automatic import of python-aspecd

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+%global _empty_manifest_terminate_build 0
+Name:		python-aspecd
+Version:	0.8.0
+Release:	1
+Summary:	Framework for handling spectroscopic data.
+License:	BSD
+URL:		https://www.aspecd.de/
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/93/94/812ec7958882e2e0e8c12c6551a2f8c53c162d6888d17098625fdf0ec718/aspecd-0.8.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-asdf
+Requires:	python3-bibrecord
+Requires:	python3-jinja2
+Requires:	python3-matplotlib
+Requires:	python3-numpy
+Requires:	python3-oyaml
+Requires:	python3-scipy
+Requires:	python3-prospector
+Requires:	python3-sphinx
+Requires:	python3-sphinx-multiversion
+Requires:	python3-sphinx-rtd-theme
+
+%description
+ASpecD is a **framework for handling spectroscopic data** focussing on **reproducibility**. In short: Each and every processing step applied to your data will be recorded and can be traced back, and additionally, for each representation of your data (e.g., figures, tables) you can easily follow how the data shown have been processed and where they originate from.
+What is even better: Actual data processing and analysis **no longer requires programming skills**, but is as simple as writing a text file summarising all the steps you want to have been performed on your dataset(s) in an organised way. Curious? Here is an example::
+    format:
+      type: ASpecD recipe
+      version: '0.2'
+    datasets:
+      - /path/to/first/dataset
+      - /path/to/second/dataset
+    tasks:
+      - kind: processing
+        type: BaselineCorrection
+        properties:
+          parameters:
+            kind: polynomial
+            order: 0
+      - kind: singleplot
+        type: SinglePlotter1D
+        properties:
+          filename:
+            - first-dataset.pdf
+            - second-dataset.pdf
+For more general information on the ASpecD framework see its `homepage <https://www.aspecd.de/>`_, and for how to use it, its `documentation <https://doc.aspecd.de/>`_.
+
+%package -n python3-aspecd
+Summary:	Framework for handling spectroscopic data.
+Provides:	python-aspecd
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-aspecd
+ASpecD is a **framework for handling spectroscopic data** focussing on **reproducibility**. In short: Each and every processing step applied to your data will be recorded and can be traced back, and additionally, for each representation of your data (e.g., figures, tables) you can easily follow how the data shown have been processed and where they originate from.
+What is even better: Actual data processing and analysis **no longer requires programming skills**, but is as simple as writing a text file summarising all the steps you want to have been performed on your dataset(s) in an organised way. Curious? Here is an example::
+    format:
+      type: ASpecD recipe
+      version: '0.2'
+    datasets:
+      - /path/to/first/dataset
+      - /path/to/second/dataset
+    tasks:
+      - kind: processing
+        type: BaselineCorrection
+        properties:
+          parameters:
+            kind: polynomial
+            order: 0
+      - kind: singleplot
+        type: SinglePlotter1D
+        properties:
+          filename:
+            - first-dataset.pdf
+            - second-dataset.pdf
+For more general information on the ASpecD framework see its `homepage <https://www.aspecd.de/>`_, and for how to use it, its `documentation <https://doc.aspecd.de/>`_.
+
+%package help
+Summary:	Development documents and examples for aspecd
+Provides:	python3-aspecd-doc
+%description help
+ASpecD is a **framework for handling spectroscopic data** focussing on **reproducibility**. In short: Each and every processing step applied to your data will be recorded and can be traced back, and additionally, for each representation of your data (e.g., figures, tables) you can easily follow how the data shown have been processed and where they originate from.
+What is even better: Actual data processing and analysis **no longer requires programming skills**, but is as simple as writing a text file summarising all the steps you want to have been performed on your dataset(s) in an organised way. Curious? Here is an example::
+    format:
+      type: ASpecD recipe
+      version: '0.2'
+    datasets:
+      - /path/to/first/dataset
+      - /path/to/second/dataset
+    tasks:
+      - kind: processing
+        type: BaselineCorrection
+        properties:
+          parameters:
+            kind: polynomial
+            order: 0
+      - kind: singleplot
+        type: SinglePlotter1D
+        properties:
+          filename:
+            - first-dataset.pdf
+            - second-dataset.pdf
+For more general information on the ASpecD framework see its `homepage <https://www.aspecd.de/>`_, and for how to use it, its `documentation <https://doc.aspecd.de/>`_.
+
+%prep
+%autosetup -n aspecd-0.8.0
+
+%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-aspecd -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 29 2023 Python_Bot <Python_Bot@openeuler.org> - 0.8.0-1
+- Package Spec generated