Store

class deeptrack.features.Store(feature: Feature, key: Any | Callable[[...], Any], replace: bool | Callable[[...], bool] = False, **kwargs: Any)

Bases: Feature

Store the output of a feature for reuse.

Store evaluates a given feature and stores its output in an internal dictionary. Subsequent calls with the same key will return the stored value unless the replace parameter is set to True. This enables caching and reuse of computed feature outputs.

Parameters

feature: Feature

The feature to evaluate and store.

key: PropertyLike[Any]

The key used to identify the stored output.

replace: PropertyLike[bool], optional

If True, replaces the stored value with the current computation. Defaults to False.

**kwargs: Any

Additional keyword arguments passed to the parent Feature class.

Attributes

__distributed__: bool

Always False for Store, as it handles caching locally.

_store: dict[tuple[Any, tuple[int, …]], Any]

A dictionary used to store the outputs of the evaluated feature.

Methods

get(inputs, key, replace, _ID, **kwargs) -> Any

Evaluate and store the feature output, or return the cached result.

Examples

>>> import deeptrack as dt

Create a Store feature with a key:

>>> import numpy as np
>>>
>>> value_feature = dt.Value(lambda: np.random.rand())
>>> store_feature = dt.Store(feature=value_feature, key="example")

Retrieve and store the value:

>>> output = store_feature(None)  # replace=False
>>> output
0.16627384166489168

Retrieve the stored value without recomputing:

>>> value_feature.new()
0.6541155683335725

>>> cached_output = store_feature(None)  # replace=False
>>> cached_output
0.16627384166489168

Retrieve the stored value while recomputing:

>>> value_feature.new()
0.26025510106604566

>>> cached_output = store_feature(None, replace=True)
>>> cached_output
0.26025510106604566

Methods Summary

get(inputs, key, replace[, _ID])

Evaluate and store the feature output, or return the cached result.

Methods Documentation

get(inputs: Any, key: Any, replace: bool, _ID: tuple[int, ...] = (), **kwargs: Any) → Any

Evaluate and store the feature output, or return the cached result.

Parameters

inputs: Any

Inputs to the feature.

key: Any

The key used to identify the stored output.

replace: bool

If True, replaces the stored value with a new computation.

_ID: tuple[int, …], optional

The unique identifier for the current execution. Defaults to ().

**kwargs: Any

Additional keyword arguments passed to the feature.

Returns

Any

The stored output or a newly computed result.