setup.py 1.7 KB

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  1. #!/usr/bin/env python
  2. # -*- encoding: utf-8 -*-
  3. from __future__ import absolute_import
  4. from __future__ import print_function
  5. import io
  6. import re
  7. from glob import glob
  8. from os.path import basename
  9. from os.path import dirname
  10. from os.path import join
  11. from os.path import splitext
  12. from setuptools import find_packages
  13. from setuptools import setup
  14. def read(*names, **kwargs):
  15. return io.open(
  16. join(dirname(__file__), *names),
  17. encoding=kwargs.get('encoding', 'utf8')
  18. ).read()
  19. setup(
  20. name="drs-bloom-filter",
  21. version="1.01",
  22. packages=find_packages('src'),
  23. package_dir={'': 'src'},
  24. py_modules=[splitext(basename(path))[0] for path in glob('src/*.py')],
  25. # scripts=['drs_bloom_filter.py', 'python2x3.py'],
  26. # metadata for upload to PyPI
  27. author="Daniel Richard Stromberg",
  28. author_email="strombrg@gmail.com",
  29. description='Pure Python Bloom Filter module',
  30. long_description="""
  31. A pure python bloom filter (low storage requirement, probabilistic
  32. set datastructure) is provided. It is known to work on CPython 2.x,
  33. CPython 3.x, Pypy and Jython.
  34. Includes mmap, in-memory and disk-seek backends.
  35. The user specifies the desired maximum number of elements and the
  36. desired maximum false positive probability, and the module
  37. calculates the rest.
  38. """,
  39. license="MIT",
  40. keywords="probabilistic set datastructure",
  41. url='http://stromberg.dnsalias.org/~strombrg/drs-bloom-filter/',
  42. platforms='Cross platform',
  43. classifiers=[
  44. "Development Status :: 5 - Production/Stable",
  45. "Intended Audience :: Developers",
  46. "Programming Language :: Python :: 2",
  47. "Programming Language :: Python :: 3",
  48. ],
  49. )