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e2b70df012
* Use isort with Black profile * isort all the things * Fix import cycles as a result of import sorting * Add DOCBIN_ALL_ATTRS type definition * Add isort to requirements * Remove isort from build dependencies check * Typo
75 lines
2.0 KiB
Python
75 lines
2.0 KiB
Python
import pytest
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from spacy.lang.es import Spanish
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from spacy.lang.es.lex_attrs import like_num
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@pytest.mark.issue(3803)
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def test_issue3803():
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"""Test that spanish num-like tokens have True for like_num attribute."""
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nlp = Spanish()
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text = "2 dos 1000 mil 12 doce"
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doc = nlp(text)
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assert [t.like_num for t in doc] == [True, True, True, True, True, True]
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def test_es_tokenizer_handles_long_text(es_tokenizer):
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text = """Cuando a José Mujica lo invitaron a dar una conferencia
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en Oxford este verano, su cabeza hizo "crac". La "más antigua" universidad de habla
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inglesa, esa que cobra decenas de miles de euros de matrícula a sus alumnos
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y en cuyos salones han disertado desde Margaret Thatcher hasta Stephen Hawking,
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reclamaba los servicios de este viejo de 81 años, formado en un colegio público
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en Montevideo y que pregona las bondades de la vida austera."""
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tokens = es_tokenizer(text)
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assert len(tokens) == 90
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@pytest.mark.parametrize(
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"text,length",
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[
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("¿Por qué José Mujica?", 6),
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("“¿Oh no?”", 6),
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("""¡Sí! "Vámonos", contestó José Arcadio Buendía""", 11),
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("Corrieron aprox. 10km.", 5),
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("Y entonces por qué...", 5),
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],
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)
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def test_es_tokenizer_handles_cnts(es_tokenizer, text, length):
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tokens = es_tokenizer(text)
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assert len(tokens) == length
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@pytest.mark.parametrize(
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"text,match",
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[
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("10", True),
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("1", True),
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("10.000", True),
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("1000", True),
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("999,0", True),
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("uno", True),
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("dos", True),
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("billón", True),
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("veintiséis", True),
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("perro", False),
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(",", False),
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("1/2", True),
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],
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)
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def test_lex_attrs_like_number(es_tokenizer, text, match):
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tokens = es_tokenizer(text)
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assert len(tokens) == 1
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assert tokens[0].like_num == match
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@pytest.mark.parametrize("word", ["once"])
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def test_es_lex_attrs_capitals(word):
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assert like_num(word)
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assert like_num(word.upper())
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