Minimal and clean examples of machine learning algorithms implementations
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from setuptools import setup, find_packages
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from codecs import open
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from os import path
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__version__ = '0.0.1'
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here = path.abspath(path.dirname(__file__))
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# Get the long description from the README file
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with open(path.join(here, 'README.md'), encoding='utf-8') as f:
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long_description = f.read()
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# get the dependencies and installs
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with open(path.join(here, 'requirements.txt'), encoding='utf-8') as f:
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all_reqs = f.read().split('\n')
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install_requires = [x.strip() for x in all_reqs if 'git+' not in x]
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dependency_links = [x.strip().replace('git+', '') for x in all_reqs if x.startswith('git+')]
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setup(
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name='mla',
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version=__version__,
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description='A collection of minimal and clean implementations of machine learning algorithms.',
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long_description=long_description,
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url='https://github.com/rushter/mla',
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download_url='https://github.com/rushter/mla/tarball/' + __version__,
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license='MIT',
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packages=find_packages(exclude=['docs', 'tests*']),
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include_package_data=True,
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author='Artem Golubin',
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install_requires=install_requires,
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setup_requires=['numpy>=1.10', 'scipy>=0.17'],
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dependency_links=dependency_links,
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author_email='gh@rushter.com'
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)
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