Gets an object from the cache with the given key. Returns `null` if the entry is not found.

Sets an object to the cache with the given key

Creates a derived value.

Compute embeddings and generate 2D projections for a DataFrame column. This is a unified entry point that auto-detects the modality of the i

Creates a stateful derived value.

Compute PageRank scores from a list of edges of a graph using PyTorch sparse matrix power iteration. The graph can be either unweighted (each

Add data to the summarizer

Create a narwhals Series from a list of values via pandas.

* Run the UMAP algorithm to completion.

Detect whether binary data is an image or audio based on magic bytes.

Destroy the instance and release resources

Store a value in the encrypted file cache. This function serializes, encrypts, and stores a value in the file cache using the provided k

Map the inputs by an async function, return a future that resolves to the mapped array (in correct order). Args: inputs: List of ite

Creates a value node.

Retrieve a cached value from the encrypted file cache. This function attempts to load and decrypt a previously cached value using the pr

Set the prop with key to value, only if value is not None. Key can be a dot-separated path for nested properties

Infer the modality by inspecting the first non-null value in the series.

Fill the given rect as occupied

* Invoke the method on target if defined, and if all args are defined.

Convert series to canonical image format: list[{"bytes": bytes}].

Convert raw UMAP k-nearest-neighbor (KNN) arrays into a weighted edge list, which can then be passed into pagerank(). Raw KNN distances

Run a benchmark command that writes a JSON result file. Returns the parsed result dict with 'threads' added, or None on failure.

Async version of ``file_cache_value``. Identical behaviour but *value_func* is awaited on a cache miss.

Return the datasets directory for a benchmark suite.

Retrieve a cached value or compute and cache it if not present. This is a read-through cache helper: if a cached value exists for the given

Convert series to canonical text format: list[str] with nulls as 'null'.

Convert series to canonical vector format: list[ndarray[float32]].