automatic import of python-tweezepyopeneuler20.03

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diff --git a/.gitignore b/.gitignore
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+/Tweezepy-1.2.6.tar.gz
diff --git a/python-tweezepy.spec b/python-tweezepy.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-Tweezepy
+Version:	1.2.6
+Release:	1
+Summary:	Single-molecule force spectroscopy calibration
+License:	GPLv3
+URL:		https://github.com/ianlmorgan/tweezepy
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/12/4f/31868b52ce4376f16b53710cfda2a6bac82ac68c616279d68b99546a08e1/Tweezepy-1.2.6.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-autograd
+Requires:	python3-corner
+Requires:	python3-emcee
+Requires:	python3-matplotlib
+Requires:	python3-numba
+Requires:	python3-numpy
+Requires:	python3-scipy
+
+%description
+# Tweezepy
+[![DOI](https://zenodo.org/badge/261266475.svg)](https://zenodo.org/badge/latestdoi/261266475)
+
+
+This is [Tweezepy](https://github.com/ianlmorgan/tweezepy), a Python package for calibrating forces in single-molecule force spectroscopy video-tracking experiments using the power spectral density (PSD) and Allan variance (AV).
+
+## Documentation
+Read the documentation for [Tweezepy](https://tweezepy.readthedocs.io/).
+
+## How to install
+The simplest method of installing the `Tweezepy` package is via the [Python Package Index](https://packaging.python.org/glossary/#term-python-package-index-pypi) (PyPI). To install from PyPI, you will need to be able to run python from the command line and make sure you have [pip](https://packaging.python.org/key_projects/#pip) available.
+
+Install from PyPI:
+
+    pip install tweezepy
+An alternative method to install `Tweezepy` is with setuptools.  Clone the repository onto a local machine, then navigate to the directory.
+
+Using setuptools:
+    
+    cd path/to/tweezepy
+
+    python setup.py install
+    
+## Contents
+The `Tweezepy` package includes the following modules:
+* 'smmcalibration' - classes for calibration methods using the PSD and AV
+* 'expressions' - functions with closed-form expressions for thermal motion in the PSD and AV
+* 'MLE' - classes for maximum likelihood estimation (MLE) and Monte Carlo Markov chain (MCMC) sampling
+* 'allanvar' - tools for calculating the AV and equivalent degrees of freedom
+* 'simulations' - tools to simulate bead thermal motion
+
+
+
+%package -n python3-Tweezepy
+Summary:	Single-molecule force spectroscopy calibration
+Provides:	python-Tweezepy
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-Tweezepy
+# Tweezepy
+[![DOI](https://zenodo.org/badge/261266475.svg)](https://zenodo.org/badge/latestdoi/261266475)
+
+
+This is [Tweezepy](https://github.com/ianlmorgan/tweezepy), a Python package for calibrating forces in single-molecule force spectroscopy video-tracking experiments using the power spectral density (PSD) and Allan variance (AV).
+
+## Documentation
+Read the documentation for [Tweezepy](https://tweezepy.readthedocs.io/).
+
+## How to install
+The simplest method of installing the `Tweezepy` package is via the [Python Package Index](https://packaging.python.org/glossary/#term-python-package-index-pypi) (PyPI). To install from PyPI, you will need to be able to run python from the command line and make sure you have [pip](https://packaging.python.org/key_projects/#pip) available.
+
+Install from PyPI:
+
+    pip install tweezepy
+An alternative method to install `Tweezepy` is with setuptools.  Clone the repository onto a local machine, then navigate to the directory.
+
+Using setuptools:
+    
+    cd path/to/tweezepy
+
+    python setup.py install
+    
+## Contents
+The `Tweezepy` package includes the following modules:
+* 'smmcalibration' - classes for calibration methods using the PSD and AV
+* 'expressions' - functions with closed-form expressions for thermal motion in the PSD and AV
+* 'MLE' - classes for maximum likelihood estimation (MLE) and Monte Carlo Markov chain (MCMC) sampling
+* 'allanvar' - tools for calculating the AV and equivalent degrees of freedom
+* 'simulations' - tools to simulate bead thermal motion
+
+
+
+%package help
+Summary:	Development documents and examples for Tweezepy
+Provides:	python3-Tweezepy-doc
+%description help
+# Tweezepy
+[![DOI](https://zenodo.org/badge/261266475.svg)](https://zenodo.org/badge/latestdoi/261266475)
+
+
+This is [Tweezepy](https://github.com/ianlmorgan/tweezepy), a Python package for calibrating forces in single-molecule force spectroscopy video-tracking experiments using the power spectral density (PSD) and Allan variance (AV).
+
+## Documentation
+Read the documentation for [Tweezepy](https://tweezepy.readthedocs.io/).
+
+## How to install
+The simplest method of installing the `Tweezepy` package is via the [Python Package Index](https://packaging.python.org/glossary/#term-python-package-index-pypi) (PyPI). To install from PyPI, you will need to be able to run python from the command line and make sure you have [pip](https://packaging.python.org/key_projects/#pip) available.
+
+Install from PyPI:
+
+    pip install tweezepy
+An alternative method to install `Tweezepy` is with setuptools.  Clone the repository onto a local machine, then navigate to the directory.
+
+Using setuptools:
+    
+    cd path/to/tweezepy
+
+    python setup.py install
+    
+## Contents
+The `Tweezepy` package includes the following modules:
+* 'smmcalibration' - classes for calibration methods using the PSD and AV
+* 'expressions' - functions with closed-form expressions for thermal motion in the PSD and AV
+* 'MLE' - classes for maximum likelihood estimation (MLE) and Monte Carlo Markov chain (MCMC) sampling
+* 'allanvar' - tools for calculating the AV and equivalent degrees of freedom
+* 'simulations' - tools to simulate bead thermal motion
+
+
+
+%prep
+%autosetup -n Tweezepy-1.2.6
+
+%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-Tweezepy -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.2.6-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..21d7182
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+9f068f89c4c04a22e3cba70419270eec  Tweezepy-1.2.6.tar.gz