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  1. Metadata-Version: 2.1
  2. Name: numpy
  3. Version: 1.21.6
  4. Summary: NumPy is the fundamental package for array computing with Python.
  5. Home-page: https://www.numpy.org
  6. Author: Travis E. Oliphant et al.
  7. Maintainer: NumPy Developers
  8. Maintainer-email: numpy-discussion@python.org
  9. License: BSD
  10. Download-URL: https://pypi.python.org/pypi/numpy
  11. Project-URL: Bug Tracker, https://github.com/numpy/numpy/issues
  12. Project-URL: Documentation, https://numpy.org/doc/1.21
  13. Project-URL: Source Code, https://github.com/numpy/numpy
  14. Platform: Windows
  15. Platform: Linux
  16. Platform: Solaris
  17. Platform: Mac OS-X
  18. Platform: Unix
  19. Classifier: Development Status :: 5 - Production/Stable
  20. Classifier: Intended Audience :: Science/Research
  21. Classifier: Intended Audience :: Developers
  22. Classifier: License :: OSI Approved :: BSD License
  23. Classifier: Programming Language :: C
  24. Classifier: Programming Language :: Python
  25. Classifier: Programming Language :: Python :: 3
  26. Classifier: Programming Language :: Python :: 3.7
  27. Classifier: Programming Language :: Python :: 3.8
  28. Classifier: Programming Language :: Python :: 3.9
  29. Classifier: Programming Language :: Python :: 3.10
  30. Classifier: Programming Language :: Python :: 3 :: Only
  31. Classifier: Programming Language :: Python :: Implementation :: CPython
  32. Classifier: Topic :: Software Development
  33. Classifier: Topic :: Scientific/Engineering
  34. Classifier: Typing :: Typed
  35. Classifier: Operating System :: Microsoft :: Windows
  36. Classifier: Operating System :: POSIX
  37. Classifier: Operating System :: Unix
  38. Classifier: Operating System :: MacOS
  39. Requires-Python: >=3.7,<3.11
  40. License-File: LICENSE.txt
  41. License-File: LICENSES_bundled.txt
  42. It provides:
  43. - a powerful N-dimensional array object
  44. - sophisticated (broadcasting) functions
  45. - tools for integrating C/C++ and Fortran code
  46. - useful linear algebra, Fourier transform, and random number capabilities
  47. - and much more
  48. Besides its obvious scientific uses, NumPy can also be used as an efficient
  49. multi-dimensional container of generic data. Arbitrary data-types can be
  50. defined. This allows NumPy to seamlessly and speedily integrate with a wide
  51. variety of databases.
  52. All NumPy wheels distributed on PyPI are BSD licensed.