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%global _empty_manifest_terminate_build 0
Name: python-stock-analysis-engine
Version: 1.9.15
Release: 1
Summary: Backtest 1000s of minute-by-minute trading algorithms. Automated pricing data ingestion from: IEX Cloud (https://iexcloud.io), Tradier (https://tradier.com) and FinViz. Datasets and trading performance automatically compressed and published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes with Helm and docker-compose. >150 million trading history rows generated from +5000 algorithms
License: Apache Software License
URL: https://github.com/AlgoTraders/stock-analysis-engine
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/af/0a/840074fc4cf3817a22b590d07794d3367d896e78d26f9b416a7ed7a917b7/stock-analysis-engine-1.9.15.tar.gz
BuildArch: noarch
Requires: python3-boto3
Requires: python3-bs4
Requires: python3-celery
Requires: python3-celery[redis]
Requires: python3-colorlog
Requires: python3-coverage
Requires: python3-flake8
Requires: python3-future
Requires: python3-matplotlib
Requires: python3-mock
Requires: python3-numpy
Requires: python3-pandas
Requires: python3-pep8
Requires: python3-pycodestyle
Requires: python3-pylint
Requires: python3-recommonmark
Requires: python3-redis
Requires: python3-seaborn
Requires: python3-sphinx
Requires: python3-sphinx-autobuild
Requires: python3-sphinx-rtd-theme
Requires: python3-spylunking
Requires: python3-tabulate
Requires: python3-trading-calendars
Requires: python3-unittest2
Requires: python3-urllib3
Requires: python3-ujson
Requires: python3-vprof
Requires: python3-awscli
Requires: python3-h5py
Requires: python3-keras
Requires: python3-scikit-learn
Requires: python3-tables
Requires: python3-ta-lib
Requires: python3-tensorflow
%description
Build and tune investment algorithms for use with `artificial intelligence (deep neural networks) <https://github.com/AlgoTraders/stock-analysis-engine/blob/master/compose/docker/notebooks/Comparing-3-Deep-Neural-Networks-Trained-to-Predict-a-Stocks-Closing-Price-Using-The-Analysis-Engine.ipynb>`__ with a distributed stack for running backtests using live pricing data on publicly traded companies with automated datafeeds from: `IEX Cloud <https://iexcloud.io/>`__, `Tradier <https://tradier.com/>`__ and `FinViz <https://finviz.com>`__ (includes: pricing, options, news, dividends, daily, intraday, screeners, statistics, financials, earnings, and more).
Kubernetes users please refer to `the Helm guide to get started <https://stock-analysis-engine.readthedocs.io/en/latest/deploy_on_kubernetes_using_helm.html>`__ and `Metalnetes for running multiple Analysis Engines at the same time on a bare-metal server <https://metalnetes.readthedocs.io/en/latest/#>`__
%package -n python3-stock-analysis-engine
Summary: Backtest 1000s of minute-by-minute trading algorithms. Automated pricing data ingestion from: IEX Cloud (https://iexcloud.io), Tradier (https://tradier.com) and FinViz. Datasets and trading performance automatically compressed and published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes with Helm and docker-compose. >150 million trading history rows generated from +5000 algorithms
Provides: python-stock-analysis-engine
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-stock-analysis-engine
Build and tune investment algorithms for use with `artificial intelligence (deep neural networks) <https://github.com/AlgoTraders/stock-analysis-engine/blob/master/compose/docker/notebooks/Comparing-3-Deep-Neural-Networks-Trained-to-Predict-a-Stocks-Closing-Price-Using-The-Analysis-Engine.ipynb>`__ with a distributed stack for running backtests using live pricing data on publicly traded companies with automated datafeeds from: `IEX Cloud <https://iexcloud.io/>`__, `Tradier <https://tradier.com/>`__ and `FinViz <https://finviz.com>`__ (includes: pricing, options, news, dividends, daily, intraday, screeners, statistics, financials, earnings, and more).
Kubernetes users please refer to `the Helm guide to get started <https://stock-analysis-engine.readthedocs.io/en/latest/deploy_on_kubernetes_using_helm.html>`__ and `Metalnetes for running multiple Analysis Engines at the same time on a bare-metal server <https://metalnetes.readthedocs.io/en/latest/#>`__
%package help
Summary: Development documents and examples for stock-analysis-engine
Provides: python3-stock-analysis-engine-doc
%description help
Build and tune investment algorithms for use with `artificial intelligence (deep neural networks) <https://github.com/AlgoTraders/stock-analysis-engine/blob/master/compose/docker/notebooks/Comparing-3-Deep-Neural-Networks-Trained-to-Predict-a-Stocks-Closing-Price-Using-The-Analysis-Engine.ipynb>`__ with a distributed stack for running backtests using live pricing data on publicly traded companies with automated datafeeds from: `IEX Cloud <https://iexcloud.io/>`__, `Tradier <https://tradier.com/>`__ and `FinViz <https://finviz.com>`__ (includes: pricing, options, news, dividends, daily, intraday, screeners, statistics, financials, earnings, and more).
Kubernetes users please refer to `the Helm guide to get started <https://stock-analysis-engine.readthedocs.io/en/latest/deploy_on_kubernetes_using_helm.html>`__ and `Metalnetes for running multiple Analysis Engines at the same time on a bare-metal server <https://metalnetes.readthedocs.io/en/latest/#>`__
%prep
%autosetup -n stock-analysis-engine-1.9.15
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-stock-analysis-engine -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.9.15-1
- Package Spec generated
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