mirror of
https://github.com/wassname/pandas-ta.git
synced 2026-06-27 16:10:07 +08:00
Kevin Johnson
74 lines
2.9 KiB
Python
74 lines
2.9 KiB
Python
# -*- coding: utf-8 -*-
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from distutils.core import setup
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long_description = "Pandas Technical Analysis, Pandas TA, is a free, Open Source, and easy to use Technical Analysis library with a Pandas DataFrame Extension. It has over 200 indicators, utility functions and TA Lib Candlestick Patterns. Beyond TA feature generation, it has a flat library structure, it's own DataFrame Extension (called 'ta'), Custom Indicator Studies and Independent Custom Directory."
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setup(
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name="pandas_ta",
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packages=[
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"pandas_ta",
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"pandas_ta.candles",
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"pandas_ta.cycles",
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"pandas_ta.momentum",
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"pandas_ta.overlap",
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"pandas_ta.performance",
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"pandas_ta.statistics",
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"pandas_ta.transform",
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"pandas_ta.trend",
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"pandas_ta.utils",
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"pandas_ta.utils.data",
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"pandas_ta.volatility",
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"pandas_ta.volume"
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],
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version=".".join(("0", "3", "69b")),
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description=long_description,
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long_description=long_description,
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author="Kevin Johnson",
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author_email="appliedmathkj@gmail.com",
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url="https://github.com/twopirllc/pandas-ta",
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maintainer="Kevin Johnson",
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maintainer_email="appliedmathkj@gmail.com",
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download_url="https://github.com/twopirllc/pandas-ta.git",
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keywords=[
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"technical analysis", "trading", "backtest", "trading bot",
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"features",
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"pandas", "numpy", "vectorbt", "yfinance", "polygon",
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"python3"
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],
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license="The MIT License (MIT)",
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classifiers=[
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"Development Status :: 4 - Beta",
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"Programming Language :: Python :: 3.6",
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"Programming Language :: Python :: 3.7",
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"Programming Language :: Python :: 3.8",
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"Programming Language :: Python :: 3.9",
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"Programming Language :: Python :: 3.10",
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"Operating System :: OS Independent",
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"License :: OSI Approved :: MIT License",
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"Natural Language :: English",
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"Intended Audience :: Developers",
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"Intended Audience :: Financial and Insurance Industry",
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"Intended Audience :: Science/Research",
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"Topic :: Office/Business :: Financial",
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"Topic :: Office/Business :: Financial :: Investment",
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"Topic :: Scientific/Engineering",
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"Topic :: Scientific/Engineering :: Information Analysis",
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],
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package_data={
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"data": ["data/*.csv"],
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},
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install_requires=["pandas"],
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# List additional groups of dependencies here (e.g. development dependencies).
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# You can install these using the following syntax, for example:
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# $ pip install -e .[full,test] # locally
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# $ pip install -U pandas_ta[full] # pip
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extras_require={
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"full": [
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"alphaVantage-api", "matplotlib", "mplfinance", "numba", "polygon"
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"python-dotenv", "scipy", "sklearn", "statsmodels", "stochastic",
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"ta-lib", "tqdm", "vectorbt", "yfinance",
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],
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"test": ["ta-lib"],
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},
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)
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