from __future__ import unicode_literals import pytest from spacy.strings import StringStore from spacy.matcher import * from spacy.attrs import LOWER from spacy.tokens.doc import Doc from spacy.vocab import Vocab from spacy.en import English @pytest.fixture def matcher(): patterns = { 'JS': ['PRODUCT', {}, [[{'ORTH': 'JavaScript'}]]], 'GoogleNow': ['PRODUCT', {}, [[{'ORTH': 'Google'}, {'ORTH': 'Now'}]]], 'Java': ['PRODUCT', {}, [[{'LOWER': 'java'}]]], } return Matcher(Vocab(get_lex_attr=English.default_lex_attrs()), patterns) def test_compile(matcher): assert matcher.n_patterns == 3 def test_no_match(matcher): doc = Doc(matcher.vocab, ['I', 'like', 'cheese', '.']) assert matcher(doc) == [] def test_match_start(matcher): doc = Doc(matcher.vocab, ['JavaScript', 'is', 'good']) assert matcher(doc) == [(matcher.vocab.strings['JS'], matcher.vocab.strings['PRODUCT'], 0, 1)] def test_match_end(matcher): doc = Doc(matcher.vocab, ['I', 'like', 'java']) assert matcher(doc) == [(doc.vocab.strings['Java'], doc.vocab.strings['PRODUCT'], 2, 3)] def test_match_middle(matcher): doc = Doc(matcher.vocab, ['I', 'like', 'Google', 'Now', 'best']) assert matcher(doc) == [(doc.vocab.strings['GoogleNow'], doc.vocab.strings['PRODUCT'], 2, 4)] def test_match_multi(matcher): doc = Doc(matcher.vocab, 'I like Google Now and java best'.split()) assert matcher(doc) == [(doc.vocab.strings['GoogleNow'], doc.vocab.strings['PRODUCT'], 2, 4), (doc.vocab.strings['Java'], doc.vocab.strings['PRODUCT'], 5, 6)] def test_match_zero(matcher): matcher.add('Quote', '', {}, [ [ {'ORTH': '"'}, {'OP': '!', 'IS_PUNCT': True}, {'OP': '!', 'IS_PUNCT': True}, {'ORTH': '"'} ]]) doc = Doc(matcher.vocab, 'He said , " some words " ...'.split()) assert len(matcher(doc)) == 1 doc = Doc(matcher.vocab, 'He said , " some three words " ...'.split()) assert len(matcher(doc)) == 0 matcher.add('Quote', '', {}, [ [ {'ORTH': '"'}, {'IS_PUNCT': True}, {'IS_PUNCT': True}, {'IS_PUNCT': True}, {'ORTH': '"'} ]]) assert len(matcher(doc)) == 0 def test_match_zero_plus(matcher): matcher.add('Quote', '', {}, [ [ {'ORTH': '"'}, {'OP': '*', 'IS_PUNCT': False}, {'ORTH': '"'} ]]) doc = Doc(matcher.vocab, 'He said , " some words " ...'.split()) assert len(matcher(doc)) == 1 @pytest.mark.models def test_match_preserved(EN): patterns = { 'JS': ['PRODUCT', {}, [[{'ORTH': 'JavaScript'}]]], 'GoogleNow': ['PRODUCT', {}, [[{'ORTH': 'Google'}, {'ORTH': 'Now'}]]], 'Java': ['PRODUCT', {}, [[{'LOWER': 'java'}]]], } matcher = Matcher(EN.vocab, patterns) doc = EN.tokenizer('I like java.') EN.tagger(doc) assert len(doc.ents) == 0 doc = EN.tokenizer('I like java.') doc.ents += tuple(matcher(doc)) assert len(doc.ents) == 1 EN.tagger(doc) EN.entity(doc) assert len(doc.ents) == 1