kedro.extras.datasets.pandas.JSONDataSet

class kedro.extras.datasets.pandas.JSONDataSet(filepath, load_args=None, save_args=None, version=None, credentials=None, fs_args=None, layer=None)[source]

Bases: kedro.io.core.AbstractVersionedDataSet

JSONDataSet loads/saves data from/to a JSON file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to handle the json file.

Example:

from kedro.extras.datasets.pandas import JSONDataSet
import pandas as pd

data = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5],
                     'col3': [5, 6]})

# data_set = JSONDataSet(filepath="gcs://bucket/test.json")
data_set = JSONDataSet(filepath="test.json")
data_set.save(data)
reloaded = data_set.load()
assert data.equals(reloaded)

Attributes

JSONDataSet.DEFAULT_LOAD_ARGS
JSONDataSet.DEFAULT_SAVE_ARGS

Methods

JSONDataSet.__init__(filepath[, load_args, …]) Creates a new instance of JSONDataSet pointing to a concrete JSON file on a specific filesystem.
JSONDataSet.exists() Checks whether a data set’s output already exists by calling the provided _exists() method.
JSONDataSet.from_config(name, config[, …]) Create a data set instance using the configuration provided.
JSONDataSet.get_last_load_version() Versioned datasets should override this property to return last loaded version
JSONDataSet.get_last_save_version() Versioned datasets should override this property to return last saved version.
JSONDataSet.invalidate_cache() Invalidate underlying filesystem caches.
JSONDataSet.load() Loads data by delegation to the provided load method.
JSONDataSet.release() Release any cached data.
JSONDataSet.save(data) Saves data by delegation to the provided save method.
DEFAULT_LOAD_ARGS = {}
DEFAULT_SAVE_ARGS = {}
__init__(filepath, load_args=None, save_args=None, version=None, credentials=None, fs_args=None, layer=None)[source]

Creates a new instance of JSONDataSet pointing to a concrete JSON file on a specific filesystem.

Parameters:
  • filepath (str) – Filepath 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.
  • load_args (Optional[Dict[str, Any]]) – Pandas options for loading JSON files. Here you can find all available arguments: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_json.html All defaults are preserved.
  • save_args (Optional[Dict[str, Any]]) – Pandas options for saving JSON files. Here you can find all available arguments: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_json.html All defaults are preserved, but “index”, which is set to False.
  • version (Optional[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.
  • credentials (Optional[Dict[str, Any]]) – Credentials required to get access to the underlying filesystem. E.g. for GCSFileSystem it should look like {‘token’: None}.
  • fs_args (Optional[Dict[str, Any]]) – Extra arguments to pass into underlying filesystem class. E.g. for GCSFileSystem class: {project: ‘my-project’, …}.
  • layer (Optional[str]) – The data layer according to the data engineering convention: https://kedro.readthedocs.io/en/stable/06_resources/01_faq.html#what-is-data-engineering-convention
Return type:

None

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 (str) – Data set name.
  • config (Dict[str, Any]) – Data set config dictionary.
  • load_version (Optional[str]) – 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 (Optional[str]) – 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.
Return type:

AbstractDataSet

Returns:

An instance of an AbstractDataSet subclass.

Raises:

DataSetError – When the function fails to create the data set from its config.

get_last_load_version()

Versioned datasets should override this property to return last loaded version

Return type:Optional[str]
get_last_save_version()

Versioned datasets should override this property to return last saved version.

Return type:Optional[str]
invalidate_cache()[source]

Invalidate underlying filesystem caches.

Return type:None
load()

Loads data by delegation to the provided load method.

Return type:Any
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 exists method raises error.
Return type:None
save(data)

Saves data by delegation to the provided save method.

Parameters:data (Any) – the value to be saved by provided save method.
Raises:DataSetError – when underlying save method raises error.
Return type:None