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authorCoprDistGit <infra@openeuler.org>2023-05-15 05:38:12 +0000
committerCoprDistGit <infra@openeuler.org>2023-05-15 05:38:12 +0000
commit3e5343e964251bd25e0deced975e766760561876 (patch)
tree55f9cf23ec3a65a13fc172d5dc37b2b87075ca75
parent0d6cf0d4ef54086cadf06523f18060fee41667ad (diff)
automatic import of python-ads2gephi
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-rw-r--r--python-ads2gephi.spec226
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+/ads2gephi-0.3.8.tar.gz
diff --git a/python-ads2gephi.spec b/python-ads2gephi.spec
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+%global _empty_manifest_terminate_build 0
+Name: python-ads2gephi
+Version: 0.3.8
+Release: 1
+Summary: A command line tool for querying and modeling citation networks from the Astrophysical Data System (ADS) in a format compatible with Gephi
+License: MIT
+URL: https://github.com/03b8/ads2gephi
+Source0: https://mirrors.nju.edu.cn/pypi/web/packages/66/93/3d29d926e03b5a06d86aea431c764427e0c881ba4690448e02814682a4ae/ads2gephi-0.3.8.tar.gz
+BuildArch: noarch
+
+Requires: python3-ads
+Requires: python3-sqlalchemy
+Requires: python3-configparser
+Requires: python3-click
+Requires: python3-igraph
+Requires: python3-tqdm
+Requires: python3-yaspin
+
+%description
+[![PyPI version](https://badge.fury.io/py/ads2gephi.svg)](https://badge.fury.io/py/ads2gephi)
+![CI](https://github.com/03b8/ads2gephi/actions/workflows/github-ci.yml/badge.svg)
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+
+# ads2gephi
+
+is a command line tool for querying and modeling citation networks from the Astrophysical Data System (ADS) in a format compatible with Gephi, a popular network visualization tool. ads2gephi has been developed at the history of science department of TU Berlin as part of [a research project on the history of extragalactic astronomy](https://gepris.dfg.de/gepris/projekt/289438140?language=en) financed by the German Research Foundation DFG (PI Karin Pelte).
+
+You can install `ads2gephi` from PyPI:
+```
+pip install ads2gephi
+```
+
+### Usage
+
+When using the tool for the first time to model a network, you will be prompted to enter your ADS API key. Your key will then be stored in a configuration file under ~/.ads2gephi.
+
+In order to sample an initial citation network, you need to provide ads2gephi with a plain text file with bibcodes (ADS unique identifiers), one per line, as input. The queried network will be output in a SQLite database stored in the current directory:
+
+```
+ads2gephi -c bibcodes_example.txt -d my_fancy_netzwerk.db
+```
+
+Afterwards you can extend the queried network by providing the existing database file and using the additional sampling options. For example, you can extend the network by querying all the items cited in every publication previously queried:
+
+```
+ads2gephi -s ref -d my_fancy_netzwerk.db
+```
+
+Finally you might want to also generate the edges of the network. There are several options for generating edges. For example you can use a semantic similarity measure like bibliographic coupling or co-citation:
+```
+ads2gephi -e bibcp -d my_fancy_netzwerk.db
+```
+
+You can also do everything at once:
+```
+ads2gephi -c bibcodes_example.txt -s ref -e bibcp -d my_fancy_netzwerk.db
+```
+
+All other querying and modelling options are described in the help page:
+```
+ads2gephi --help
+```
+
+Once you've finished querying and modeling, the database file can be directly imported in Gephi for network visualization and analysis.
+
+## Special thanks to
+
+* Edwin Henneken
+
+
+%package -n python3-ads2gephi
+Summary: A command line tool for querying and modeling citation networks from the Astrophysical Data System (ADS) in a format compatible with Gephi
+Provides: python-ads2gephi
+BuildRequires: python3-devel
+BuildRequires: python3-setuptools
+BuildRequires: python3-pip
+%description -n python3-ads2gephi
+[![PyPI version](https://badge.fury.io/py/ads2gephi.svg)](https://badge.fury.io/py/ads2gephi)
+![CI](https://github.com/03b8/ads2gephi/actions/workflows/github-ci.yml/badge.svg)
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+
+# ads2gephi
+
+is a command line tool for querying and modeling citation networks from the Astrophysical Data System (ADS) in a format compatible with Gephi, a popular network visualization tool. ads2gephi has been developed at the history of science department of TU Berlin as part of [a research project on the history of extragalactic astronomy](https://gepris.dfg.de/gepris/projekt/289438140?language=en) financed by the German Research Foundation DFG (PI Karin Pelte).
