From 93ebbae188fcb472de6d4c7c15e88e175b793404 Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Tue, 11 Apr 2023 13:24:46 +0000 Subject: automatic import of python-csaps --- python-csaps.spec | 763 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 763 insertions(+) create mode 100644 python-csaps.spec (limited to 'python-csaps.spec') diff --git a/python-csaps.spec b/python-csaps.spec new file mode 100644 index 0000000..867dfa4 --- /dev/null +++ b/python-csaps.spec @@ -0,0 +1,763 @@ +%global _empty_manifest_terminate_build 0 +Name: python-csaps +Version: 1.1.0 +Release: 1 +Summary: Cubic spline approximation (smoothing) +License: MIT +URL: https://github.com/espdev/csaps +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/f3/de/ef40ae9b0485b36c0128d0d0065e065d7dc8fa3c2334a886548dc70e8ad7/csaps-1.1.0.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-scipy +Requires: python3-sphinx +Requires: python3-matplotlib +Requires: python3-numpydoc +Requires: python3-m2r2 +Requires: python3-pytest +Requires: python3-coverage +Requires: python3-pytest-cov +Requires: python3-coveralls + +%description +

+ csaps
+

+ +

+ PyPI version + Supported Python versions + GitHub Actions (Tests) + Documentation Status + Coverage Status + License +

+ +**csaps** is a Python package for univariate, multivariate and n-dimensional grid data approximation using cubic smoothing splines. +The package can be useful in practical engineering tasks for data approximation and smoothing. + +## Installing + +Use pip for installing: + +``` +pip install -U csaps +``` + +The module depends only on NumPy and SciPy. Python 3.6 or above is supported. + +## Simple Examples + +Here is a couple of examples of smoothing data. + +An univariate data smoothing: + +```python +import numpy as np +import matplotlib.pyplot as plt + +from csaps import csaps + +np.random.seed(1234) + +x = np.linspace(-5., 5., 25) +y = np.exp(-(x/2.5)**2) + (np.random.rand(25) - 0.2) * 0.3 +xs = np.linspace(x[0], x[-1], 150) + +ys = csaps(x, y, xs, smooth=0.85) + +plt.plot(x, y, 'o', xs, ys, '-') +plt.show() +``` + +

+ univariate +

+ +A surface data smoothing: + +```python +import numpy as np +import matplotlib.pyplot as plt +from mpl_toolkits.mplot3d import Axes3D + +from csaps import csaps + +np.random.seed(1234) +xdata = [np.linspace(-3, 3, 41), np.linspace(-3.5, 3.5, 31)] +i, j = np.meshgrid(*xdata, indexing='ij') +ydata = (3 * (1 - j)**2. * np.exp(-(j**2) - (i + 1)**2) + - 10 * (j / 5 - j**3 - i**5) * np.exp(-j**2 - i**2) + - 1 / 3 * np.exp(-(j + 1)**2 - i**2)) +ydata = ydata + (np.random.randn(*ydata.shape) * 0.75) + +ydata_s = csaps(xdata, ydata, xdata, smooth=0.988) + +fig = plt.figure(figsize=(7, 4.5)) +ax = fig.add_subplot(111, projection='3d') +ax.set_facecolor('none') +c = [s['color'] for s in plt.rcParams['axes.prop_cycle']] +ax.plot_wireframe(j, i, ydata, linewidths=0.5, color=c[0], alpha=0.5) +ax.scatter(j, i, ydata, s=10, c=c[0], alpha=0.5) +ax.plot_surface(j, i, ydata_s, color=c[1], linewidth=0, alpha=1.0) +ax.view_init(elev=9., azim=290) + +plt.show() +``` + +

