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  2. 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]

  3. CuPy - Wikipedia

    en.wikipedia.org/wiki/CuPy

    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.

  4. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]

  5. Spyder (software) - Wikipedia

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

    It is an open-source cross-platform integrated development environment (IDE) for scientific programming in the Python language.Spyder integrates with a number of prominent packages in the scientific Python stack, including NumPy, SciPy, Matplotlib, pandas, IPython, SymPy and Cython, as well as other open-source software.

  6. CellProfiler - Wikipedia

    en.wikipedia.org/wiki/CellProfiler

    CellProfiler interfaces with the high-performance scientific libraries NumPy and SciPy for many mathematical operations, the Open Microscopy Environment [11] Consortium’s Bio-Formats library for reading more than 100 image file formats, ImageJ for use of plugins and macros, and ilastik for pixel-based classification. [12]

  7. Math Kernel Library - Wikipedia

    en.wikipedia.org/wiki/Math_Kernel_Library

    As of 2020, Intel's MKL remains the numeric library installed by default along with many pre-compiled mathematical applications on Windows (such as NumPy, SymPy). [12] [13] Although relying on the MKL, MATLAB implemented a workaround starting with Release 2020a which ensures full support for AVX2 by the MKL also for non Intel (AMD) CPUs. [14]

  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. It also exposes low-level APIs ...

  9. Numba - Wikipedia

    en.wikipedia.org/wiki/Numba

    Numba is an open-source JIT compiler that translates a subset of Python and NumPy into fast machine code using LLVM, via the llvmlite Python package.It offers a range of options for parallelising Python code for CPUs and GPUs, often with only minor code changes.