kedro.extras.datasets.tracking.MetricsDataSet¶
- class kedro.extras.datasets.tracking.MetricsDataSet(filepath, save_args=None, version=None, credentials=None, fs_args=None)[source]¶
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. TheMetricsDataSet
is part of Kedro Experiment Tracking. The dataset is write-only, it is versioned by default and only takes metrics of numeric values.Example usage for the YAML API:
cars: type: metrics.MetricsDataSet filepath: data/09_tracking/cars.json
Example usage for the Python API:
from kedro.extras.datasets.tracking import MetricsDataSet data = {'col1': 1, 'col2': 0.23, 'col3': 0.002} data_set = MetricsDataSet(filepath="test.json") data_set.save(data)
Attributes
Methods
exists
()Checks whether a data set's output already exists by calling the provided _exists() method.
from_config
(name, config[, load_version, ...])Create a data set instance using the configuration provided.
load
()Loads data by delegation to the provided load method.
release
()Release any cached data.
Compute the version the dataset should be loaded with.
Compute the version the dataset should be saved with.
save
(data)Saves data by delegation to the provided save method.
- DEFAULT_SAVE_ARGS: Dict[str, Any] = {'indent': 2}¶
- __init__(filepath, save_args=None, version=None, credentials=None, fs_args=None)¶
Creates a new instance of
JSONDataSet
pointing to a concrete JSON file on a specific filesystem.- Parameters
filepath (
str
) – 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 byfsspec
. Note: http(s) doesn’t support versioning.save_args (
Optional
[Dict
[str
,Any
]]) – 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 (
Optional
[Version
]) – If specified, should be an instance ofkedro.io.core.Version
. If itsload
attribute is None, the latest version will be loaded. If itssave
attribute is None, save version will be autogenerated.credentials (
Optional
[Dict
[str
,Any
]]) – Credentials required to get access to the underlying filesystem. E.g. forGCSFileSystem
it should look like {“token”: None}.fs_args (
Optional
[Dict
[str
,Any
]]) – Extra arguments to pass into underlying filesystem class constructor (e.g. {“project”: “my-project”} forGCSFileSystem
), 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.
- exists()¶
Checks whether a data set’s output already exists by calling the provided _exists() method.
- Return type
bool
- Returns
Flag indicating whether the output already exists.
- Raises
DatasetError – when underlying exists method raises error.
- classmethod from_config(name, config, load_version=None, save_version=None)¶
Create a data set instance using the configuration provided.
- Parameters
name – Data set name.
config – Data set config dictionary.
load_version – Version string to be used for
load
operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.save_version – Version string to be used for
save
operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.
- Returns
An instance of an
AbstractDataset
subclass.- Raises
DatasetError – When the function fails to create the data set from its config.
- load()¶
Loads data by delegation to the provided load method.
- Return type
TypeVar
(_DO
)- Returns
Data returned by the provided load method.
- Raises
DatasetError – When underlying load method raises error.
- release()¶
Release any cached data.
- Raises
DatasetError – when underlying release method raises error.
- Return type
None
- resolve_load_version()¶
Compute the version the dataset should be loaded with.
- Return type
str | None
- resolve_save_version()¶
Compute the version the dataset should be saved with.
- Return type
str | None
- save(data)¶
Saves data by delegation to the provided save method.
- Parameters
data (
TypeVar
(_DI
)) – the value to be saved by provided save method.- Raises
DatasetError – when underlying save method raises error.
FileNotFoundError – when save method got file instead of dir, on Windows.
NotADirectoryError – when save method got file instead of dir, on Unix.
- Return type
None
- versioned = True¶