Numpy Interface

The homogeneous N-dimensional array interface is a default mechanism for objects to share N-dimensional array memory and information. The interface consists of a Python-side and a C-side using two attributes. Objects wishing to be considered an N-dimensional array in application code should support at least one of these attributes.

Numpy and Scipy Documentation. Welcome! This is the documentation for Numpy and Scipy. For contributors

correction - with the right 'data' value your holder works in np.array. np.array is definitely not going to work since it expects an iterable, some things like a list of lists, and parses the individual values.. There is a low level constructor, np.ndarray that takes a buffer parameter. And a np.frombuffer.. But my impression is that x.__array_interface__'data'0 is a integer

Want to make it easy to manipulate the data with NumPy, or whatever other library, but would not like to have NumPy as a dependency. Currently, 3 solutions the quotoldquot buffer interface the array interface the quotnewquot buffer interface

The first set of interoperability features from the NumPy API allows foreign objects to be treated as NumPy arrays whenever possible. When NumPy functions encounter a foreign object, they will try in order The buffer protocol, described in the Python C-API documentation. The __array_interface__ protocol, described in this page. A precursor

This page describes the NumPy-specific API for accessing the contents of a NumPy array from other C extensions. The array interface sometimes called array protocol was created in 2005 as a means for array-like Python objects to reuse each other's data buffers intelligently whenever possible. The homogeneous N-dimensional array interface

NumPy reference Release 2.3. Date June 09, 2025. This reference manual details functions, modules, and objects included in NumPy, describing what they are and what they do. For learning how to use NumPy, see the complete documentation. Python API

Note. This page describes the numpy-specific API for accessing the contents of a numpy array from other C extensions. PEP 3118 - The Revised Buffer Protocol introduces similar, standardized API to Python 2.6 and 3.0 for any extension module to use. Cython's buffer array support uses the PEP 3118 API see the Cython numpy tutorial.Cython provides a way to write code that supports the buffer

6.3.1. The array API . numpy_interface array objects behave very similar to NumPy arrays. In fact, arrays from vtkDataSet subclasses are instances of VTKArray, which is a subclass of numpy.ndarray.Arrays from vtkCompositeDataSet and subclasses are not NumPy arrays, but they behave very similarly. We will outline the differences in a separate section. Let's start with the basi

NumPy is the primary array programming library for Python here its fundamental concepts are reviewed and its evolution into a flexible interoperability layer between increasingly specialized