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setup.py
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#!/usr/bin/env python3
import re
import sys
import os
from distutils.core import setup
if sys.version_info < (3, 5):
sys.exit('Price_predictor requires Python >= 3.5.')
abs_path = os.path.abspath(os.path.dirname(__file__))
def get_version():
with open(os.path.join(abs_path, 'price_predictor/__init__.py')) as f:
for line in f:
m = re.match("__version__ = '(.*)'", line)
if m:
return m.group(1)
raise SystemExit("Could not find version string.")
actual_version = str(get_version())
setup(
name = 'price_predictor',
packages = ['price_predictor'],
version = actual_version,
license='MIT',
description = 'Quickly predict the future prices of financial instruments with a customizable LSTM Recurrent Neural Network',
long_description = open(os.path.join(abs_path, 'README.rst')).read(),
author = 'Ludovico Lemma',
author_email = 'lwdovico@protonmail.com',
url = 'https://github.com/ludovicolemma/price-predictor',
download_url = 'https://github.com/ludovicolemma/price-predictor/archive/refs/tags/v{version}.tar.gz'.format(version = actual_version),
keywords = ['LSTM',
'Machine Learning',
'Market Price Prediction',
'Stock Price Prediction',
'Financial Forecasting'],
python_requires='>=3.5',
install_requires=[
'numpy',
'pandas',
'matplotlib',
'sklearn',
'tensorflow',
],
entry_points={'console_scripts': ['price_predictor=price_predictor.__main__:main']},
classifiers=[
'Development Status :: 3 - Alpha',
'Intended Audience :: Financial and Insurance Industry',
'Intended Audience :: Developers',
'Intended Audience :: End Users/Desktop',
'Topic :: Software Development :: Build Tools',
'Topic :: Office/Business :: Financial :: Investment',
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
],
)