+ surface +

+ +## Documentation + +More examples of usage and the full documentation can be found at https://csaps.readthedocs.io. + +## Testing + +We use pytest for testing. + +``` +cd /path/to/csaps/project/directory +pip install -e .[tests] +pytest +``` + +## Algorithm and Implementation + +**csaps** Python package is inspired by MATLAB [CSAPS](https://www.mathworks.com/help/curvefit/csaps.html) function that is an implementation of +Fortran routine SMOOTH from [PGS](http://pages.cs.wisc.edu/~deboor/pgs/) (originally written by Carl de Boor). + +Also the algothithm implementation in other languages: + +* [csaps-rs](https://github.com/espdev/csaps-rs) Rust ndarray/sprs based implementation +* [csaps-cpp](https://github.com/espdev/csaps-cpp) C++11 Eigen based implementation (incomplete) + + +## References + +C. de Boor, A Practical Guide to Splines, Springer-Verlag, 1978. + +## License + +[MIT](https://choosealicense.com/licenses/mit/) + +# Changelog + +## v1.1.0 + +* Introduced optional `normalizedsmooth` argument to reduce dependence on xdata and weights [#47](https://github.com/espdev/csaps/pull/47) +* Update numpy and scipy dependency ranges + +## v1.0.4 (04.05.2021) + +* Bump numpy dependency version + +## v1.0.3 (01.01.2021) + +* Bump scipy dependency version +* Bump sphinx dependency version and use m2r2 sphinx extension instead of m2r +* Add Python 3.9 to classifiers list and to Travis CI +* Set development status classifier to "5 - Production/Stable" +* Happy New Year! + +## v1.0.2 (19.07.2020) + +* Fix using 'nu' argument when n-d grid spline evaluating [#32](https://github.com/espdev/csaps/pull/32) + +## v1.0.1 (19.07.2020) + +* Fix n-d grid spline evaluating performance regression [#31](https://github.com/espdev/csaps/pull/31) + +## v1.0.0 (11.07.2020) + +* Use `PPoly` and `NdPPoly` base classes from SciPy interpolate module for `SplinePPForm` and `NdGridSplinePPForm` respectively. +* Remove deprecated classes `UnivariateCubicSmoothingSpline` and `MultivariateCubicSmoothingSpline` +* Update the documentation + +**Notes** + +In this release the spline representation (the array of spline coefficients) has been changed +according to `PPoly`/`NdPPoly`. +See SciPy [PPoly](https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.PPoly.html) +and [NdPPoly](https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.NdPPoly.html) documentation for details. + + +## v0.11.0 (28.03.2020) + +* Internal re-design `SplinePPForm` and `NdGridSplinePPForm` classes [#17](https://github.com/espdev/csaps/issues/17): + - Remove `shape` and `axis` properties and reshaping data in these classes + - `NdGridSplinePPForm` coefficients array for 1D grid now is 1-d instead of 2-d +* Refactoring the code and decrease memory consumption +* Add `overload` type-hints for `csaps` function signatures + +## v0.10.1 (19.03.2020) + +* Fix call of `numpy.pad` function for numpy <1.17 [#15](https://github.com/espdev/csaps/issues/15) + +## v0.10.0 (18.02.2020) + +* Significant performance improvements for make/evaluate splines and memory consumption optimization +* Change format for storing spline coefficients (reshape coeffs array) to improve performance +* Add shape property to `SplinePPForm`/`NdGridSplinePPForm` and axis property to `SplinePPForm` +* Fix issues with the smoothing factor in nd-grid case: inverted ordering and unnable to use 0.0 value +* Update documentation + +## v0.9.0 (21.01.2020) + +* Drop support of Python 3.5 +* `weights`, `smooth` and `axis` arguments in `csaps` function are keyword-only now +* `UnivariateCubicSmoothingSpline` and `MultivariateCubicSmoothingSpline` classes are deprecated + and will be removed in 1.0.0 version. Use `CubicSmoothingSpline` instead. + +## v0.8.0 (13.01.2020) + +* Add `csaps` function that can be used as the main API +* Refactor the internal structure of the package +* Add the [documentation](https://csaps.readthedocs.io) + +**Attention** + +This is the last version that supports Python 3.5. +The next versions will support Python 3.6 or above. + +## v0.7.0 (19.09.2019) + +* Add Generic-based type-hints and mypy-compatibility + +## v0.6.1 (13.09.2019) + +* A slight refactoring and extra data copies removing + +## v0.6.0 (12.09.2019) + +* Add "axis" parameter for univariate/multivariate cases + +## v0.5.0 (10.06.2019) + +* Reorganize the project to package-based structure +* Add the interface class for all smoothing spline classes + +## v0.4.2 (07.09.2019) + +* FIX: "smooth" value is 0.0 was not used + +## v0.4.1 (30.05.2019) + +* First PyPI release + + + + +%package -n python3-csaps +Summary: Cubic spline approximation (smoothing) +Provides: python-csaps +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-csaps +

