# numba **Repository Path**: giteebytsl/numba ## Basic Information - **Project Name**: numba - **Description**: No description available - **Primary Language**: Unknown - **License**: BSD-2-Clause - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2021-04-13 - **Last Updated**: 2021-04-13 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README ***** Numba ***** .. image:: https://badges.gitter.im/numba/numba.svg :target: https://gitter.im/numba/numba?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge :alt: Gitter .. image:: https://img.shields.io/badge/discuss-on%20discourse-blue :target: https://numba.discourse.group/ :alt: Discourse .. image:: https://zenodo.org/badge/3659275.svg :target: https://zenodo.org/badge/latestdoi/3659275 :alt: Zenodo DOI A Just-In-Time Compiler for Numerical Functions in Python ######################################################### Numba is an open source, NumPy-aware optimizing compiler for Python sponsored by Anaconda, Inc. It uses the LLVM compiler project to generate machine code from Python syntax. Numba can compile a large subset of numerically-focused Python, including many NumPy functions. Additionally, Numba has support for automatic parallelization of loops, generation of GPU-accelerated code, and creation of ufuncs and C callbacks. For more information about Numba, see the Numba homepage: https://numba.pydata.org Supported Platforms =================== * Operating systems and CPUs: - Linux: x86 (32-bit), x86_64, ppc64le (POWER8 and 9), ARMv7 (32-bit), ARMv8 (64-bit) - Windows: x86, x86_64 - macOS: x86_64, (M1/Arm64, unofficial support only) - \*BSD: (unofficial support only) * (Optional) Accelerators and GPUs: * NVIDIA GPUs (Kepler architecture or later) via CUDA driver on Linux, Windows, macOS (< 10.14) * AMD GPUs via ROCm driver on Linux Dependencies ============ * Python versions: 3.6-3.9 * llvmlite 0.36.* * NumPy >=1.15 (can build with 1.11 for ABI compatibility) Optionally: * SciPy >=1.0.0 (for ``numpy.linalg`` support) Installing ========== The easiest way to install Numba and get updates is by using the Anaconda Distribution: https://www.anaconda.com/download :: $ conda install numba For more options, see the Installation Guide: https://numba.readthedocs.io/en/stable/user/installing.html Documentation ============= https://numba.readthedocs.io/en/stable/index.html Mailing Lists ============= Join the Numba mailing list numba-users@continuum.io: https://groups.google.com/a/continuum.io/d/forum/numba-users Some old archives are at: http://librelist.com/browser/numba/ Continuous Integration ====================== .. image:: https://dev.azure.com/numba/numba/_apis/build/status/numba.numba?branchName=master :target: https://dev.azure.com/numba/numba/_build/latest?definitionId=1?branchName=master :alt: Azure Pipelines