Python Array API Standard: Toward Array Interoperability in the Scientific Python Ecosystem

The Python array API standard specifies standardized application programming interfaces (APIs) and behaviors for array and tensor objects and operations as commonly found in libraries such as NumPy Harris2020a, CuPy Okuta2017a, PyTorch Paszke2019a, JAX Bradbury2018a, TensorFlow Abadi2016a, Dask Rocklin2015a, and MXNet Chen2015a. The establishment and subsequent adoption of the standard aims to reduce ecosystem fragmentation and facilitate array library interoperability in user code and among array-consuming libraries, such as scikit-learn Pedregosa2011a and SciPy Virtanen2020a. A key benefit of array interoperability for downstream consumers of the standard is device agnosticism, whereby previously CPU-bound implementations can more readily leverage hardware acceleration via graphics processing units (GPUs), tensor processing units (TPUs), and other accelerator devices.