automatic import of python-midropeneuler20.03

3 files changed, 593 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..74c3ac2 100644
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/midr-1.5.1.tar.gz
diff --git a/python-midr.spec b/python-midr.spec
new file mode 100644
index 0000000..0f480a3
--- /dev/null
+++ b/python-midr.spec
@@ -0,0 +1,591 @@
+%global _empty_manifest_terminate_build 0
+Name:		python-midr
+Version:	1.5.1
+Release:	1
+Summary:	Compute idr from m NarrowPeak files and a merged NarrowPeak
+License:	CEA CNRS Inria Logiciel Libre License, version 2.1 (CeCILL-2.1)
+URL:		https://gitbio.ens-lyon.fr/LBMC/sbdm/midr
+Source0:	https://mirrors.aliyun.com/pypi/web/packages/0e/65/efcda47b6786746ebd703041c8a54c8898db20b6e16c0265b5592772a299/midr-1.5.1.tar.gz
+BuildArch:	noarch
+
+
+%description
+# IDR
+
+This tool is designed to compute the Irreproducible Discovery Rate (IDR)
+from NarrowPeaks files for two or more replicates.
+It’s an implementation of the method described in the following paper using
+Gaussian copula.
+
+> LI, Qunhua, BROWN, James B., HUANG, Haiyan, et al. Measuring reproducibility
+> of high-throughput experiments. The annals of applied statistics, 2011,
+> vol. 5, no 3, p. 1752-1779. doi:10.1214/11-AOAS466
+
+The default method for the IDR computation is the one developped in the 
+following paper using Archimedean copula.
+
+> Measuring Reproducibility of High-Throughput Deep-Sequencing Experiments 
+> Based on Self-adaptive Mixture Copula. Part of the Lecture Notes in Computer
+> Science book series (LNCS, volume 7818) PAKDD 2013: Advances in Knowledge 
+> Discovery and Data Mining p 301-313, isbn: 978-3-642-37453-1
+
+All the estimators for multivariate Archimedean copula are implemented from the 
+two following papers:
+
+> Likelihood inference for Archimedean copulas in high dimensions under known
+> margins, Journal of Multivariate Analysis, 2012, p133-150, 
+> doi:10.1016/j.jmva.2012.02.019
+
+> Archimedean Copulas in High Dimensions: Estimators and Numerical Challenges
+> Motivated by Financial Applications | Journal de la Société Française de
+> Statistique, Vol. 154 No. 1 (2013), ISSN: 2102-6238
+
+## Getting Started
+
+These instructions will get you a copy of the project up and running on your
+local machine for development and testing purposes.
+
+### Prerequisites
+
+To run **midr** on your computer you need to have python (>= 3) installed.
+
+```sh
+python3 --version
+```
+
+### Installing
+
+To easily install **midr** on your computer using `pip` run the following command:
+
+```
+pip3 install midr
+```
+
+Otherwise you can clone this repository:
+
+```
+git clone git@gitbio.ens-lyon.fr:/LBMC/sbdm/midr.git
+cd midr/src/
+python3 setup.py install
+```
+
+Given a list of peak calls in NarrowPeaks format and the corresponding peak
+call for the merged replicate. This tool computes and appends a IDR column to
+NarrowPeaks files.
+
+### Dependencies
+
+The **idr** package depends on the following python3 library:
+
+- [scipy>=1.3](https://scipy.org) [DOI:10.1109/MCSE.2007.58](https://doi.org/10.1109/MCSE.2007.58) [DOI:10.1109/MCSE.2011.36](https://doi.org/10.1109/MCSE.2011.36)
+
+> Travis E. Oliphant. Python for Scientific Computing, Computing in Science &
+> Engineering, 9, 10-20 (2007), DOI:10.1109/MCSE.2007.58
+
+> K. Jarrod Millman and Michael Aivazis. Python for Scientists and Engineers,
+> Computing in Science & Engineering, 13, 9-12 (2011),
+> DOI:10.1109/MCSE.2011.36
+
+
+- [numpy>=1.16](https://numpy.org/) [DOI:10.1109/MCSE.2011.37](https://doi.org/10.1109/MCSE.2010.118)
+
+> Travis E, Oliphant. A guide to NumPy, USA: Trelgol Publishing, (2006).
