Source code for kedro.extras.datasets.tracking.metrics_dataset

# Copyright 2021 QuantumBlack Visual Analytics Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
# OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND
# NONINFRINGEMENT. IN NO EVENT WILL THE LICENSOR OR OTHER CONTRIBUTORS
# BE LIABLE FOR ANY CLAIM, DAMAGES, OR OTHER LIABILITY, WHETHER IN AN
# ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF, OR IN
# CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
#
# The QuantumBlack Visual Analytics Limited ("QuantumBlack") name and logo
# (either separately or in combination, "QuantumBlack Trademarks") are
# trademarks of QuantumBlack. The License does not grant you any right or
# license to the QuantumBlack Trademarks. You may not use the QuantumBlack
# Trademarks or any confusingly similar mark as a trademark for your product,
# or use the QuantumBlack Trademarks in any other manner that might cause
# confusion in the marketplace, including but not limited to in advertising,
# on websites, or on software.
#
# See the License for the specific language governing permissions and
# limitations under the License.

"""``MetricsDataSet`` saves data to a JSON file using an underlying
filesystem (e.g.: local, S3, GCS). It uses native json to handle the JSON file.
The ``MetricsDataSet`` is part of Kedro Experiment Tracking. The dataset is versioned by default
and only takes metrics of numeric values.
"""
import json
from typing import Any, Dict

from kedro.extras.datasets.json import JSONDataSet
from kedro.io.core import DataSetError, Version, get_filepath_str


[docs]class MetricsDataSet(JSONDataSet): """``MetricsDataSet`` saves data to a JSON file using an underlying filesystem (e.g.: local, S3, GCS). It uses native json to handle the JSON file. The ``MetricsDataSet`` is part of Kedro Experiment Tracking. The dataset is versioned by default and only takes metrics of numeric values. Example: :: >>> from kedro.extras.datasets.tracking import MetricsDataSet >>> >>> data = {'col1': 1, 'col2': 0.23, 'col3': 0.002} >>> >>> # data_set = MetricsDataSet(filepath="gcs://bucket/test.json") >>> data_set = MetricsDataSet(filepath="test.json") >>> data_set.save(data) >>> reloaded = data_set.load() >>> assert data == reloaded """ # pylint: disable=too-many-arguments
[docs] def __init__( self, filepath: str, save_args: Dict[str, Any] = None, version: Version = Version(None, None), credentials: Dict[str, Any] = None, fs_args: Dict[str, Any] = None, ) -> None: """Creates a new instance of ``MetricsDataSet`` pointing to a concrete JSON file on a specific filesystem. Args: filepath: Filepath in POSIX format to a JSON file prefixed with a protocol like `s3://`. If prefix is not provided, `file` protocol (local filesystem) will be used. The prefix should be any protocol supported by ``fsspec``. Note: `http(s)` doesn't support versioning. save_args: json options for saving JSON files (arguments passed into ```json.dump``). Here you can find all available arguments: https://docs.python.org/3/library/json.html All defaults are preserved, but "default_flow_style", which is set to False. version: If specified, should be an instance of ``kedro.io.core.Version``. If its ``load`` attribute is None, the latest version will be loaded. If its ``save`` attribute is None, save version will be autogenerated. Versioning for this dataset is turned on by default and can not be turned off. credentials: Credentials required to get access to the underlying filesystem. E.g. for ``GCSFileSystem`` it should look like `{"token": None}`. fs_args: Extra arguments to pass into underlying filesystem class constructor (e.g. `{"project": "my-project"}` for ``GCSFileSystem``), as well as to pass to the filesystem's `open` method through nested keys `open_args_load` and `open_args_save`. Here you can find all available arguments for `open`: https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open All defaults are preserved, except `mode`, which is set to `r` when loading and to `w` when saving. """ super().__init__( filepath=filepath, save_args=save_args, credentials=credentials, version=version, fs_args=fs_args, )
def _load(self) -> Dict: raise DataSetError(f"Loading not supported for `{self.__class__.__name__}`") def _save(self, data: Dict[str, float]) -> None: """Converts all values in the data from a ``MetricsDataSet`` to float to make sure they are numeric values which can be displayed in Kedro Viz and then saves the dataset. """ try: for key, value in data.items(): data[key] = float(value) except ValueError as exc: raise DataSetError( f"The MetricsDataSet expects only numeric values. {exc}" ) from exc save_path = get_filepath_str(self._get_save_path(), self._protocol) with self._fs.open(save_path, **self._fs_open_args_save) as fs_file: json.dump(data, fs_file, **self._save_args) self._invalidate_cache()