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To avoid installing the large SciPy package just to get an array object, this new package was separated and called NumPy. Support for Python 3 was added in 2011 with NumPy version 1.5.0. [15] In 2011, PyPy started development on an implementation of the NumPy API for PyPy. [16] As of 2023, it is not yet fully compatible with NumPy. [17]
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.
This is a list of free and open-source software (FOSS) packages, computer software licensed under free software licenses and open-source licenses. Software that fits the Free Software Definition may be more appropriately called free software; the GNU project in particular objects to their works being referred to as open-source. [1]
Slice semantics potentially differ per object; new semantics can be introduced when operator overloading the indexing operator. With Python standard lists (which are dynamic arrays), every slice is a copy. Slices of NumPy arrays, by contrast, are views onto the same underlying buffer.
An array data structure can be mathematically modeled as an abstract data structure (an abstract array) with two operations get(A, I): the data stored in the element of the array A whose indices are the integer tuple I. set(A, I, V): the array that results by setting the value of that element to V. These operations are required to satisfy the ...
Unlike object orientation which implicitly breaks down data to its constituent parts (or scalar quantities), array orientation looks to group data and apply a uniform handling. Function rank is an important concept to array programming languages in general, by analogy to tensor rank in mathematics: functions that operate on data may be ...
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
On 14 October 2019, version 7.2 was released, with support for Python 3.6.9. [28] On 24 December 2019, version 7.3 was released, with support for Python 3.6.9. [29] On 16 February 2020, the PyPy team announced the move of the source code hosting from Bitbucket to heptapod.net with the repositories of the CFFI (C Foreign Function Interface ...