+
+> Stéfan van der Walt, S. Chris Colbert and Gaël Varoquaux. The NumPy Array:
+> A Structure for Efficient Numerical Computation, Computing in Science &
+> Engineering, 13, 22-30 (2011), DOI:10.1109/MCSE.2011.37
+
+- [matplotlib>=3.1](https://github.com/matplotlib/matplotlib/tree/v3.1.1) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3264781.svg)](https://doi.org/10.5281/zenodo.3264781)
+
+>  J. D. Hunter, "Matplotlib: A 2D Graphics Environment",
+> Computing in Science & Engineering, vol. 9, no. 3, pp. 90-95, 2007.
+
+- [pandas>=0.25.0](https://pandas.pydata.org)
+> McKinney. Data Structures for Statistical Computing in Python, Proceedings
+> of the 9th Python in Science Conference, 51-56 (2010) [(publisher link)](http://conference.scipy.org/proceedings/scipy2010/mckinney.html)
+
+- [pynverse>=0.1](https://pypi.org/project/pynverse/)
+
+- [mpmath>=1.1.0](http://mpmath.org/)
+- [cython>=0.28.0](https://cython.org/)
+
+## Usage
+
+**idr** Takes as input file in the [NarrowPeaks format](https://genome.ucsc.edu/FAQ/FAQformat.html#format12),
+and output NarrowPeaks files with an additional *idr* column.
+
+Computing *IDR* between three replicates
+
+```
+$ midr -m merged_peak_calling.NarrowPeaks \
+     -f replicate1_.NarrowPeaks replicate2.NarrowPeaks replicate3.NarrowPeaks \
+     -o results
+```
+
+Where `replicate1_.NarrowPeaks` is the output of the peak caller on the 
+alignment file corresponding to the first replicate and 
+`merged_peak_calling.NarrowPeaks` is the output of the peak caller on the merge
+of the replicates alignment files.
+`Results` are the directory where we want to output our results.
+
+Displaying help:
+
+```
+$ midr -h
+usage: midr [-h] [--merged FILE] [--files FILES [FILES ...]] [--output DIR] [--score SCORE_COLUMN] [--threshold THRESHOLD] [--merge_function MERGE_FUNCTION] [--size SIZE_MERGE] [--nodrop] [--method METHOD]
+            [--cpu CPU] [--debug] [--verbose] [--matrix FILE]
+
+Compute the Irreproducible Discovery Rate (IDR) from NarrowPeaks files
+
+Implementation of the IDR methods for two or more replicates.
+
+LI, Qunhua, BROWN, James B., HUANG, Haiyan, et al. Measuring reproducibility
+of high-throughput experiments. The annals of applied statistics, 2011,
+vol. 5, no 3, p. 1752-1779.
+
+Given a list of peak calls in NarrowPeaks format and the corresponding peak
+call for the merged replicate. This tool computes and appends a IDR column to
+NarrowPeaks files.
+
+optional arguments:
+  -h, --help            show this help message and exit
+
+IDR settings:
+  --merged FILE, -m FILE
+                        file of the merged NarrowPeaks
+  --files FILES [FILES ...], -f FILES [FILES ...]
+                        list of NarrowPeaks files
+  --output DIR, -o DIR  output directory (default: results)
+  --score SCORE_COLUMN, -s SCORE_COLUMN
+                        NarrowPeaks score column to compute the IDR on, one of 'score', 'signalValue', 'pValue' or 'qValue' (default: signalValue)
+  --threshold THRESHOLD, -t THRESHOLD
+                        Threshold value for the precision of the estimators (default: 0.0001)
+  --merge_function MERGE_FUNCTION, -mf MERGE_FUNCTION
+                        function to determine the score to keep for overlapping peak within a replica ('sum', 'max', 'mean', 'median', 'min') (default: max)
+  --size SIZE_MERGE, -ws SIZE_MERGE
+                        distance (bp) to add before and after each peak before merging finding match between --merged file and --files files (default: 100)
+  --nodrop, -nd         don't drop peak unmatched in any bed. The score of the absent peak is set to 0.0 (default: True)
+  --method METHOD, -mt METHOD
+                        copula model to use('archimedean' or 'gaussian' (default: archimedean)
+  --cpu CPU, -cpu CPU   number of thread to use for merging the beds files (default: 1)
+  --debug, -d           enable debugging (default: False)
+  --verbose, -v         log to console (default: False)
+  --matrix FILE         matrix file of the peaks score in raw (tsv format), replace the --merge and --files options if used
+```
+
+
+## Authors
+
+* **Laurent Modolo** - *Initial work*
+
+## License
+
+This project is licensed under the CeCiLL License- see the [LICENSE](LICENSE) file for details.
