LazyDataLoader

class dtaianomaly.data.LazyDataLoader(do_caching: bool = False)

A lazy dataloader for anomaly detection workflows.

This is a data loading utility to point towards a specific data set and to load it at a later point in time during execution of a workflow.

This way we limit memory usage and allow for virtually unlimited scaling of the number of data sets in a workflow.

Parameters:

do_cachingbool, default=False

Whether to cache the loaded data or not.

Attributes:

cache_DataSet

Cached version of the loaded data set. Only available if do_caching==True and the data has been loaded before.

load() → DataSet

Load the time series.

Load the dataset. If do_caching==True, the loaded will be saved in the cache if no cache is available yet, and the cached data will be returned.

Returns:

DataSet

The loaded dataset.