mirror of https://github.com/explosion/spaCy.git
107 lines
3.3 KiB
Python
107 lines
3.3 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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from spacy.en import English
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@pytest.fixture
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def matcher():
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patterns = {
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'JS': ['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(Vocab(get_lex_attr=English.Defaults.lex_attr_getters), 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):
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doc = Doc(matcher.vocab, ['I', 'like', 'cheese', '.'])
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assert matcher(doc) == []
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def test_match_start(matcher):
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doc = Doc(matcher.vocab, ['JavaScript', 'is', 'good'])
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assert matcher(doc) == [(matcher.vocab.strings['JS'],
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matcher.vocab.strings['PRODUCT'], 0, 1)]
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def test_match_end(matcher):
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doc = Doc(matcher.vocab, ['I', 'like', 'java'])
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assert matcher(doc) == [(doc.vocab.strings['Java'],
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doc.vocab.strings['PRODUCT'], 2, 3)]
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def test_match_middle(matcher):
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doc = Doc(matcher.vocab, ['I', 'like', 'Google', 'Now', 'best'])
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assert matcher(doc) == [(doc.vocab.strings['GoogleNow'],
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doc.vocab.strings['PRODUCT'], 2, 4)]
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def test_match_multi(matcher):
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doc = Doc(matcher.vocab, 'I like Google Now and java best'.split())
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assert matcher(doc) == [(doc.vocab.strings['GoogleNow'],
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doc.vocab.strings['PRODUCT'], 2, 4),
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(doc.vocab.strings['Java'],
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doc.vocab.strings['PRODUCT'], 5, 6)]
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def test_match_zero(matcher):
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matcher.add('Quote', '', {}, [
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[
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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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doc = Doc(matcher.vocab, 'He said , " some words " ...'.split())
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assert len(matcher(doc)) == 1
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doc = Doc(matcher.vocab, 'He said , " some three words " ...'.split())
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assert len(matcher(doc)) == 0
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matcher.add('Quote', '', {}, [
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[
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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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assert len(matcher(doc)) == 0
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def test_match_zero_plus(matcher):
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matcher.add('Quote', '', {}, [
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[
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{'ORTH': '"'},
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{'OP': '*', 'IS_PUNCT': False},
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{'ORTH': '"'}
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]])
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doc = Doc(matcher.vocab, 'He said , " some words " ...'.split())
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assert len(matcher(doc)) == 1
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@pytest.mark.models
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def test_match_preserved(EN):
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patterns = {
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'JS': ['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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matcher = Matcher(EN.vocab, patterns)
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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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doc.ents += tuple(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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