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]¶
ProphetModelDatasetloads/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
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.
Compute the version the dataset should be loaded with.
Compute the version the dataset should be saved with.
save(data)Saves a Prophet model to a JSON file.
- __init__(*, filepath, save_args=None, version=None, credentials=None, fs_args=None, metadata=None)[source]¶
Creates a new instance of
ProphetModelDatasetpointing 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 itsloadattribute is None, the latest version will be loaded. If itssaveattribute is None, save version will be autogenerated.credentials (
Optional[dict[str,Any]]) – Credentials required to get access to the underlying filesystem. E.g. forGCSFileSystemit 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.openmetadata (
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:
- 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.load_version (
Optional[str]) – Version string to be used forloadoperation 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 forsaveoperation if the dataset is versioned. Has no effect on the dataset if versioning was not enabled.
- Return type:
- Returns:
An instance of an
AbstractDatasetsubclass.- 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.
- release()¶
Release any cached data.
- Raises:
DatasetError – when underlying release method raises error.
- Return type:
- resolve_load_version()¶
Compute the version the dataset should be loaded with.
- resolve_save_version()¶
Compute the version the dataset should be saved with.