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authorCoprDistGit <infra@openeuler.org>2023-04-12 00:13:36 +0000
committerCoprDistGit <infra@openeuler.org>2023-04-12 00:13:36 +0000
commit0c1e5320c61b4297724ec4a4df6ffee95b71d606 (patch)
treef46177a64476ae8822663b565a5e995bd903d6a2
parent65a6921cd6bc003a9e30306feb2eca17f2a1f715 (diff)
automatic import of python-greykite
-rw-r--r--.gitignore1
-rw-r--r--python-greykite.spec119
-rw-r--r--sources1
3 files changed, 121 insertions, 0 deletions
diff --git a/.gitignore b/.gitignore
index e69de29..e7c6294 100644
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/greykite-0.5.0.tar.gz
diff --git a/python-greykite.spec b/python-greykite.spec
new file mode 100644
index 0000000..aa3ed59
--- /dev/null
+++ b/python-greykite.spec
@@ -0,0 +1,119 @@
+%global _empty_manifest_terminate_build 0
+Name: python-greykite
+Version: 0.5.0
+Release: 1
+Summary: A python package for flexible forecasting
+License: BSD-2-CLAUSE
+URL: https://github.com/linkedin/greykite
+Source0: https://mirrors.nju.edu.cn/pypi/web/packages/4c/a9/2bcbcc31b4db440490d0be818fb0cc4b598a116bff1339f76b4eeed03264/greykite-0.5.0.tar.gz
+BuildArch: noarch
+
+Requires: python3-cvxpy
+Requires: python3-dill
+Requires: python3-holidays-ext
+Requires: python3-ipython
+Requires: python3-matplotlib
+Requires: python3-numpy
+Requires: python3-osqp
+Requires: python3-overrides
+Requires: python3-pandas
+Requires: python3-patsy
+Requires: python3-plotly
+Requires: python3-pmdarima
+Requires: python3-pytest
+Requires: python3-pytest-runner
+Requires: python3-scipy
+Requires: python3-six
+Requires: python3-scikit-learn
+Requires: python3-statsmodels
+Requires: python3-testfixtures
+Requires: python3-tqdm
+
+%description
+The Greykite library provides flexible, intuitive and fast forecasts through its flagship algorithm, Silverkite.
+Silverkite algorithm works well on most time series, and is especially adept for those with changepoints in trend or seasonality,
+event/holiday effects, and temporal dependencies.
+Its forecasts are interpretable and therefore useful for trusted decision-making and insights.
+The Greykite library provides a framework that makes it easy to develop a good forecast model,
+with exploratory data analysis, outlier/anomaly preprocessing, feature extraction and engineering, grid search,
+evaluation, benchmarking, and plotting.
+Other open source algorithms can be supported through Greykite’s interface to take advantage of this framework,
+as listed below.
+For a demo, please see our `quickstart <https://linkedin.github.io/greykite/get_started>`_.
+
+%package -n python3-greykite
+Summary: A python package for flexible forecasting
+Provides: python-greykite
+BuildRequires: python3-devel
+BuildRequires: python3-setuptools
+BuildRequires: python3-pip
+%description -n python3-greykite
+The Greykite library provides flexible, intuitive and fast forecasts through its flagship algorithm, Silverkite.
+Silverkite algorithm works well on most time series, and is especially adept for those with changepoints in trend or seasonality,
+event/holiday effects, and temporal dependencies.
+Its forecasts are interpretable and therefore useful for trusted decision-making and insights.
+The Greykite library provides a framework that makes it easy to develop a good forecast model,
+with exploratory data analysis, outlier/anomaly preprocessing, feature extraction and engineering, grid search,
+evaluation, benchmarking, and plotting.
+Other open source algorithms can be supported through Greykite’s interface to take advantage of this framework,
+as listed below.
+For a demo, please see our `quickstart <https://linkedin.github.io/greykite/get_started>`_.
+
+%package help
+Summary: Development documents and examples for greykite
+Provides: python3-greykite-doc
+%description help
+The Greykite library provides flexible, intuitive and fast forecasts through its flagship algorithm, Silverkite.
+Silverkite algorithm works well on most time series, and is especially adept for those with changepoints in trend or seasonality,
+event/holiday effects, and temporal dependencies.
+Its forecasts are interpretable and therefore useful for trusted decision-making and insights.
+The Greykite library provides a framework that makes it easy to develop a good forecast model,
+with exploratory data analysis, outlier/anomaly preprocessing, feature extraction and engineering, grid search,
+evaluation, benchmarking, and plotting.
+Other open source algorithms can be supported through Greykite’s interface to take advantage of this framework,
+as listed below.
+For a demo, please see our `quickstart <https://linkedin.github.io/greykite/get_started>`_.
+
+%prep
+%autosetup -n greykite-0.5.0
+
+%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-greykite -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed Apr 12 2023 Python_Bot <Python_Bot@openeuler.org> - 0.5.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..e0540ed
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+5704e3b3c8c2e825ae3dd49b931e0cd6 greykite-0.5.0.tar.gz