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Metadata-Version: 2.1 Name: numpy Version: 1.13.3 Summary: NumPy: array processing for numbers, strings, records, and objects. Home-page: http://www.numpy.org Author: Travis E. Oliphant et al. Maintainer: NumPy Developers Maintainer-email: numpy-discussion@python.org License: BSD Download-URL: http://sourceforge.net/projects/numpy/files/NumPy/ Platform: Windows Platform: Linux Platform: Solaris Platform: Mac OS-X Platform: Unix Classifier: Development Status :: 5 - Production/Stable Classifier: Intended Audience :: Science/Research Classifier: Intended Audience :: Developers Classifier: License :: OSI Approved Classifier: Programming Language :: C Classifier: Programming Language :: Python Classifier: Programming Language :: Python :: 2 Classifier: Programming Language :: Python :: 2.7 Classifier: Programming Language :: Python :: 3 Classifier: Programming Language :: Python :: 3.4 Classifier: Programming Language :: Python :: 3.5 Classifier: Programming Language :: Python :: 3.6 Classifier: Programming Language :: Python :: Implementation :: CPython Classifier: Topic :: Software Development Classifier: Topic :: Scientific/Engineering Classifier: Operating System :: Microsoft :: Windows Classifier: Operating System :: POSIX Classifier: Operating System :: Unix Classifier: Operating System :: MacOS Requires-Python: >=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.* License-File: LICENSE.txt NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type which also makes NumPy suitable for interfacing with general-purpose data-base applications. There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation. All numpy wheels distributed from pypi are BSD licensed. Windows wheels are linked against the ATLAS BLAS / LAPACK library, restricted to SSE2 instructions, so may not give optimal linear algebra performance for your machine. See http://docs.scipy.org/doc/numpy/user/install.html for alternatives.