+
+You can install `ads2gephi` from PyPI:
+```
+pip install ads2gephi
+```
+
+### Usage
+
+When using the tool for the first time to model a network, you will be prompted to enter your ADS API key. Your key will then be stored in a configuration file under ~/.ads2gephi.
+
+In order to sample an initial citation network, you need to provide ads2gephi with a plain text file with bibcodes (ADS unique identifiers), one per line, as input. The queried network will be output in a SQLite database stored in the current directory:
+
+```
+ads2gephi -c bibcodes_example.txt -d my_fancy_netzwerk.db
+```
+
+Afterwards you can extend the queried network by providing the existing database file and using the additional sampling options. For example, you can extend the network by querying all the items cited in every publication previously queried:
+
+```
+ads2gephi -s ref -d my_fancy_netzwerk.db
+```
+
+Finally you might want to also generate the edges of the network. There are several options for generating edges. For example you can use a semantic similarity measure like bibliographic coupling or co-citation:
+```
+ads2gephi -e bibcp -d my_fancy_netzwerk.db
+```
+
+You can also do everything at once:
+```
+ads2gephi -c bibcodes_example.txt -s ref -e bibcp -d my_fancy_netzwerk.db
+```
+
+All other querying and modelling options are described in the help page:
+```
+ads2gephi --help
+```
+
+Once you've finished querying and modeling, the database file can be directly imported in Gephi for network visualization and analysis.
+
+## Special thanks to
+
+* Edwin Henneken
+
+
+%package help
+Summary: Development documents and examples for ads2gephi
+Provides: python3-ads2gephi-doc
+%description help
+[![PyPI version](https://badge.fury.io/py/ads2gephi.svg)](https://badge.fury.io/py/ads2gephi)
+![CI](https://github.com/03b8/ads2gephi/actions/workflows/github-ci.yml/badge.svg)
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+
+# ads2gephi
+
+is a command line tool for querying and modeling citation networks from the Astrophysical Data System (ADS) in a format compatible with Gephi, a popular network visualization tool. ads2gephi has been developed at the history of science department of TU Berlin as part of [a research project on the history of extragalactic astronomy](https://gepris.dfg.de/gepris/projekt/289438140?language=en) financed by the German Research Foundation DFG (PI Karin Pelte).
+
+You can install `ads2gephi` from PyPI:
+```
+pip install ads2gephi
+```
+
+### Usage
+
+When using the tool for the first time to model a network, you will be prompted to enter your ADS API key. Your key will then be stored in a configuration file under ~/.ads2gephi.
+
+In order to sample an initial citation network, you need to provide ads2gephi with a plain text file with bibcodes (ADS unique identifiers), one per line, as input. The queried network will be output in a SQLite database stored in the current directory:
+
+```
+ads2gephi -c bibcodes_example.txt -d my_fancy_netzwerk.db
+```
+
+Afterwards you can extend the queried network by providing the existing database file and using the additional sampling options. For example, you can extend the network by querying all the items cited in every publication previously queried:
+
+```
+ads2gephi -s ref -d my_fancy_netzwerk.db
+```
+
+Finally you might want to also generate the edges of the network. There are several options for generating edges. For example you can use a semantic similarity measure like bibliographic coupling or co-citation:
+```
+ads2gephi -e bibcp -d my_fancy_netzwerk.db
+```
+
+You can also do everything at once:
+```
+ads2gephi -c bibcodes_example.txt -s ref -e bibcp -d my_fancy_netzwerk.db
+```
+
+All other querying and modelling options are described in the help page:
+```
+ads2gephi --help
+```
+
+Once you've finished querying and modeling, the database file can be directly imported in Gephi for network visualization and analysis.
+
+## Special thanks to
+
+* Edwin Henneken
+
+
+%prep
+%autosetup -n ads2gephi-0.3.8
+
+%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-ads2gephi -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 0.3.8-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
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--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+b7ec6ed12e3cde8b10b8e82e4e7de98c ads2gephi-0.3.8.tar.gz