spaCy/spacy/tests/regression/test_issue1769.py

85 lines
2.3 KiB
Python

# coding: utf-8
from __future__ import unicode_literals
from ...lang.da.lex_attrs import like_num as da_like_num
from ...lang.en.lex_attrs import like_num as en_like_num
from ...lang.fr.lex_attrs import like_num as fr_like_num
from ...lang.id.lex_attrs import like_num as id_like_num
# from ...lang.nl.lex_attrs import like_num as nl_like_num
# from ...lang.pt.lex_attrs import like_num as pt_like_num
# from ...lang.ru.lex_attrs import like_num as ru_like_num
import pytest
@pytest.fixture
def words():
return {
"da": {
"num_words": ('elleve', 'ELLEVE'),
"ord_words": ('første', 'FØRSTE')
},
"en": {
"num_words": ('eleven', 'ELEVEN')
},
"fr": {
"num_words": ('onze', 'ONZE'),
"ord_words": ('onzième', 'ONZIÈME')
},
"id": {
"num_words": ('sebelas', 'SEBELAS')
},
"nl": {
"num_words": ('elf', 'ELF'),
"ord_words": ('elfde', 'ELFDE')
},
"pt": {
"num_words": ('onze', 'ONZE'),
"ord_words": ('quadragésimo', 'QUADRAGÉSIMO')
},
"ru": {
"num_words": ('одиннадцать', 'ОДИННАДЦАТЬ')
}
}
def like_num(words, fn):
ok = True
for word in words:
if fn(word) is not True:
ok = False
break
return ok
def test_da_lex_attrs(words):
assert like_num(words["da"]["num_words"], da_like_num) == True
assert like_num(words["da"]["ord_words"], da_like_num) == True
def test_en_lex_attrs(words):
assert like_num(words["en"]["num_words"], en_like_num) == True
def test_fr_lex_attrs(words):
assert like_num(words["fr"]["num_words"], fr_like_num) == True
assert like_num(words["fr"]["ord_words"], fr_like_num) == True
def test_id_lex_attrs(words):
assert like_num(words["id"]["num_words"], id_like_num) == True
# def test_nl_lex_attrs(words):
# assert like_num(words["nl"]["num_words"], nl_like_num) == True
# assert like_num(words["nl"]["ord_words"], nl_like_num) == True
#
#
# def test_pt_lex_attrs(words):
# assert like_num(words["pt"]["num_words"], pt_like_num) == True
# assert like_num(words["pt"]["ord_words"], pt_like_num) == True
#
#
# def test_ru_lex_attrs(words):
# assert like_num(words["ru"]["num_words"], ru_like_num) == True