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  2. PyPy - Wikipedia

    en.wikipedia.org/wiki/PyPy

    On 20 June 2014, PyPy3 was declared stable [14] and introduced compatibility with the more modern Python 3. It was released alongside PyPy 2.3.1 and bears the same version number. On 21 March 2017, the PyPy project released version 5.7 of both PyPy and PyPy3, with the latter introducing beta-quality support for Python 3.5. [25]

  3. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    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]

  4. pip (package manager) - Wikipedia

    en.wikipedia.org/wiki/Pip_(package_manager)

    pip (also known by Python 3's alias pip3) is a package-management system written in Python and is used to install and manage software packages. [4] The Python Software Foundation recommends using pip for installing Python applications and its dependencies during deployment. [5]

  5. CuPy - Wikipedia

    en.wikipedia.org/wiki/CuPy

    CuPy is a part of the NumPy ecosystem array libraries [7] and is widely adopted to utilize GPU with Python, [8] especially in high-performance computing environments such as Summit, [9] Perlmutter, [10] EULER, [11] and ABCI.

  6. Python Package Index - Wikipedia

    en.wikipedia.org/wiki/Python_Package_Index

    The Python Distribution Utilities (distutils) Python module was first added to the Python standard library in the 1.6.1 release, in September 2000, and in the 2.0 release, in October 2000, nine years after the first Python release in February 1991, with the goal of simplifying the process of installing third-party Python packages.

  7. List of Python software - Wikipedia

    en.wikipedia.org/wiki/List_of_Python_software

    NumPy, a BSD-licensed library that adds support for the manipulation of large, multi-dimensional arrays and matrices; it also includes a large collection of high-level mathematical functions. NumPy serves as the backbone for a number of other numerical libraries, notably SciPy. De facto standard for matrix/tensor operations in Python.

  8. Dask (software) - Wikipedia

    en.wikipedia.org/wiki/Dask_(software)

    Dask is an open-source Python library for parallel computing.Dask [1] scales Python code from multi-core local machines to large distributed clusters in the cloud. Dask provides a familiar user interface by mirroring the APIs of other libraries in the PyData ecosystem including: Pandas, scikit-learn and NumPy.

  9. PyCharm - Wikipedia

    en.wikipedia.org/wiki/PyCharm

    PyCharm is an integrated development environment (IDE) used for programming in Python.It provides code analysis, a graphical debugger, an integrated unit tester, integration with version control systems, and supports web development with Django.