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diff --git a/python-serveit.spec b/python-serveit.spec new file mode 100644 index 0000000..3e3846f --- /dev/null +++ b/python-serveit.spec @@ -0,0 +1,167 @@ +%global _empty_manifest_terminate_build 0 +Name: python-ServeIt +Version: 0.0.9 +Release: 1 +Summary: Machine learning prediction serving +License: MIT License +URL: https://github.com/rtlee9/serveit +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/f6/83/bda15c52f95b802f7da9165d076e6f4d9601a385b278f81fb8a2706072cb/ServeIt-0.0.9.tar.gz +BuildArch: noarch + +Requires: python3-flask +Requires: python3-flask-restful +Requires: python3-meinheld +Requires: python3-check-manifest +Requires: python3-coverage + +%description +|Build Status| |Codacy Grade Badge| |Codacy Coverage Badge| |PyPI +version| +ServeIt lets you serve model predictions and supplementary information +from a RESTful API using your favorite Python ML library in as little as +one line of code: + from serveit.server import ModelServer + from sklearn.linear_model import LogisticRegression + from sklearn.datasets import load_iris + # fit logistic regression on Iris data + clf = LogisticRegression() + data = load_iris() + clf.fit(data.data, data.target) + # initialize server with a model and start serving predictions + ModelServer(clf, clf.predict).serve() +Your new API is now accepting ``POST`` requests at +``localhost:5000/predictions``! Please see the `examples <examples>`__ +directory for detailed examples across domains (e.g., regression, image +classification), including live examples. +Features +^^^^^^^^ +Current ServeIt features include: +1. Model inference serving via RESTful API endpoint +2. Extensible library for inference-time data loading, preprocessing, + input validation, and postprocessing +3. Supplementary information endpoint creation +4. Automatic JSON serialization of responses +5. Configurable request and response logging (work in progress) +Supported libraries +^^^^^^^^^^^^^^^^^^^ +The following libraries are currently supported: \* Scikit-Learn \* +Keras \* PyTorch + +%package -n python3-ServeIt +Summary: Machine learning prediction serving +Provides: python-ServeIt +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-ServeIt +|Build Status| |Codacy Grade Badge| |Codacy Coverage Badge| |PyPI +version| +ServeIt lets you serve model predictions and supplementary information +from a RESTful API using your favorite Python ML library in as little as +one line of code: + from serveit.server import ModelServer + from sklearn.linear_model import LogisticRegression + from sklearn.datasets import load_iris + # fit logistic regression on Iris data + clf = LogisticRegression() + data = load_iris() + clf.fit(data.data, data.target) + # initialize server with a model and start serving predictions + ModelServer(clf, clf.predict).serve() +Your new API is now accepting ``POST`` requests at +``localhost:5000/predictions``! Please see the `examples <examples>`__ +directory for detailed examples across domains (e.g., regression, image +classification), including live examples. +Features +^^^^^^^^ +Current ServeIt features include: +1. Model inference serving via RESTful API endpoint +2. Extensible library for inference-time data loading, preprocessing, + input validation, and postprocessing +3. Supplementary information endpoint creation +4. Automatic JSON serialization of responses +5. Configurable request and response logging (work in progress) +Supported libraries +^^^^^^^^^^^^^^^^^^^ +The following libraries are currently supported: \* Scikit-Learn \* +Keras \* PyTorch + +%package help +Summary: Development documents and examples for ServeIt +Provides: python3-ServeIt-doc +%description help +|Build Status| |Codacy Grade Badge| |Codacy Coverage Badge| |PyPI +version| +ServeIt lets you serve model predictions and supplementary information +from a RESTful API using your favorite Python ML library in as little as +one line of code: + from serveit.server import ModelServer + from sklearn.linear_model import LogisticRegression + from sklearn.datasets import load_iris + # fit logistic regression on Iris data + clf = LogisticRegression() + data = load_iris() + clf.fit(data.data, data.target) + # initialize server with a model and start serving predictions + ModelServer(clf, clf.predict).serve() +Your new API is now accepting ``POST`` requests at +``localhost:5000/predictions``! Please see the `examples <examples>`__ +directory for detailed examples across domains (e.g., regression, image +classification), including live examples. +Features +^^^^^^^^ +Current ServeIt features include: +1. Model inference serving via RESTful API endpoint +2. Extensible library for inference-time data loading, preprocessing, + input validation, and postprocessing +3. Supplementary information endpoint creation +4. Automatic JSON serialization of responses +5. Configurable request and response logging (work in progress) +Supported libraries +^^^^^^^^^^^^^^^^^^^ +The following libraries are currently supported: \* Scikit-Learn \* +Keras \* PyTorch + +%prep +%autosetup -n ServeIt-0.0.9 + +%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-ServeIt -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.9-1 +- Package Spec generated |