def test_validator(mocker, mock_check_index, missing_files, invalid_checksums):
mock_check_index.return_value = missing_files, invalid_checksums
m, c = utils.validator('foo', 'bar', True)
assert m == missing_files
assert c == invalid_checksums
mock_check_index.assert_called_once_with('foo', 'bar', True)
def test_validator(mocker, mock_check_index, missing_files, invalid_checksums):
mock_check_index.return_value = missing_files, invalid_checksums
m, c = utils.validator("foo", "bar", False)
assert m == missing_files
assert c == invalid_checksums
mock_check_index.assert_called_once_with("foo", "bar", False)
def test_validator_already_validated(mocker, mock_validated, mock_check_index,
mock_create_invalid,
mock_create_validated):
mock_validated.return_value = True
m, c = utils.validator('foo', 'bar', 'baz', True)
assert m == {}
assert c == {}
mock_validated.assert_called_once_with('baz')
mock_check_index.assert_not_called()
mock_create_invalid.assert_not_called()
mock_create_validated.assert_not_called()
def validate(self, verbose=True):
"""Validate if the stored dataset is a valid version
Args:
verbose (bool): If False, don't print output
Returns:
missing_files (list): List of file paths that are in the dataset index
but missing locally
invalid_checksums (list): List of file paths that file exists in the dataset
index but has a different checksum compare to the reference checksum
"""
missing_files, invalid_checksums = utils.validator(
self._index, self.data_home, verbose=verbose
)
return missing_files, invalid_checksums
def test_validator(mocker, mock_validated, mock_check_index,
mock_create_invalid, mock_create_validated, missing_files,
invalid_checksums):
mock_validated.return_value = False
mock_check_index.return_value = missing_files, invalid_checksums
m, c = utils.validator('foo', 'bar', 'baz', True)
assert m == missing_files
assert c == invalid_checksums
mock_validated.assert_called_once_with('baz')
mock_check_index.assert_called_once_with('foo', 'bar', True)
if missing_files or invalid_checksums:
mock_create_invalid.assert_called_once_with('baz', missing_files,
invalid_checksums)
else:
mock_create_validated.assert_called_once_with('baz')
def validate(dataset_path, data_home=None):
"""Validate if the stored dataset is a valid version
Args:
dataset_path (str): MedleyDB melody dataset local path
data_home (str): Local path where the dataset is stored.
If `None`, looks for the data in the default directory, `~/mir_datasets`
Returns:
missing_files (list): List of file paths that are in the dataset index
but missing locally
invalid_checksums (list): List of file paths that file exists in the dataset
index but has a different checksum compare to the reference checksum
"""
missing_files, invalid_checksums = utils.validator(INDEX, data_home,
dataset_path)
return missing_files, invalid_checksums
def validate(data_home=None, silence=False):
"""Validate if the stored dataset is a valid version
Args:
data_home (str): Local path where the dataset is stored.
If `None`, looks for the data in the default directory, `~/mir_datasets`
Returns:
missing_files (list): List of file paths that are in the dataset index
but missing locally
invalid_checksums (list): List of file paths that file exists in the dataset
index but has a different checksum compare to the reference checksum
"""
if data_home is None:
data_home = utils.get_default_dataset_path(DATASET_DIR)
missing_files, invalid_checksums = utils.validator(INDEX,
data_home,
silence=silence)
return missing_files, invalid_checksums
def validate(data_home=None, silence=False):
"""Validate if a local version of this dataset is consistent
Args:
data_home (str): Local path where the dataset is stored.
If `None`, looks for the data in the default directory, `~/mir_datasets`
Returns:
missing_files (list): List of file paths that are in the dataset index
but missing locally
invalid_checksums (list): List of file paths where the expected file exists locally
but has a different checksum than the reference
"""
if data_home is None:
data_home = utils.get_default_dataset_path(DATASET_DIR)
missing_files, invalid_checksums = utils.validator(DATA.index,
data_home,
silence=silence)
return missing_files, invalid_checksums
def validate(dataset_path, data_home=None):
"""Validate if a local version of this dataset is consistent
Args:
dataset_path (str): the Beatles dataset local path
data_home (str): Local path where the dataset is stored.
If `None`, looks for the data in the default directory, `~/mir_datasets`
Returns:
missing_files (list): List of file paths that are in the dataset index
but missing locally
invalid_checksums (list): List of file paths where the expected file exists locally
but has a different checksum than the reference
"""
missing_files, invalid_checksums = utils.validator(
INDEX, data_home, dataset_path
)
return missing_files, invalid_checksums
