kedro_datasets_experimental.prophet.ProphetModelDataset

class kedro_datasets_experimental.prophet.ProphetModelDataset(*, filepath, save_args=None, version=None, credentials=None, fs_args=None, metadata=None)[source]

ProphetModelDataset loads/saves Facebook Prophet models to a JSON file using an underlying filesystem (e.g., local, S3, GCS). It uses Prophet’s built-in serialization to handle the JSON file.

Example usage for the YAML API:

model:
  type: custom_datasets.ProphetModelDataset
  filepath: gcs://your_bucket/model.json
  fs_args:
    project: my-project
  credentials: my_gcp_credentials

Example usage for the Python API:

 from kedro_datasets_experimental.prophet import ProphetModelDataset
 from prophet import Prophet
 import pandas as pd

 df = pd.DataFrame(
...     {"ds": ["2024-01-01", "2024-01-02", "2024-01-03"], "y": [100, 200, 300]}
... )

 model = Prophet()
 model.fit(df)
 dataset = ProphetModelDataset(filepath="path/to/model.json")
 dataset.save(model)
 reloaded_model = dataset.load()

Attributes

DEFAULT_FS_ARGS

DEFAULT_SAVE_ARGS

Methods

exists()

Checks whether a dataset's output already exists by calling the provided _exists() method.

from_config(name, config[, load_version, ...])

Create a dataset instance using the configuration provided.

load()

Loads a Prophet model from a JSON file.

preview()

Generate a preview of the JSON dataset with a specified number of items.

release()

Release any cached data.

resolve_load_version()

Compute the version the dataset should be loaded with.

resolve_save_version()

Compute the version the dataset should be saved with.

save(data)

Saves a Prophet model to a JSON file.

DEFAULT_FS_ARGS: dict[str, Any] = {'open_args_save': {'mode': 'w'}}
DEFAULT_SAVE_ARGS: dict[str, Any] = {'indent': 2}
__init__(*, filepath, save_args=None, version=None, credentials=None, fs_args=None, metadata=None)[source]

Creates a new instance of ProphetModelDataset 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 by fsspec. 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 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 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

  • metadata (Optional[dict[str, Any]]) – Any arbitrary metadata. This is ignored by Kedro, but may be consumed by users or external plugins.

exists()

Checks whether a dataset’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 dataset 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 dataset is versioned. Has no effect on the dataset if versioning was not enabled.

  • save_version (Optional[str]) – Version string to be used for save operation if the dataset is versioned. Has no effect on the dataset if versioning was not enabled.

Return type:

AbstractDataset

Returns:

An instance of an AbstractDataset subclass.

Raises:

DatasetError – When the function fails to create the dataset from its config.

load()[source]

Loads a Prophet model from a JSON file.

Returns:

A deserialized Prophet model.

Return type:

Prophet

preview()

Generate a preview of the JSON dataset with a specified number of items.

Return type:

NewType(JSONPreview, str)

Returns:

A string representing the JSON data for previewing.

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:

Optional[str]

resolve_save_version()

Compute the version the dataset should be saved with.

Return type:

Optional[str]

save(data)[source]

Saves a Prophet model to a JSON file.

Parameters:

data (Prophet) – The Prophet model instance to be serialized and saved.

Return type:

None