+ csaps
+

+ +

+ PyPI version + Supported Python versions + GitHub Actions (Tests) + Documentation Status + Coverage Status + License +

+ +**csaps** is a Python package for univariate, multivariate and n-dimensional grid data approximation using cubic smoothing splines. +The package can be useful in practical engineering tasks for data approximation and smoothing. + +## Installing + +Use pip for installing: + +``` +pip install -U csaps +``` + +The module depends only on NumPy and SciPy. Python 3.6 or above is supported. + +## Simple Examples + +Here is a couple of examples of smoothing data. + +An univariate data smoothing: + +```python +import numpy as np +import matplotlib.pyplot as plt + +from csaps import csaps + +np.random.seed(1234) + +x = np.linspace(-5., 5., 25) +y = np.exp(-(x/2.5)**2) + (np.random.rand(25) - 0.2) * 0.3 +xs = np.linspace(x[0], x[-1], 150) + +ys = csaps(x, y, xs, smooth=0.85) + +plt.plot(x, y, 'o', xs, ys, '-') +plt.show() +``` + +

+ univariate +

+ +A surface data smoothing: + +```python +import numpy as np +import matplotlib.pyplot as plt +from mpl_toolkits.mplot3d import Axes3D + +from csaps import csaps + +np.random.seed(1234) +xdata = [np.linspace(-3, 3, 41), np.linspace(-3.5, 3.5, 31)] +i, j = np.meshgrid(*xdata, indexing='ij') +ydata = (3 * (1 - j)**2. * np.exp(-(j**2) - (i + 1)**2) + - 10 * (j / 5 - j**3 - i**5) * np.exp(-j**2 - i**2) + - 1 / 3 * np.exp(-(j + 1)**2 - i**2)) +ydata = ydata + (np.random.randn(*ydata.shape) * 0.75) + +ydata_s = csaps(xdata, ydata, xdata, smooth=0.988) + +fig = plt.figure(figsize=(7, 4.5)) +ax = fig.add_subplot(111, projection='3d') +ax.set_facecolor('none') +c = [s['color'] for s in plt.rcParams['axes.prop_cycle']] +ax.plot_wireframe(j, i, ydata, linewidths=0.5, color=c[0], alpha=0.5) +ax.scatter(j, i, ydata, s=10, c=c[0], alpha=0.5) +ax.plot_surface(j, i, ydata_s, color=c[1], linewidth=0, alpha=1.0) +ax.view_init(elev=9., azim=290) + +plt.show() +``` + +

