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Metadata-Version: 2.1
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Name: numpy
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Version: 1.14.5
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Summary: NumPy: array processing for numbers, strings, records, and objects.
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Home-page: http://www.numpy.org
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Author: Travis E. Oliphant et al.
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Maintainer: NumPy Developers
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Maintainer-email: numpy-discussion@python.org
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License: BSD
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Download-URL: https://pypi.python.org/pypi/numpy
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Platform: Windows
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Platform: Linux
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Platform: Solaris
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Platform: Mac OS-X
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Platform: Unix
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Classifier: Development Status :: 5 - Production/Stable
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Classifier: Intended Audience :: Science/Research
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Classifier: Intended Audience :: Developers
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Classifier: License :: OSI Approved
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Classifier: Programming Language :: C
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Classifier: Programming Language :: Python
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Classifier: Programming Language :: Python :: 2
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Classifier: Programming Language :: Python :: 2.7
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3.4
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Classifier: Programming Language :: Python :: 3.5
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Classifier: Programming Language :: Python :: 3.6
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Classifier: Programming Language :: Python :: Implementation :: CPython
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Classifier: Topic :: Software Development
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Classifier: Topic :: Scientific/Engineering
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Classifier: Operating System :: Microsoft :: Windows
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Classifier: Operating System :: POSIX
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Classifier: Operating System :: Unix
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Classifier: Operating System :: MacOS
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Requires-Python: >=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*
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NumPy is a general-purpose array-processing package designed to
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efficiently manipulate large multi-dimensional arrays of arbitrary
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records without sacrificing too much speed for small multi-dimensional
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arrays. NumPy is built on the Numeric code base and adds features
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introduced by numarray as well as an extended C-API and the ability to
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create arrays of arbitrary type which also makes NumPy suitable for
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interfacing with general-purpose data-base applications.
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There are also basic facilities for discrete fourier transform,
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basic linear algebra and random number generation.
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All numpy wheels distributed from pypi are BSD licensed.
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Windows wheels are linked against the ATLAS BLAS / LAPACK library, restricted
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to SSE2 instructions, so may not give optimal linear algebra performance for
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your machine. See http://docs.scipy.org/doc/numpy/user/install.html for
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alternatives.
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