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