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Home/ Questions/Q 8124653
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Editorial Team
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Editorial Team
Asked: June 6, 20262026-06-06T06:31:36+00:00 2026-06-06T06:31:36+00:00

Are there any C++ (or C) libs that have NumPy-like arrays with support for

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Are there any C++ (or C) libs that have NumPy-like arrays with support for slicing, vectorized operations, adding and subtracting contents element-by-element, etc.?

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  1. Editorial Team
    Editorial Team
    2026-06-06T06:31:38+00:00Added an answer on June 6, 2026 at 6:31 am

    Here are several free software that may suit your needs.

    1. The GNU Scientific Library is a GPL software written in C. Thus, it has a C-like allocation and way of programming (pointers, etc.). With the GSLwrap, you can have a C++ way of programming, while still using the GSL. GSL has a BLAS implementation, but you can use ATLAS instead of the default CBLAS, if you want even more performances.

    2. The boost/uBLAS library is a BSL library, written in C++ and distributed as a boost package. It is a C++-way of implementing the BLAS standard. uBLAS comes with a few linear algebra functions, and there is an experimental binding to ATLAS.

    3. eigen is a linear algebra library written in C++, distributed under the MPL2 license (starting from version 3.1.1) or LGPL3/GPL2 (older versions). It’s a C++ way of programming, but more integrated than the two others (more algorithms and data structures are available). Eigen claims to be faster than the BLAS implementations above, while not following the de-facto standard BLAS API. Eigen does not seem to put a lot of effort on parallel implementation.

    4. Armadillo is LGPL3 library for C++. It has binding for LAPACK (the library used by numpy). It uses recursive templates and template meta-programming, which is a good point (I don’t know if other libraries are doing it also?).

    5. xtensor is a C++ library that is BSD licensed. It offers A C++ API very similar to that of NumPy. See https://xtensor.readthedocs.io/en/latest/numpy.html for a cheat sheet.

    These alternatives are really good if you just want to get data structures and basic linear algebra. Depending on your taste about style, license or sysadmin challenges (installing big libraries like LAPACK may be difficult), you may choose the one that best suits your needs.

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