+ surface +

+ +## Documentation + +More examples of usage and the full documentation can be found at https://csaps.readthedocs.io. + +## Testing + +We use pytest for testing. + +``` +cd /path/to/csaps/project/directory +pip install -e .[tests] +pytest +``` + +## Algorithm and Implementation + +**csaps** Python package is inspired by MATLAB [CSAPS](https://www.mathworks.com/help/curvefit/csaps.html) function that is an implementation of +Fortran routine SMOOTH from [PGS](http://pages.cs.wisc.edu/~deboor/pgs/) (originally written by Carl de Boor). + +Also the algothithm implementation in other languages: + +* [csaps-rs](https://github.com/espdev/csaps-rs) Rust ndarray/sprs based implementation +* [csaps-cpp](https://github.com/espdev/csaps-cpp) C++11 Eigen based implementation (incomplete) + + +## References + +C. de Boor, A Practical Guide to Splines, Springer-Verlag, 1978. + +## License + +[MIT](https://choosealicense.com/licenses/mit/) + +# Changelog + +## v1.1.0 + +* Introduced optional `normalizedsmooth` argument to reduce dependence on xdata and weights [#47](https://github.com/espdev/csaps/pull/47) +* Update numpy and scipy dependency ranges + +## v1.0.4 (04.05.2021) + +* Bump numpy dependency version + +## v1.0.3 (01.01.2021) + +* Bump scipy dependency version +* Bump sphinx dependency version and use m2r2 sphinx extension instead of m2r +* Add Python 3.9 to classifiers list and to Travis CI +* Set development status classifier to "5 - Production/Stable" +* Happy New Year! + +## v1.0.2 (19.07.2020) + +* Fix using 'nu' argument when n-d grid spline evaluating [#32](https://github.com/espdev/csaps/pull/32) + +## v1.0.1 (19.07.2020) + +* Fix n-d grid spline evaluating performance regression [#31](https://github.com/espdev/csaps/pull/31) + +## v1.0.0 (11.07.2020) + +* Use `PPoly` and `NdPPoly` base classes from SciPy interpolate module for `SplinePPForm` and `NdGridSplinePPForm` respectively. +* Remove deprecated classes `UnivariateCubicSmoothingSpline` and `MultivariateCubicSmoothingSpline` +* Update the documentation + +**Notes** + +In this release the spline representation (the array of spline coefficients) has been changed +according to `PPoly`/`NdPPoly`. +See SciPy [PPoly](https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.PPoly.html) +and [NdPPoly](https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.NdPPoly.html) documentation for details. + + +## v0.11.0 (28.03.2020) + +* Internal re-design `SplinePPForm` and `NdGridSplinePPForm` classes [#17](https://github.com/espdev/csaps/issues/17): + - Remove `shape` and `axis` properties and reshaping data in these classes + - `NdGridSplinePPForm` coefficients array for 1D grid now is 1-d instead of 2-d +* Refactoring the code and decrease memory consumption +* Add `overload` type-hints for `csaps` function signatures + +## v0.10.1 (19.03.2020) + +* Fix call of `numpy.pad` function for numpy <1.17 [#15](https://github.com/espdev/csaps/issues/15) + +## v0.10.0 (18.02.2020) + +* Significant performance improvements for make/evaluate splines and memory consumption optimization +* Change format for storing spline coefficients (reshape coeffs array) to improve performance +* Add shape property to `SplinePPForm`/`NdGridSplinePPForm` and axis property to `SplinePPForm` +* Fix issues with the smoothing factor in nd-grid case: inverted ordering and unnable to use 0.0 value +* Update documentation + +## v0.9.0 (21.01.2020) + +* Drop support of Python 3.5 +* `weights`, `smooth` and `axis` arguments in `csaps` function are keyword-only now +* `UnivariateCubicSmoothingSpline` and `MultivariateCubicSmoothingSpline` classes are deprecated + and will be removed in 1.0.0 version. Use `CubicSmoothingSpline` instead. + +## v0.8.0 (13.01.2020) + +* Add `csaps` function that can be used as the main API +* Refactor the internal structure of the package +* Add the [documentation](https://csaps.readthedocs.io) + +**Attention** + +This is the last version that supports Python 3.5. +The next versions will support Python 3.6 or above. + +## v0.7.0 (19.09.2019) + +* Add Generic-based type-hints and mypy-compatibility + +## v0.6.1 (13.09.2019) + +* A slight refactoring and extra data copies removing + +## v0.6.0 (12.09.2019) + +* Add "axis" parameter for univariate/multivariate cases + +## v0.5.0 (10.06.2019) + +* Reorganize the project to package-based structure +* Add the interface class for all smoothing spline classes + +## v0.4.2 (07.09.2019) + +* FIX: "smooth" value is 0.0 was not used + +## v0.4.1 (30.05.2019) + +* First PyPI release + + + + +%package help +Summary: Development documents and examples for csaps +Provides: python3-csaps-doc +%description help +

