automatic import of python-kxyopeneuler20.03

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+/kxy-1.4.11.tar.gz
diff --git a/python-kxy.spec b/python-kxy.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-kxy
+Version:	1.4.11
+Release:	1
+Summary:	A Powerful Serverless Pre-Learning and Post-Learning Analysis Toolkit
+License:	GPLv3
+URL:		https://www.kxy.ai
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/43/d1/a8ce29122712ba3edd8cfabcbd2a0f30bfb3534b4f406f5489fa5c982a4b/kxy-1.4.11.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+Requires:	python3-scipy
+Requires:	python3-pandas
+Requires:	python3-requests
+Requires:	python3-pandarallel
+Requires:	python3-halo
+Requires:	python3-ipywidgets
+Requires:	python3-scikit-learn
+
+%description
+# Boosting The Productivity of Machine Learning Engineers
+[![License](https://img.shields.io/badge/license-GPLv3%2B-blue)](https://github.com/kxytechnologies/kxy-python/blob/master/LICENSE)
+[![PyPI Latest Release](https://img.shields.io/pypi/v/kxy.svg)](https://www.kxy.ai/)
+[![Downloads](https://pepy.tech/badge/kxy)](https://www.kxy.ai/)
+## Documentation
+https://www.kxy.ai/reference/
+## Blog
+https://blog.kxy.ai
+## Installation
+From PyPi:
+```Bash
+pip install kxy -U
+```
+From GitHub:
+```Bash
+git clone https://github.com/kxytechnologies/kxy-python.git & cd ./kxy-python & pip install .
+```
+## Authentication
+All heavy-duty computations are run on our serverless infrastructure and require an API key. To configure the package with your API key, run 
+```Bash
+kxy configure
+```
+and follow the instructions. To get your own API key you need an account; you can sign up [here](https://www.kxy.ai/signup/). You'll then be automatically given an API key which you can find [here](https://www.kxy.ai/portal/profile/identity/).
+## Docker
+The Docker image [kxytechnologies/kxy](https://hub.docker.com/repository/docker/kxytechnologies/kxy) has been built for your convenience, and comes with anaconda, auto-sklearn, and the kxy package. 
+To start a Jupyter Notebook server from a sandboxed Docker environment, run
+```Bash
+docker run -i -t -p 5555:8888 kxytechnologies/kxy:latest /bin/bash -c "kxy configure <YOUR API KEY> && /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root --NotebookApp.token=''"
+```
+where you should replace `<YOUR API KEY>` with your API key and navigate to [http://localhost:5555](http://localhost:5555) in your browser. This docker environment comes with [all examples available on the documentation website](https://www.kxy.ai/reference/latest/examples/).
+To start a Jupyter Notebook server from an existing directory of notebooks, run
+```Bash
+docker run -i -t --mount src=</path/to/your/local/dir>,target=/opt/notebooks,type=bind -p 5555:8888 kxytechnologies/kxy:latest /bin/bash -c "kxy configure <YOUR API KEY> && /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root --NotebookApp.token=''"
+```
+where you should replace `</path/to/your/local/dir>` with the path to your local notebook folder and navigate to [http://localhost:5555](http://localhost:5555) in your browser.
+You can also get the same Docker image from GitHub [here](https://github.com/kxytechnologies/kxy-python/pkgs/container/kxy-python).
+## Other Programming Language
+We plan to release friendly API client in more programming language. 
+In the meantime, you can directly issue requests to our [RESTFul API](https://www.kxy.ai/reference/latest/api/index.html) using your favorite programming language. 
+## Pricing 
+All API keys are given a free quota (a few dozen backend tasks) that should be enough to try out the package and see if you love it. Beyond the free quota you will be billed a small fee per task. 
+KXY is free for academic use; simply signup with your university email. 
+KXY is also free for Kaggle competitions; sign up and email kaggle@kxy.ai to get a promotional code.
+
+%package -n python3-kxy
+Summary:	A Powerful Serverless Pre-Learning and Post-Learning Analysis Toolkit
+Provides:	python-kxy
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-kxy
+# Boosting The Productivity of Machine Learning Engineers
+[![License](https://img.shields.io/badge/license-GPLv3%2B-blue)](https://github.com/kxytechnologies/kxy-python/blob/master/LICENSE)
+[![PyPI Latest Release](https://img.shields.io/pypi/v/kxy.svg)](https://www.kxy.ai/)
+[![Downloads](https://pepy.tech/badge/kxy)](https://www.kxy.ai/)
+## Documentation
+https://www.kxy.ai/reference/
+## Blog
+https://blog.kxy.ai
+## Installation
+From PyPi:
+```Bash
+pip install kxy -U
+```
+From GitHub:
+```Bash
+git clone https://github.com/kxytechnologies/kxy-python.git & cd ./kxy-python & pip install .
+```
+## Authentication
+All heavy-duty computations are run on our serverless infrastructure and require an API key. To configure the package with your API key, run 
+```Bash
+kxy configure
+```
+and follow the instructions. To get your own API key you need an account; you can sign up [here](https://www.kxy.ai/signup/). You'll then be automatically given an API key which you can find [here](https://www.kxy.ai/portal/profile/identity/).
