2019-05-08 00:10:54 +04:00
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import setuptools
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2018-02-26 20:11:29 +04:00
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2019-05-08 05:18:57 +04:00
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#with open("README.md", "r") as fh:
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# long_description = fh.read()
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2019-05-08 00:10:54 +04:00
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setuptools.setup(
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2018-02-26 20:11:29 +04:00
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name='pyFTS',
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2021-01-13 00:40:21 +04:00
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packages=['pyFTS', 'pyFTS.benchmarks', 'pyFTS.common', 'pyFTS.common.transformations', 'pyFTS.data',
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'pyFTS.models.ensemble', 'pyFTS.models', 'pyFTS.models.seasonal', 'pyFTS.partitioners',
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'pyFTS.probabilistic', 'pyFTS.tests', 'pyFTS.models.nonstationary', 'pyFTS.models.multivariate',
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2019-05-08 00:10:54 +04:00
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'pyFTS.models.incremental', 'pyFTS.hyperparam', 'pyFTS.distributed', 'pyFTS.fcm'],
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2019-05-07 23:24:59 +04:00
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version='1.6',
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2018-02-26 20:11:29 +04:00
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description='Fuzzy Time Series for Python',
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2019-05-08 05:18:57 +04:00
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long_description='Fuzzy Time Series for Python',
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2019-05-08 00:10:54 +04:00
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long_description_content_type="text/markdown",
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2018-02-26 20:11:29 +04:00
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author='Petronio Candido L. e Silva',
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author_email='petronio.candido@gmail.com',
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2018-10-29 23:48:05 +04:00
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url='https://pyfts.github.io/pyFTS/',
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2019-05-07 23:24:59 +04:00
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download_url='https://github.com/PYFTS/pyFTS/archive/pkg1.6.tar.gz',
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2018-02-26 20:11:29 +04:00
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keywords=['forecasting', 'fuzzy time series', 'fuzzy', 'time series forecasting'],
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2018-03-06 01:32:23 +04:00
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classifiers=[
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'Programming Language :: Python :: 3',
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'Programming Language :: Python :: 3.4',
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'Programming Language :: Python :: 3.5',
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'Programming Language :: Python :: 3.6',
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2019-05-08 00:10:54 +04:00
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'Intended Audience :: Science/Research',
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'Intended Audience :: Developers',
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'Intended Audience :: Education',
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'Topic :: Scientific/Engineering',
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'Development Status :: 5 - Production/Stable'
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2019-05-07 23:24:59 +04:00
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]
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2017-07-07 17:54:28 +04:00
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)
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