{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/4"}],"enrichment":{"capability":"Converts and computes statistics across sparse, dense, GPU, and distributed array formats with a unified interface.","skillfed_tags":["array-conversion","sparse-dense","gpu-compute"],"use_cases":["Densify sparse matrices before passing to dense-only algorithms.","Compute row or column statistics across mixed array types without format-specific code.","Move Dask or CuPy arrays to CPU memory for serialization or downstream libraries.","Unify array handling in pipelines that mix dense, sparse, and GPU data.","Calculate aggregate statistics across distributed or GPU-resident arrays."],"what_it_does":"fast-array-utils provides a unified interface to convert and analyze arrays across multiple storage and compute backends\u2014NumPy, SciPy sparse matrices, CuPy GPU arrays, Dask distributed arrays, and file-backed formats like HDF5 and Zarr. It abstracts away the differences between these formats so you can densify sparse data, move arrays between CPU and GPU memory, and compute statistics without rewriting logic for each array type.\n\nThe package is built on top of numpy and array-api-compat, keeping its core lightweight. It targets modern Python (3.12+) and is marked Production/Stable. Use it when you need to work with heterogeneous array sources in the same pipeline\u2014for instance, reading sparse matrices from disk, densifying them, computing row statistics, and optionally moving results to GPU for downstream processing.","worth_installing":"Yes, if you work with multiple array formats (sparse, GPU, distributed, file-backed) and want a single conversion and stats API. The low install friction, active maintenance, and zero known vulnerabilities make it safe to adopt. Be aware of the MPL-2.0 copyleft license if you redistribute. Verify that optional dependencies align with your environment before relying on GPU or Dask features."},"id":"fast-array-utils","links":{"html":"https://skillfed.io/packages/fast-array-utils","md":"https://skillfed.io/packages/fast-array-utils.md","pypi":"https://pypi.org/project/fast-array-utils/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-17","license_spdx":"MPL-2.0","license_treatment":"copyleft","name":"fast-array-utils","python_support":"supports_current","summary":null},"popularity":{"monthly_downloads":417790,"position":6807,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.5"}