+ csaps
+

+ +

+ PyPI version + Supported Python versions + GitHub Actions (Tests) + Documentation Status + Coverage Status + License +

+ +**csaps** is a Python package for univariate, multivariate and n-dimensional grid data approximation using cubic smoothing splines. +The package can be useful in practical engineering tasks for data approximation and smoothing. + +## Installing + +Use pip for installing: + +``` +pip install -U csaps +``` + +The module depends only on NumPy and SciPy. Python 3.6 or above is supported. + +## Simple Examples + +Here is a couple of examples of smoothing data. + +An univariate data smoothing: + +```python +import numpy as np +import matplotlib.pyplot as plt + +from csaps import csaps + +np.random.seed(1234) + +x = np.linspace(-5., 5., 25) +y = np.exp(-(x/2.5)**2) + (np.random.rand(25) - 0.2) * 0.3 +xs = np.linspace(x[0], x[-1], 150) + +ys = csaps(x, y, xs, smooth=0.85) + +plt.plot(x, y, 'o', xs, ys, '-') +plt.show() +``` + +

+ univariate +

+ +A surface data smoothing: + +```python +import numpy as np +import matplotlib.pyplot as plt +from mpl_toolkits.mplot3d import Axes3D + +from csaps import csaps + +np.random.seed(1234) +xdata = [np.linspace(-3, 3, 41), np.linspace(-3.5, 3.5, 31)] +i, j = np.meshgrid(*xdata, indexing='ij') +ydata = (3 * (1 - j)**2. * np.exp(-(j**2) - (i + 1)**2) + - 10 * (j / 5 - j**3 - i**5) * np.exp(-j**2 - i**2) + - 1 / 3 * np.exp(-(j + 1)**2 - i**2)) +ydata = ydata + (np.random.randn(*ydata.shape) * 0.75) + +ydata_s = csaps(xdata, ydata, xdata, smooth=0.988) + +fig = plt.figure(figsize=(7, 4.5)) +ax = fig.add_subplot(111, projection='3d') +ax.set_facecolor('none') +c = [s['color'] for s in plt.rcParams['axes.prop_cycle']] +ax.plot_wireframe(j, i, ydata, linewidths=0.5, color=c[0], alpha=0.5) +ax.scatter(j, i, ydata, s=10, c=c[0], alpha=0.5) +ax.plot_surface(j, i, ydata_s, color=c[1], linewidth=0, alpha=1.0) +ax.view_init(elev=9., azim=290) + +plt.show() +``` + +

