def test_get_index_when_no_extract_passed_returns_not_none():
reader = create_tokens_reader(filename_fields=None,
fix_whitespaces=True,
fix_hyphenation=True)
corpus = corpora.TokenizedCorpus(reader)
result = corpus.metadata
assert result is not None
def test_next_document_when_new_corpus_returns_document():
reader = create_tokens_reader(fix_whitespaces=True, fix_hyphenation=True)
corpus = corpora.TokenizedCorpus(reader)
result = next(corpus)
expected = ("Tre svarta ekar ur snön . " +
"Så grova , men fingerfärdiga . " +
"Ur deras väldiga flaskor " + "ska grönskan skumma i vår .")
assert expected == ' '.join(result[1])
def test_n_tokens_when_exhausted_iterater_returns_expected_count():
reader = create_reader()
corpus = corpora.TokenizedCorpus(
reader,
transform_opts=TokensTransformOpts(only_any_alphanumeric=False))
_ = [x for x in corpus]
n_tokens = list(corpus.document_index.n_tokens)
expected = [22, 16, 26, 45, 21]
assert expected == n_tokens
def test_next_document_when_only_any_alphanumeric_true_skips_deliminators_using_defaults(
):
reader = create_tokens_reader(filename_fields=None,
fix_whitespaces=True,
fix_hyphenation=True)
corpus = corpora.TokenizedCorpus(
reader, transform_opts=TokensTransformOpts(only_any_alphanumeric=True))
_, tokens = next(corpus)
expected = "Tre svarta ekar ur snön Så grova men fingerfärdiga Ur deras väldiga flaskor ska grönskan skumma i vår"
assert expected.split() == tokens
def test_n_tokens_when_exhausted_and_only_any_alphanumeric_is_true_returns_expected_count(
):
reader = create_tokens_reader(filename_fields=None,
fix_whitespaces=True,
fix_hyphenation=True)
corpus = corpora.TokenizedCorpus(
reader, transform_opts=TokensTransformOpts(only_any_alphanumeric=True))
_ = [x for x in corpus]
n_tokens = list(corpus.document_index.n_tokens)
expected = [18, 14, 24, 42, 18]
assert expected == n_tokens
def test_n_tokens_when_exhausted_and_only_any_alphanumeric_min_len_two_returns_expected_count(
):
reader = create_reader()
corpus = corpora.TokenizedCorpus(
reader,
transform_opts=TokensTransformOpts(only_any_alphanumeric=True,
min_len=2))
n_expected = [17, 13, 21, 42, 18]
_ = [x for x in corpus]
n_tokens = list(corpus.document_index.n_tokens)
assert n_expected == n_tokens
def create_corpus(self):
reader = self.create_reader()
transform_opts = corpora.TokensTransformOpts(
only_any_alphanumeric=True,
to_lower=True,
remove_accents=False,
min_len=2,
max_len=None,
keep_numerals=False,
)
corpus = corpora.TokenizedCorpus(reader, transform_opts=transform_opts)
return corpus
def test_next_document_when_max_len_is_six_returns_filter_out_longer_words():
reader = create_reader()
transform_opts = TokensTransformOpts(only_any_alphanumeric=True,
to_lower=True,
remove_accents=False,
min_len=2,
max_len=6,
keep_numerals=True)
corpus = corpora.TokenizedCorpus(reader, transform_opts=transform_opts)
_, tokens = next(corpus)
expected = "tre svarta ekar ur snön så grova men ur deras ska skumma vår"
assert expected.split() == tokens
def test_next_document_when_to_lower_is_true_returns_all_lowercase():
reader = create_reader()
transform_opts = TokensTransformOpts(only_any_alphanumeric=True,
to_lower=True,
remove_accents=False,
min_len=1,
max_len=None,
keep_numerals=True)
corpus = corpora.TokenizedCorpus(reader, transform_opts=transform_opts)
_, tokens = next(corpus)
expected = "tre svarta ekar ur snön så grova men fingerfärdiga ur deras väldiga flaskor ska grönskan skumma i vår"
assert expected.split() == tokens
def test_corpus_can_be_reiterated():
reader = create_tokens_reader(filename_fields=None,
fix_whitespaces=True,
fix_hyphenation=True)
corpus = corpora.TokenizedCorpus(
reader, transform_opts=TokensTransformOpts(only_any_alphanumeric=True))
for _ in range(0, 4):
n_tokens = [len(x) for x in corpus.terms]
expected = [18, 14, 24, 42, 18]
assert expected == n_tokens # , f"iteration{i}"
def test_next_document_when_token_corpus_returns_tokenized_document():
reader = create_tokens_reader(filename_fields=None,
fix_whitespaces=True,
fix_hyphenation=True)
corpus = corpora.TokenizedCorpus(
reader,
transform_opts=TokensTransformOpts(only_any_alphanumeric=False))
_, tokens = next(corpus)
expected = (
"Tre svarta ekar ur snön . Så grova , men fingerfärdiga . Ur deras väldiga flaskor ska grönskan skumma i vår ."
)
assert expected.split() == tokens
def test_next_document_when_only_any_alphanumeric_true_skips_deliminators():
reader = create_reader()
corpus = corpora.TokenizedCorpus(
reader,
transform_opts=TokensTransformOpts(only_any_alphanumeric=True,
to_lower=False,
remove_accents=False,
min_len=1,
keep_numerals=True),
)
_, tokens = next(corpus)
expected = "Tre svarta ekar ur snön Så grova men fingerfärdiga Ur deras väldiga flaskor ska grönskan skumma i vår"
assert expected.split() == tokens
def test_get_index_when_extract_passed_returns_expected_count():
reader = create_reader()
transform_opts = TokensTransformOpts(
only_any_alphanumeric=False,
to_lower=False,
remove_accents=False,
min_len=2,
max_len=None,
keep_numerals=True,
)
corpus = corpora.TokenizedCorpus(reader, transform_opts=transform_opts)
result = corpus.metadata
assert 5 == len(result)
def test_get_index_when_extract_passed_returns_metadata():
filename_fields = dict(year=r".{5}(\d{4})_.*", serial_no=r".{9}_(\d+).*")
reader = create_tokens_reader(filename_fields=filename_fields,
fix_whitespaces=True,
fix_hyphenation=True)
corpus = corpora.TokenizedCorpus(reader)
result = corpus.metadata
expected = [
dict(filename='dikt_2019_01_test.txt', serial_no=1, year=2019),
dict(filename='dikt_2019_02_test.txt', serial_no=2, year=2019),
dict(filename='dikt_2019_03_test.txt', serial_no=3, year=2019),
dict(filename='dikt_2020_01_test.txt', serial_no=1, year=2020),
dict(filename='dikt_2020_02_test.txt', serial_no=2, year=2020),
]
assert len(corpus.document_index) == len(expected)
for i in range(0, len(expected)):
assert expected[i] == result[i]
def test_next_document_when_only_any_alphanumeric_is_false_returns_all_tokens(
):
reader = create_reader()
transform_opts = TokensTransformOpts(
only_any_alphanumeric=False,
to_lower=False,
remove_accents=False,
min_len=1,
max_len=None,
keep_numerals=True,
only_alphabetic=False,
)
corpus = corpora.TokenizedCorpus(reader, transform_opts=transform_opts)
_, tokens = next(corpus)
expected = (
"Tre svarta ekar ur snön . Så grova , men fingerfärdiga . Ur deras väldiga flaskor ska grönskan skumma i vår ."
)
assert expected.split() == tokens
