automatic import of python-locationtaggeropeneuler20.03

3 files changed, 87 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..ad02c5a 100644
--- a/.gitignore
+++ b/.gitignore
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+/locationtagger-0.0.1.tar.gz
diff --git a/python-locationtagger.spec b/python-locationtagger.spec
new file mode 100644
index 0000000..978c380
--- /dev/null
+++ b/python-locationtagger.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-locationtagger
+Version:	0.0.1
+Release:	1
+Summary:	Detect & Extract locations from text or URL and find relationships among locations
+License:	MIT
+URL:		https://github.com/kaushiksoni10/locationtagger
+Source0:	https://mirrors.aliyun.com/pypi/web/packages/48/fb/9b7a5f874fe5d54b6de8aeb9ff0fd86e720a38716e7c444b1f3683601ba8/locationtagger-0.0.1.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-nltk
+Requires:	python3-spacy
+Requires:	python3-newspaper3k
+Requires:	python3-pycountry
+
+%description
+## About Project
+In the field of [Natural Lauguage Processing](https://en.wikipedia.org/wiki/Natural_language_processing), many algorithms have been derived for different types of syntactic & semantic analysis of the textual data. NER ([Named Entity Recognition](https://en.wikipedia.org/wiki/Named-entity_recognition)) is one of the best & frequently needed tasks in real-world problems of text mining that follows some grammer-based rules & statistical modelling approaches. An entity extracted from NER can be a name of person, place, organization or product. [locationtagger](https://github.com/kaushiksoni10/locationtagger) is a further process of tagging & filter out place names (locations) amongst all the entities found with NER.
+Approach followed is given below in the picture;
+https://github.com/kaushiksoni10/locationtagger/blob/master/locationtagger/data/diagram.jpg?raw=true
+
+%package -n python3-locationtagger
+Summary:	Detect & Extract locations from text or URL and find relationships among locations
+Provides:	python-locationtagger
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-locationtagger
+## About Project
+In the field of [Natural Lauguage Processing](https://en.wikipedia.org/wiki/Natural_language_processing), many algorithms have been derived for different types of syntactic & semantic analysis of the textual data. NER ([Named Entity Recognition](https://en.wikipedia.org/wiki/Named-entity_recognition)) is one of the best & frequently needed tasks in real-world problems of text mining that follows some grammer-based rules & statistical modelling approaches. An entity extracted from NER can be a name of person, place, organization or product. [locationtagger](https://github.com/kaushiksoni10/locationtagger) is a further process of tagging & filter out place names (locations) amongst all the entities found with NER.
+Approach followed is given below in the picture;
+https://github.com/kaushiksoni10/locationtagger/blob/master/locationtagger/data/diagram.jpg?raw=true
+
+%package help
+Summary:	Development documents and examples for locationtagger
+Provides:	python3-locationtagger-doc
+%description help
+## About Project
+In the field of [Natural Lauguage Processing](https://en.wikipedia.org/wiki/Natural_language_processing), many algorithms have been derived for different types of syntactic & semantic analysis of the textual data. NER ([Named Entity Recognition](https://en.wikipedia.org/wiki/Named-entity_recognition)) is one of the best & frequently needed tasks in real-world problems of text mining that follows some grammer-based rules & statistical modelling approaches. An entity extracted from NER can be a name of person, place, organization or product. [locationtagger](https://github.com/kaushiksoni10/locationtagger) is a further process of tagging & filter out place names (locations) amongst all the entities found with NER.
+Approach followed is given below in the picture;
+https://github.com/kaushiksoni10/locationtagger/blob/master/locationtagger/data/diagram.jpg?raw=true
+
+%prep
+%autosetup -n locationtagger-0.0.1
+
+%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-locationtagger -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.1-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..0ecdf7c
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+9fbcff56b16e62baa52ce21a7f24ae37  locationtagger-0.0.1.tar.gz