+ surface +

+ +## Documentation + +More examples of usage and the full documentation can be found at https://csaps.readthedocs.io. + +## Testing + +We use pytest for testing. + +``` +cd /path/to/csaps/project/directory +pip install -e .[tests] +pytest +``` + +## Algorithm and Implementation + +**csaps** Python package is inspired by MATLAB [CSAPS](https://www.mathworks.com/help/curvefit/csaps.html) function that is an implementation of +Fortran routine SMOOTH from [PGS](http://pages.cs.wisc.edu/~deboor/pgs/) (originally written by Carl de Boor). + +Also the algothithm implementation in other languages: + +* [csaps-rs](https://github.com/espdev/csaps-rs) Rust ndarray/sprs based implementation +* [csaps-cpp](https://github.com/espdev/csaps-cpp) C++11 Eigen based implementation (incomplete) + + +## References + +C. de Boor, A Practical Guide to Splines, Springer-Verlag, 1978. + +## License + +[MIT](https://choosealicense.com/licenses/mit/) + +# Changelog + +## v1.1.0 + +* Introduced optional `normalizedsmooth` argument to reduce dependence on xdata and weights [#47](https://github.com/espdev/csaps/pull/47) +* Update numpy and scipy dependency ranges + +## v1.0.4 (04.05.2021) + +* Bump numpy dependency version + +## v1.0.3 (01.01.2021) + +* Bump scipy dependency version +* Bump sphinx dependency version and use m2r2 sphinx extension instead of m2r +* Add Python 3.9 to classifiers list and to Travis CI +* Set development status classifier to "5 - Production/Stable" +* Happy New Year! + +## v1.0.2 (19.07.2020) + +* Fix using 'nu' argument when n-d grid spline evaluating [#32](https://github.com/espdev/csaps/pull/32) + +## v1.0.1 (19.07.2020) + +* Fix n-d grid spline evaluating performance regression [#31](https://github.com/espdev/csaps/pull/31) + +## v1.0.0 (11.07.2020) + +* Use `PPoly` and `NdPPoly` base classes from SciPy interpolate module for `SplinePPForm` and `NdGridSplinePPForm` respectively. +* Remove deprecated classes `UnivariateCubicSmoothingSpline` and `MultivariateCubicSmoothingSpline` +* Update the documentation + +**Notes** + +In this release the spline representation (the array of spline coefficients) has been changed +according to `PPoly`/`NdPPoly`. +See SciPy [PPoly](https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.PPoly.html) +and [NdPPoly](https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.NdPPoly.html) documentation for details. + + +## v0.11.0 (28.03.2020) + +* Internal re-design `SplinePPForm` and `NdGridSplinePPForm` classes [#17](https://github.com/espdev/csaps/issues/17): + - Remove `shape` and `axis` properties and reshaping data in these classes + - `NdGridSplinePPForm` coefficients array for 1D grid now is 1-d instead of 2-d +* Refactoring the code and decrease memory consumption +* Add `overload` type-hints for `csaps` function signatures + +## v0.10.1 (19.03.2020) + +* Fix call of `numpy.pad` function for numpy <1.17 [#15](https://github.com/espdev/csaps/issues/15) + +## v0.10.0 (18.02.2020) + +* Significant performance improvements for make/evaluate splines and memory consumption optimization +* Change format for storing spline coefficients (reshape coeffs array) to improve performance +* Add shape property to `SplinePPForm`/`NdGridSplinePPForm` and axis property to `SplinePPForm` +* Fix issues with the smoothing factor in nd-grid case: inverted ordering and unnable to use 0.0 value +* Update documentation + +## v0.9.0 (21.01.2020) + +* Drop support of Python 3.5 +* `weights`, `smooth` and `axis` arguments in `csaps` function are keyword-only now +* `UnivariateCubicSmoothingSpline` and `MultivariateCubicSmoothingSpline` classes are deprecated + and will be removed in 1.0.0 version. Use `CubicSmoothingSpline` instead. + +## v0.8.0 (13.01.2020) + +* Add `csaps` function that can be used as the main API +* Refactor the internal structure of the package +* Add the [documentation](https://csaps.readthedocs.io) + +**Attention** + +This is the last version that supports Python 3.5. +The next versions will support Python 3.6 or above. + +## v0.7.0 (19.09.2019) + +* Add Generic-based type-hints and mypy-compatibility + +## v0.6.1 (13.09.2019) + +* A slight refactoring and extra data copies removing + +## v0.6.0 (12.09.2019) + +* Add "axis" parameter for univariate/multivariate cases + +## v0.5.0 (10.06.2019) + +* Reorganize the project to package-based structure +* Add the interface class for all smoothing spline classes + +## v0.4.2 (07.09.2019) + +* FIX: "smooth" value is 0.0 was not used + +## v0.4.1 (30.05.2019) + +* First PyPI release + + + + +%prep +%autosetup -n csaps-1.1.0 + +%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-csaps -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Apr 11 2023 Python_Bot - 1.1.0-1 +- Package Spec generated -- cgit v1.2.3