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@@ -1,28 +1,8 @@ | ||
#!/usr/bin/env python3 | ||
""" NumPy is the fundamental package for array computing with Python. | ||
It provides: | ||
- a powerful N-dimensional array object | ||
- sophisticated (broadcasting) functions | ||
- tools for integrating C/C++ and Fortran code | ||
- useful linear algebra, Fourier transform, and random number capabilities | ||
- and much more | ||
Besides its obvious scientific uses, NumPy can also be used as an efficient | ||
multi-dimensional container of generic data. Arbitrary data-types can be | ||
defined. This allows NumPy to seamlessly and speedily integrate with a wide | ||
variety of databases. | ||
All NumPy wheels distributed on PyPI are BSD licensed. | ||
NumPy requires ``pytest`` and ``hypothesis``. Tests can then be run after | ||
installation with:: | ||
python -c 'import numpy; numpy.test()' | ||
""" | ||
DOCLINES = (__doc__ or '').split("\n") | ||
Numpy build options can be modified with a site.cfg file. | ||
See site.cfg.example for a template and more information. | ||
""" | ||
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import os | ||
from pathlib import Path | ||
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@@ -435,8 +415,8 @@ def setup_package(): | |
name='numpy', | ||
maintainer="NumPy Developers", | ||
maintainer_email="[email protected]", | ||
description=DOCLINES[0], | ||
long_description= Path("README.md").read_text(encoding="utf-8"), | ||
description="Fundamental package for array computing in Python", | ||
long_description=Path("README.md").read_text(encoding="utf-8"), | ||
long_description_content_type="text/markdown", | ||
url="https://www.numpy.org", | ||
author="Travis E. Oliphant et al.", | ||
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