+
+
+
+
+%package -n python3-midr
+Summary:	Compute idr from m NarrowPeak files and a merged NarrowPeak
+Provides:	python-midr
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-midr
+# IDR
+
+This tool is designed to compute the Irreproducible Discovery Rate (IDR)
+from NarrowPeaks files for two or more replicates.
+It’s an implementation of the method described in the following paper using
+Gaussian copula.
+
+> LI, Qunhua, BROWN, James B., HUANG, Haiyan, et al. Measuring reproducibility
+> of high-throughput experiments. The annals of applied statistics, 2011,
+> vol. 5, no 3, p. 1752-1779. doi:10.1214/11-AOAS466
+
+The default method for the IDR computation is the one developped in the 
+following paper using Archimedean copula.
+
+> Measuring Reproducibility of High-Throughput Deep-Sequencing Experiments 
+> Based on Self-adaptive Mixture Copula. Part of the Lecture Notes in Computer
+> Science book series (LNCS, volume 7818) PAKDD 2013: Advances in Knowledge 
+> Discovery and Data Mining p 301-313, isbn: 978-3-642-37453-1
+
+All the estimators for multivariate Archimedean copula are implemented from the 
+two following papers:
+
+> Likelihood inference for Archimedean copulas in high dimensions under known
+> margins, Journal of Multivariate Analysis, 2012, p133-150, 
+> doi:10.1016/j.jmva.2012.02.019
+
+> Archimedean Copulas in High Dimensions: Estimators and Numerical Challenges
+> Motivated by Financial Applications | Journal de la Société Française de
+> Statistique, Vol. 154 No. 1 (2013), ISSN: 2102-6238
+
+## Getting Started
+
+These instructions will get you a copy of the project up and running on your
+local machine for development and testing purposes.
+
+### Prerequisites
+
+To run **midr** on your computer you need to have python (>= 3) installed.
+
+```sh
+python3 --version
+```
+
+### Installing
+
+To easily install **midr** on your computer using `pip` run the following command:
+
+```
+pip3 install midr
+```
+
+Otherwise you can clone this repository:
+
+```
+git clone git@gitbio.ens-lyon.fr:/LBMC/sbdm/midr.git
+cd midr/src/
+python3 setup.py install
+```
+
+Given a list of peak calls in NarrowPeaks format and the corresponding peak
+call for the merged replicate. This tool computes and appends a IDR column to
+NarrowPeaks files.
+
+### Dependencies
+
+The **idr** package depends on the following python3 library:
+
+- [scipy>=1.3](https://scipy.org) [DOI:10.1109/MCSE.2007.58](https://doi.org/10.1109/MCSE.2007.58) [DOI:10.1109/MCSE.2011.36](https://doi.org/10.1109/MCSE.2011.36)
+
+> Travis E. Oliphant. Python for Scientific Computing, Computing in Science &
+> Engineering, 9, 10-20 (2007), DOI:10.1109/MCSE.2007.58
+
+> K. Jarrod Millman and Michael Aivazis. Python for Scientists and Engineers,
+> Computing in Science & Engineering, 13, 9-12 (2011),
+> DOI:10.1109/MCSE.2011.36
+
+
+- [numpy>=1.16](https://numpy.org/) [DOI:10.1109/MCSE.2011.37](https://doi.org/10.1109/MCSE.2010.118)
+
+> Travis E, Oliphant. A guide to NumPy, USA: Trelgol Publishing, (2006).
