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62 lines
1.6 KiB
Python
62 lines
1.6 KiB
Python
from __future__ import unicode_literals
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import pytest
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from spacy.strings import StringStore
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from spacy.matcher import *
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from spacy.attrs import LOWER
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from spacy.tokens.doc import Doc
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from spacy.vocab import Vocab
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@pytest.fixture
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def matcher(EN):
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patterns = {
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'Javascript': ['PRODUCT', {}, [[{'ORTH': 'JavaScript'}]]],
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'GoogleNow': ['PRODUCT', {}, [[{'ORTH': 'Google'}, {'ORTH': 'Now'}]]],
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'Java': ['PRODUCT', {}, [[{'LOWER': 'java'}]]],
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}
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return Matcher(EN.vocab, patterns)
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def test_compile(matcher):
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assert matcher.n_patterns == 3
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def test_no_match(matcher, EN):
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tokens = EN('I like cheese')
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assert matcher(tokens) == []
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def test_match_start(matcher, EN):
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tokens = EN('JavaScript is good')
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assert matcher(tokens) == [(EN.vocab.strings['PRODUCT'], 0, 1)]
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def test_match_end(matcher, EN):
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tokens = EN('I like java')
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assert matcher(tokens) == [(EN.vocab.strings['PRODUCT'], 2, 3)]
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def test_match_middle(matcher, EN):
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tokens = EN('I like Google Now best')
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assert matcher(tokens) == [(EN.vocab.strings['PRODUCT'], 2, 4)]
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def test_match_multi(matcher, EN):
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tokens = EN('I like Google Now and java best')
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assert matcher(tokens) == [(EN.vocab.strings['PRODUCT'], 2, 4),
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(EN.vocab.strings['PRODUCT'], 5, 6)]
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@pytest.mark.models
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def test_match_preserved(matcher, EN):
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doc = EN.tokenizer('I like java')
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EN.tagger(doc)
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assert len(doc.ents) == 0
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doc = EN.tokenizer('I like java')
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matcher(doc)
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assert len(doc.ents) == 1
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EN.tagger(doc)
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EN.entity(doc)
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assert len(doc.ents) == 1
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