+## Docker
+The Docker image [kxytechnologies/kxy](https://hub.docker.com/repository/docker/kxytechnologies/kxy) has been built for your convenience, and comes with anaconda, auto-sklearn, and the kxy package. 
+To start a Jupyter Notebook server from a sandboxed Docker environment, run
+```Bash
+docker run -i -t -p 5555:8888 kxytechnologies/kxy:latest /bin/bash -c "kxy configure <YOUR API KEY> && /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root --NotebookApp.token=''"
+```
+where you should replace `<YOUR API KEY>` with your API key and navigate to [http://localhost:5555](http://localhost:5555) in your browser. This docker environment comes with [all examples available on the documentation website](https://www.kxy.ai/reference/latest/examples/).
+To start a Jupyter Notebook server from an existing directory of notebooks, run
+```Bash
+docker run -i -t --mount src=</path/to/your/local/dir>,target=/opt/notebooks,type=bind -p 5555:8888 kxytechnologies/kxy:latest /bin/bash -c "kxy configure <YOUR API KEY> && /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root --NotebookApp.token=''"
+```
+where you should replace `</path/to/your/local/dir>` with the path to your local notebook folder and navigate to [http://localhost:5555](http://localhost:5555) in your browser.
+You can also get the same Docker image from GitHub [here](https://github.com/kxytechnologies/kxy-python/pkgs/container/kxy-python).
+## Other Programming Language
+We plan to release friendly API client in more programming language. 
+In the meantime, you can directly issue requests to our [RESTFul API](https://www.kxy.ai/reference/latest/api/index.html) using your favorite programming language. 
+## Pricing 
+All API keys are given a free quota (a few dozen backend tasks) that should be enough to try out the package and see if you love it. Beyond the free quota you will be billed a small fee per task. 
+KXY is free for academic use; simply signup with your university email. 
+KXY is also free for Kaggle competitions; sign up and email kaggle@kxy.ai to get a promotional code.
+
+%package help
+Summary:	Development documents and examples for kxy
+Provides:	python3-kxy-doc
+%description help
+# Boosting The Productivity of Machine Learning Engineers
+[![License](https://img.shields.io/badge/license-GPLv3%2B-blue)](https://github.com/kxytechnologies/kxy-python/blob/master/LICENSE)
+[![PyPI Latest Release](https://img.shields.io/pypi/v/kxy.svg)](https://www.kxy.ai/)
+[![Downloads](https://pepy.tech/badge/kxy)](https://www.kxy.ai/)
+## Documentation
+https://www.kxy.ai/reference/
+## Blog
+https://blog.kxy.ai
+## Installation
+From PyPi:
+```Bash
+pip install kxy -U
+```
+From GitHub:
+```Bash
+git clone https://github.com/kxytechnologies/kxy-python.git & cd ./kxy-python & pip install .
+```
+## Authentication
+All heavy-duty computations are run on our serverless infrastructure and require an API key. To configure the package with your API key, run 
+```Bash
+kxy configure
+```
+and follow the instructions. To get your own API key you need an account; you can sign up [here](https://www.kxy.ai/signup/). You'll then be automatically given an API key which you can find [here](https://www.kxy.ai/portal/profile/identity/).
+## Docker
+The Docker image [kxytechnologies/kxy](https://hub.docker.com/repository/docker/kxytechnologies/kxy) has been built for your convenience, and comes with anaconda, auto-sklearn, and the kxy package. 
+To start a Jupyter Notebook server from a sandboxed Docker environment, run
+```Bash
+docker run -i -t -p 5555:8888 kxytechnologies/kxy:latest /bin/bash -c "kxy configure <YOUR API KEY> && /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root --NotebookApp.token=''"
+```
+where you should replace `<YOUR API KEY>` with your API key and navigate to [http://localhost:5555](http://localhost:5555) in your browser. This docker environment comes with [all examples available on the documentation website](https://www.kxy.ai/reference/latest/examples/).
+To start a Jupyter Notebook server from an existing directory of notebooks, run
+```Bash
+docker run -i -t --mount src=</path/to/your/local/dir>,target=/opt/notebooks,type=bind -p 5555:8888 kxytechnologies/kxy:latest /bin/bash -c "kxy configure <YOUR API KEY> && /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root --NotebookApp.token=''"
+```
+where you should replace `</path/to/your/local/dir>` with the path to your local notebook folder and navigate to [http://localhost:5555](http://localhost:5555) in your browser.
+You can also get the same Docker image from GitHub [here](https://github.com/kxytechnologies/kxy-python/pkgs/container/kxy-python).
+## Other Programming Language
+We plan to release friendly API client in more programming language. 
+In the meantime, you can directly issue requests to our [RESTFul API](https://www.kxy.ai/reference/latest/api/index.html) using your favorite programming language. 
+## Pricing 
+All API keys are given a free quota (a few dozen backend tasks) that should be enough to try out the package and see if you love it. Beyond the free quota you will be billed a small fee per task. 
+KXY is free for academic use; simply signup with your university email. 
+KXY is also free for Kaggle competitions; sign up and email kaggle@kxy.ai to get a promotional code.
+
+%prep
+%autosetup -n kxy-1.4.11
+
+%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-kxy -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.4.11-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
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--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+3436b530ab08d0c5c0274220636cc49c  kxy-1.4.11.tar.gz