+
+> Stéfan van der Walt, S. Chris Colbert and Gaël Varoquaux. The NumPy Array:
+> A Structure for Efficient Numerical Computation, Computing in Science &
+> Engineering, 13, 22-30 (2011), DOI:10.1109/MCSE.2011.37
+
+- [matplotlib>=3.1](https://github.com/matplotlib/matplotlib/tree/v3.1.1) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3264781.svg)](https://doi.org/10.5281/zenodo.3264781)
+
+>  J. D. Hunter, "Matplotlib: A 2D Graphics Environment",
+> Computing in Science & Engineering, vol. 9, no. 3, pp. 90-95, 2007.
+
+- [pandas>=0.25.0](https://pandas.pydata.org)
+> McKinney. Data Structures for Statistical Computing in Python, Proceedings
+> of the 9th Python in Science Conference, 51-56 (2010) [(publisher link)](http://conference.scipy.org/proceedings/scipy2010/mckinney.html)
+
+- [pynverse>=0.1](https://pypi.org/project/pynverse/)
+
+- [mpmath>=1.1.0](http://mpmath.org/)
+- [cython>=0.28.0](https://cython.org/)
+
+## Usage
+
+**idr** Takes as input file in the [NarrowPeaks format](https://genome.ucsc.edu/FAQ/FAQformat.html#format12),
+and output NarrowPeaks files with an additional *idr* column.
+
+Computing *IDR* between three replicates
+
+```
+$ midr -m merged_peak_calling.NarrowPeaks \
+     -f replicate1_.NarrowPeaks replicate2.NarrowPeaks replicate3.NarrowPeaks \
+     -o results
+```
+
+Where `replicate1_.NarrowPeaks` is the output of the peak caller on the 
+alignment file corresponding to the first replicate and 
+`merged_peak_calling.NarrowPeaks` is the output of the peak caller on the merge
+of the replicates alignment files.
+`Results` are the directory where we want to output our results.
+
+Displaying help:
+
+```
+$ midr -h
+usage: midr [-h] [--merged FILE] [--files FILES [FILES ...]] [--output DIR] [--score SCORE_COLUMN] [--threshold THRESHOLD] [--merge_function MERGE_FUNCTION] [--size SIZE_MERGE] [--nodrop] [--method METHOD]
+            [--cpu CPU] [--debug] [--verbose] [--matrix FILE]
+
+Compute the Irreproducible Discovery Rate (IDR) from NarrowPeaks files
+
+Implementation of the IDR methods for two or more replicates.
+
+LI, Qunhua, BROWN, James B., HUANG, Haiyan, et al. Measuring reproducibility
+of high-throughput experiments. The annals of applied statistics, 2011,
+vol. 5, no 3, p. 1752-1779.
+
+Given a list of peak calls in NarrowPeaks format and the corresponding peak
+call for the merged replicate. This tool computes and appends a IDR column to
+NarrowPeaks files.
+
+optional arguments:
+  -h, --help            show this help message and exit
+
+IDR settings:
+  --merged FILE, -m FILE
+                        file of the merged NarrowPeaks
+  --files FILES [FILES ...], -f FILES [FILES ...]
+                        list of NarrowPeaks files
+  --output DIR, -o DIR  output directory (default: results)
+  --score SCORE_COLUMN, -s SCORE_COLUMN
+                        NarrowPeaks score column to compute the IDR on, one of 'score', 'signalValue', 'pValue' or 'qValue' (default: signalValue)
+  --threshold THRESHOLD, -t THRESHOLD
+                        Threshold value for the precision of the estimators (default: 0.0001)
+  --merge_function MERGE_FUNCTION, -mf MERGE_FUNCTION
+                        function to determine the score to keep for overlapping peak within a replica ('sum', 'max', 'mean', 'median', 'min') (default: max)
+  --size SIZE_MERGE, -ws SIZE_MERGE
+                        distance (bp) to add before and after each peak before merging finding match between --merged file and --files files (default: 100)
+  --nodrop, -nd         don't drop peak unmatched in any bed. The score of the absent peak is set to 0.0 (default: True)
+  --method METHOD, -mt METHOD
+                        copula model to use('archimedean' or 'gaussian' (default: archimedean)
+  --cpu CPU, -cpu CPU   number of thread to use for merging the beds files (default: 1)
+  --debug, -d           enable debugging (default: False)
+  --verbose, -v         log to console (default: False)
+  --matrix FILE         matrix file of the peaks score in raw (tsv format), replace the --merge and --files options if used
+```
+
+
+## Authors
+
+* **Laurent Modolo** - *Initial work*
+
+## License
+
+This project is licensed under the CeCiLL License- see the [LICENSE](LICENSE) file for details.
