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pandas-ta/setup.py
T
2020-09-25 09:38:02 -07:00

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2.1 KiB
Python

# -*- coding: utf-8 -*-
from distutils.core import setup
long_description = "An easy to use Python 3 Pandas Extension with 115+ Technical Analysis Indicators. Can be called from a Pandas DataFrame or standalone like TA-Lib. Correlation tested with TA-Lib."
setup(
name ="pandas_ta",
packages =["pandas_ta", "pandas_ta.candles", "pandas_ta.momentum", "pandas_ta.overlap", "pandas_ta.performance", "pandas_ta.statistics", "pandas_ta.trend", "pandas_ta.volatility", "pandas_ta.volume"],
version =".".join(("0", "2", "13b")),
description =long_description,
long_description =long_description,
author ="Kevin Johnson",
author_email ="appliedmathkj@gmail.com",
url ="https://github.com/twopirllc/pandas-ta",
maintainer ="Kevin Johnson",
maintainer_email ="appliedmathkj@gmail.com",
# install_requires=["pandas"],
download_url ="https://github.com/twopirllc/pandas-ta.git",
keywords =["technical analysis", "trading", "python3", "pandas"],
license ="The MIT License (MIT)",
classifiers =[
"Development Status :: 4 - Beta",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Operating System :: OS Independent",
"License :: OSI Approved :: MIT License",
"Natural Language :: English",
"Intended Audience :: Developers",
"Intended Audience :: Financial and Insurance Industry",
"Intended Audience :: Science/Research",
"Topic :: Office/Business :: Financial",
"Topic :: Office/Business :: Financial :: Investment",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Information Analysis",
],
package_data={
"data": ["data/*.csv"],
},
install_requires =["pandas"],
# List additional groups of dependencies here (e.g. development dependencies).
# You can install these using the following syntax, for example:
# $ pip install -e .[dev,test]
extras_require = {
"dev": ["ta-lib", "jupyterlab", "sklearn", "statsmodels"],
"test": ["ta-lib"],
},
)