{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/6"}],"enrichment":{"capability":"Provides a unified wrapper around NumPy, CuPy, PyTorch, Dask, JAX, ndonnx, and sparse that implements the Array API standard, allowing code to work consistently across different array libraries.","skillfed_tags":["array-api-standard","multi-backend","interoperability"],"use_cases":["Build a scientific library that works with NumPy, CuPy, PyTorch, Dask, JAX, ndonnx, and sparse without maintaining separate code paths for each.","Write code that can run on CPU or GPU by swapping the array backend without changing operations.","Create a machine learning framework that accepts arrays from any supported library and processes them uniformly.","Migrate code between array libraries by changing only the import statement, not the operations themselves.","Develop educational materials or examples that work across multiple array libraries without duplication."],"what_it_does":"array-api-compat is a lightweight wrapper that lets you write array code once and run it against multiple array libraries\u2014NumPy, CuPy, PyTorch, Dask, JAX, ndonnx, and sparse\u2014all through a single standardized interface defined by the Array API standard. It abstracts away library-specific quirks and naming differences so your code doesn't need conditional imports or branching logic for different backends.\n\nThe package has no runtime dependencies of its own and is designed to be a thin compatibility layer. You import from it instead of directly from your array library, and it delegates to whichever backend you're using. This is useful when building libraries or applications that need to support multiple array backends without duplicating logic, or when you want to let users choose their preferred array library without rewriting your code.","worth_installing":"Yes, if you are building a library or application that needs to support multiple array backends. The package is actively maintained, has no external dependencies, and MIT-licensed. Install it if you want to write array code once and let users choose their backend; skip it if you are locked to a single array library."},"id":"array-api-compat","links":{"html":"https://skillfed.io/packages/array-api-compat","md":"https://skillfed.io/packages/array-api-compat.md","pypi":"https://pypi.org/project/array-api-compat/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-07","license_spdx":"MIT","license_treatment":"permissive","name":"array-api-compat","python_support":"supports_current","summary":"A wrapper around NumPy and other array libraries to make them compatible with the Array API standard"},"popularity":{"monthly_downloads":2341327,"position":3125,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.15.0"}