+
+
+
+
+%package help
+Summary:	Development documents and examples for midr
+Provides:	python3-midr-doc
+%description help
+# IDR
+
+This tool is designed to compute the Irreproducible Discovery Rate (IDR)
+from NarrowPeaks files for two or more replicates.
+It’s an implementation of the method described in the following paper using
+Gaussian copula.
+
+> LI, Qunhua, BROWN, James B., HUANG, Haiyan, et al. Measuring reproducibility
+> of high-throughput experiments. The annals of applied statistics, 2011,
+> vol. 5, no 3, p. 1752-1779. doi:10.1214/11-AOAS466
+
+The default method for the IDR computation is the one developped in the 
+following paper using Archimedean copula.
+
+> Measuring Reproducibility of High-Throughput Deep-Sequencing Experiments 
+> Based on Self-adaptive Mixture Copula. Part of the Lecture Notes in Computer
+> Science book series (LNCS, volume 7818) PAKDD 2013: Advances in Knowledge 
+> Discovery and Data Mining p 301-313, isbn: 978-3-642-37453-1
+
+All the estimators for multivariate Archimedean copula are implemented from the 
+two following papers:
+
+> Likelihood inference for Archimedean copulas in high dimensions under known
+> margins, Journal of Multivariate Analysis, 2012, p133-150, 
+> doi:10.1016/j.jmva.2012.02.019
+
+> Archimedean Copulas in High Dimensions: Estimators and Numerical Challenges
+> Motivated by Financial Applications | Journal de la Société Française de
+> Statistique, Vol. 154 No. 1 (2013), ISSN: 2102-6238
+
+## Getting Started
+
+These instructions will get you a copy of the project up and running on your
+local machine for development and testing purposes.
+
+### Prerequisites
+
+To run **midr** on your computer you need to have python (>= 3) installed.
+
+```sh
+python3 --version
+```
+
+### Installing
+
+To easily install **midr** on your computer using `pip` run the following command:
+
+```
+pip3 install midr
+```
+
+Otherwise you can clone this repository:
+
+```
+git clone git@gitbio.ens-lyon.fr:/LBMC/sbdm/midr.git
+cd midr/src/
+python3 setup.py install
+```
+
+Given a list of peak calls in NarrowPeaks format and the corresponding peak
+call for the merged replicate. This tool computes and appends a IDR column to
+NarrowPeaks files.
+
+### Dependencies
+
+The **idr** package depends on the following python3 library:
+
+- [scipy>=1.3](https://scipy.org) [DOI:10.1109/MCSE.2007.58](https://doi.org/10.1109/MCSE.2007.58) [DOI:10.1109/MCSE.2011.36](https://doi.org/10.1109/MCSE.2011.36)
+
+> Travis E. Oliphant. Python for Scientific Computing, Computing in Science &
+> Engineering, 9, 10-20 (2007), DOI:10.1109/MCSE.2007.58
+
+> K. Jarrod Millman and Michael Aivazis. Python for Scientists and Engineers,
+> Computing in Science & Engineering, 13, 9-12 (2011),
+> DOI:10.1109/MCSE.2011.36
+
+
+- [numpy>=1.16](https://numpy.org/) [DOI:10.1109/MCSE.2011.37](https://doi.org/10.1109/MCSE.2010.118)
+
+> Travis E, Oliphant. A guide to NumPy, USA: Trelgol Publishing, (2006).
+
+> Stéfan van der Walt, S. Chris Colbert and Gaël Varoquaux. The NumPy Array:
+> A Structure for Efficient Numerical Computation, Computing in Science &
+> Engineering, 13, 22-30 (2011), DOI:10.1109/MCSE.2011.37
+
+- [matplotlib>=3.1](https://github.com/matplotlib/matplotlib/tree/v3.1.1) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3264781.svg)](https://doi.org/10.5281/zenodo.3264781)
+
+>  J. D. Hunter, "Matplotlib: A 2D Graphics Environment",
+> Computing in Science & Engineering, vol. 9, no. 3, pp. 90-95, 2007.
