automatic import of python-gs-quant

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+%global _empty_manifest_terminate_build 0
+Name:		python-gs-quant
+Version:	0.9.100
+Release:	1
+Summary:	Goldman Sachs Quant
+License:	http://www.apache.org/licenses/LICENSE-2.0
+URL:		https://marquee.gs.com
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/d7/55/401ac871981c1617f602edbb4d1e0888236e28426c549381232207636e8e/gs_quant-0.9.100.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-asteval
+Requires:	python3-aenum
+Requires:	python3-backoff
+Requires:	python3-cachetools
+Requires:	python3-certifi
+Requires:	python3-dataclasses-json
+Requires:	python3-deprecation
+Requires:	python3-funcsigs
+Requires:	python3-inflection
+Requires:	python3-lmfit
+Requires:	python3-more-itertools
+Requires:	python3-msgpack
+Requires:	python3-nest-asyncio
+Requires:	python3-opentracing
+Requires:	python3-pandas
+Requires:	python3-pydash
+Requires:	python3-dateutil
+Requires:	python3-requests
+Requires:	python3-tqdm
+Requires:	python3-websockets
+Requires:	python3-dataclasses
+Requires:	python3-scipy
+Requires:	python3-statsmodels
+Requires:	python3-typing
+Requires:	python3-scipy
+Requires:	python3-statsmodels
+Requires:	python3-scipy
+Requires:	python3-wheel
+Requires:	python3-sphinx
+Requires:	python3-sphinx-rtd-theme
+Requires:	python3-sphinx-autodoc-typehints
+Requires:	python3-pytest
+Requires:	python3-pytest-cov
+Requires:	python3-pytest-mock
+Requires:	python3-pytest-ordering
+Requires:	python3-testfixtures
+Requires:	python3-gs-quant-internal
+Requires:	python3-jupyter
+Requires:	python3-matplotlib
+Requires:	python3-seaborn
+Requires:	python3-treelib
+Requires:	python3-pytest
+Requires:	python3-pytest-cov
+Requires:	python3-pytest-mock
+Requires:	python3-pytest-ordering
+Requires:	python3-testfixtures
+Requires:	python3-nbconvert
+Requires:	python3-nbformat
+Requires:	python3-jupyter-client
+Requires:	python3-quant-extensions
+
+%description
+# GS Quant
+
+**GS Quant** is a Python toolkit for quantitative finance, created on top of one of the world’s most powerful risk transfer platforms. Designed to accelerate development of quantitative trading strategies and risk management solutions, crafted over 25 years of experience navigating global markets.
+
+It is created and maintained by quantitative developers (quants) at Goldman Sachs to enable the development of trading strategies and analysis of derivative products. GS Quant can be used to facilitate derivative structuring, trading, and risk management, or as a set of statistical packages for data analytics applications.
+
+Please refer to [Goldman Sachs Developer](https://developer.gs.com/docs/gsquant/) for additional information.
+
+## Requirements
+
+* Python 3.6 or greater
+* Access to PIP package manager
+
+## Installation
+
+```
+pip install gs-quant
+```
+
+## Examples
+
+You can find examples, guides and tutorials in the respective folders as well as on [Goldman Sachs Developer](https://developer.gs.com/docs/gsquant/).
+
+## Contributions
+
+Contributions are encouraged! Please see CONTRIBUTING.MD for more details.
+
+## Help
+
+Please reach out to `gs-quant@gs.com` with any questions, comments or feedback.
+
+
+
+
+%package -n python3-gs-quant
+Summary:	Goldman Sachs Quant
+Provides:	python-gs-quant
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-gs-quant
+# GS Quant
+
+**GS Quant** is a Python toolkit for quantitative finance, created on top of one of the world’s most powerful risk transfer platforms. Designed to accelerate development of quantitative trading strategies and risk management solutions, crafted over 25 years of experience navigating global markets.
+
+It is created and maintained by quantitative developers (quants) at Goldman Sachs to enable the development of trading strategies and analysis of derivative products. GS Quant can be used to facilitate derivative structuring, trading, and risk management, or as a set of statistical packages for data analytics applications.
+
+Please refer to [Goldman Sachs Developer](https://developer.gs.com/docs/gsquant/) for additional information.
+
+## Requirements
+
+* Python 3.6 or greater
+* Access to PIP package manager
+
+## Installation
+
+```
+pip install gs-quant
+```
+
+## Examples
+
+You can find examples, guides and tutorials in the respective folders as well as on [Goldman Sachs Developer](https://developer.gs.com/docs/gsquant/).
+
+## Contributions
+
+Contributions are encouraged! Please see CONTRIBUTING.MD for more details.
+
+## Help
+
+Please reach out to `gs-quant@gs.com` with any questions, comments or feedback.
+
+
+
+
+%package help
+Summary:	Development documents and examples for gs-quant
+Provides:	python3-gs-quant-doc
+%description help
+# GS Quant
+
+**GS Quant** is a Python toolkit for quantitative finance, created on top of one of the world’s most powerful risk transfer platforms. Designed to accelerate development of quantitative trading strategies and risk management solutions, crafted over 25 years of experience navigating global markets.
+
+It is created and maintained by quantitative developers (quants) at Goldman Sachs to enable the development of trading strategies and analysis of derivative products. GS Quant can be used to facilitate derivative structuring, trading, and risk management, or as a set of statistical packages for data analytics applications.
+
+Please refer to [Goldman Sachs Developer](https://developer.gs.com/docs/gsquant/) for additional information.
+
+## Requirements
+
+* Python 3.6 or greater
+* Access to PIP package manager
+
+## Installation
+
+```
+pip install gs-quant
+```
+
+## Examples
+
+You can find examples, guides and tutorials in the respective folders as well as on [Goldman Sachs Developer](https://developer.gs.com/docs/gsquant/).
+
+## Contributions
+
+Contributions are encouraged! Please see CONTRIBUTING.MD for more details.
+
+## Help
+
+Please reach out to `gs-quant@gs.com` with any questions, comments or feedback.
+
+
+
+
+%prep
+%autosetup -n gs-quant-0.9.100
+
+%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-gs-quant -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.9.100-1
+- Package Spec generated