern = [{'ORTH': '"'},
{'OP': '*', 'IS_PUNCT': False},
{'ORTH': '"'}]
matcher = Matcher(matcher.vocab)
matcher.add('Quote', None, pattern)
doc = Doc(matcher.vocab, words=words)
assert len(matcher(doc)) == 1
def test_matcher_match_one_plus(matcher):
control = Matcher(matcher.vocab)
control.add('BasicPhilippe', None, [{'ORTH': 'Philippe'}])
doc = Doc(control.vocab, words=['Philippe', 'Philippe'])
m = control(doc)
assert len(m) == 2
matcher.add('KleenePhilippe', None, [{'ORTH': 'Philippe', 'OP': '1'},
{'ORTH': 'Philippe', 'OP': '+'}])
m = matcher(doc)
assert len(m) == 1
def test_matcher_any_token_operator(en_vocab):
"""Test that patterns with "any token" {} work with operators."""
matcher = Matcher(en_vocab)
matcher.add('TEST', None, [{'ORTH': 'test'}, {'OP': '*'}])
doc = Doc(en_vocab, words=['test', 'hello', 'world'])
matches = [doc[start:end].text for _, start, end in matcher(doc)]
assert len(matches) == 3
assert matches[0] == 'test'
assert matches[1] == 'test hello'
assert matches[2] == 'test hello world'
@pytest.fixture
def text():
return u"The quick brown fox jumped over the lazy fox"
@pytest.fixture
def heads():
return [3,2,1,1,0,-1,2,1,-3]
@pytest.fixture
def deps():
return ['det', 'amod', 'amod', 'nsubj', 'prep', 'pobj', 'det', 'amod']
@pytest.fixture
def dependency_tree_matcher(en_vocab):
is_brown_yellow = lambda text: bool(re.compile(r'brown|yellow|over').match(text))
IS_BROWN_YELLOW = en_vocab.add_flag(is_brown_yellow)
pattern1 = [
{'SPEC': {'NODE_NAME': 'fox'}, 'PATTERN': {'ORTH': 'fox'}},
{'SPEC': {'NODE_NAME': 'q', 'NBOR_RELOP': '>', 'NBOR_NAME': 'fox'},'PATTERN': {'LOWER': u'quick'}},
{'SPEC': {'NODE_NAME': 'r', 'NBOR_RELOP': '>', 'NBOR_NAME': 'fox'}, 'PATTERN': {IS_BROWN_YELLOW: True}}
]
pattern2 = [
{'SPEC': {'NODE_NAME': 'jumped'}, 'PATTERN': {'ORTH': 'jumped'}},
{'SPEC': {'NODE_NAME': 'fox', 'NBOR_RELOP': '>', 'NBOR_NAME': 'jumped'},'PATTERN': {'LOWER': u'fox'}},
{'SPEC': {'NODE_NAME': 'over', 'NBOR_RELOP': '>', 'NBOR_NAME': 'fox'}, 'PATTERN': {IS_BROWN_YELLOW: True}}
]
matcher = DependencyTreeMatcher(en_vocab)
matcher.add('pattern1', None, pattern1)
matcher.add('pattern2', None, pattern2)
return matcher
def test_dependency_tree_matcher_compile(dependency_tree_matcher):
assert len(dependency_tree_matcher) == 2
def test_dependency_tree_matcher(dependency_tree_matcher,text,heads,deps):
doc = get_doc(dependency_tree_matcher.vocab,text.split(),heads=heads,deps=deps)
matches = dependency_tree_matcher(doc)
assert len(matches) == 2