+
+- [pandas>=0.25.0](https://pandas.pydata.org)
+> McKinney. Data Structures for Statistical Computing in Python, Proceedings
+> of the 9th Python in Science Conference, 51-56 (2010) [(publisher link)](http://conference.scipy.org/proceedings/scipy2010/mckinney.html)
+
+- [pynverse>=0.1](https://pypi.org/project/pynverse/)
+
+- [mpmath>=1.1.0](http://mpmath.org/)
+- [cython>=0.28.0](https://cython.org/)
+
+## Usage
+
+**idr** Takes as input file in the [NarrowPeaks format](https://genome.ucsc.edu/FAQ/FAQformat.html#format12),
+and output NarrowPeaks files with an additional *idr* column.
+
+Computing *IDR* between three replicates
+
+```
+$ midr -m merged_peak_calling.NarrowPeaks \
+     -f replicate1_.NarrowPeaks replicate2.NarrowPeaks replicate3.NarrowPeaks \
+     -o results
+```
+
+Where `replicate1_.NarrowPeaks` is the output of the peak caller on the 
+alignment file corresponding to the first replicate and 
+`merged_peak_calling.NarrowPeaks` is the output of the peak caller on the merge
+of the replicates alignment files.
+`Results` are the directory where we want to output our results.
+
+Displaying help:
+
+```
+$ midr -h
+usage: midr [-h] [--merged FILE] [--files FILES [FILES ...]] [--output DIR] [--score SCORE_COLUMN] [--threshold THRESHOLD] [--merge_function MERGE_FUNCTION] [--size SIZE_MERGE] [--nodrop] [--method METHOD]
+            [--cpu CPU] [--debug] [--verbose] [--matrix FILE]
+
+Compute the Irreproducible Discovery Rate (IDR) from NarrowPeaks files
+
+Implementation of the IDR methods for two or more replicates.
+
+LI, Qunhua, BROWN, James B., HUANG, Haiyan, et al. Measuring reproducibility
+of high-throughput experiments. The annals of applied statistics, 2011,
+vol. 5, no 3, p. 1752-1779.
+
+Given a list of peak calls in NarrowPeaks format and the corresponding peak
+call for the merged replicate. This tool computes and appends a IDR column to
+NarrowPeaks files.
+
+optional arguments:
+  -h, --help            show this help message and exit
+
+IDR settings:
+  --merged FILE, -m FILE
+                        file of the merged NarrowPeaks
+  --files FILES [FILES ...], -f FILES [FILES ...]
+                        list of NarrowPeaks files
+  --output DIR, -o DIR  output directory (default: results)
+  --score SCORE_COLUMN, -s SCORE_COLUMN
+                        NarrowPeaks score column to compute the IDR on, one of 'score', 'signalValue', 'pValue' or 'qValue' (default: signalValue)
+  --threshold THRESHOLD, -t THRESHOLD
+                        Threshold value for the precision of the estimators (default: 0.0001)
+  --merge_function MERGE_FUNCTION, -mf MERGE_FUNCTION
+                        function to determine the score to keep for overlapping peak within a replica ('sum', 'max', 'mean', 'median', 'min') (default: max)
+  --size SIZE_MERGE, -ws SIZE_MERGE
+                        distance (bp) to add before and after each peak before merging finding match between --merged file and --files files (default: 100)
+  --nodrop, -nd         don't drop peak unmatched in any bed. The score of the absent peak is set to 0.0 (default: True)
+  --method METHOD, -mt METHOD
+                        copula model to use('archimedean' or 'gaussian' (default: archimedean)
+  --cpu CPU, -cpu CPU   number of thread to use for merging the beds files (default: 1)
+  --debug, -d           enable debugging (default: False)
+  --verbose, -v         log to console (default: False)
+  --matrix FILE         matrix file of the peaks score in raw (tsv format), replace the --merge and --files options if used
+```
+
+
+## Authors
+
+* **Laurent Modolo** - *Initial work*
+
+## License
+
+This project is licensed under the CeCiLL License- see the [LICENSE](LICENSE) file for details.
+
+
+
+
+%prep
+%autosetup -n midr-1.5.1
+
+%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-midr -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 1.5.1-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..3661c7a
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+e5f2e98b9db7c72b3ede3f3f73898ea2  midr-1.5.1.tar.gz