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+%global _empty_manifest_terminate_build 0
+Name:		python-spotty
+Version:	1.3.3
+Release:	1
+Summary:	Training deep learning models on AWS and GCP instances
+License:	MIT
+URL:		https://github.com/spotty-cloud/spotty
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/8d/28/8fcb680613f400e68059d62b45e8fabb2d77caadf3ef40f3153535daab4d/spotty-1.3.3.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-boto3
+Requires:	python3-google-api-python-client
+Requires:	python3-google-cloud-storage
+Requires:	python3-cfn-flip
+Requires:	python3-schema
+Requires:	python3-chevron
+
+%description
+<img src="https://spotty.cloud/_static/images/logo_740x240.png" width="370" height="120" />
+
+[![Documentation](https://img.shields.io/badge/documentation-reference-brightgreen.svg)](https://spotty.cloud)
+[![PyPI](https://img.shields.io/pypi/v/spotty.svg)](https://pypi.org/project/spotty/)
+![PyPI - Python Version](https://img.shields.io/pypi/pyversions/spotty.svg)
+![PyPI - License](https://img.shields.io/pypi/l/spotty.svg)
+
+Spotty drastically simplifies training of deep learning models on [AWS](https://aws.amazon.com/) 
+and [GCP](https://cloud.google.com/):
+
+- it makes training on GPU instances as simple as training on your local machine
+- it automatically manages all necessary cloud resources including images, volumes, snapshots and SSH keys
+- it makes your model trainable in the cloud by everyone with a couple of commands
+- it uses [tmux](https://en.wikipedia.org/wiki/Tmux) to easily detach remote processes from their terminals
+- it saves you up to 70% of the costs by using [AWS Spot Instances](https://aws.amazon.com/ec2/spot/) 
+and [GCP Preemtible VMs](https://cloud.google.com/preemptible-vms/)
+
+## Documentation
+
+- See the [documentation page](https://spotty.cloud).
+- Read [this](https://medium.com/@apls/how-to-train-deep-learning-models-on-aws-spot-instances-using-spotty-8d9e0543d365) 
+article on Medium for a real-world example.
+
+## Installation
+
+Requirements:
+  * Python >=3.6
+  * AWS CLI (see [Installing the AWS Command Line Interface](http://docs.aws.amazon.com/cli/latest/userguide/installing.html)) 
+  if you're using AWS
+  * Google Cloud SDK (see [Installing Google Cloud SDK](https://cloud.google.com/sdk/install)) 
+  if you're using GCP
+
+Use [pip](http://www.pip-installer.org/en/latest/) to install or upgrade Spotty:
+
+    $ pip install -U spotty
+
+## Get Started
+
+1. Prepare a `spotty.yaml` file and put it to the root directory of your project:
+
+   - See the file specification [here](https://spotty.cloud/docs/user-guide/configuration-file.html).
+   - Read [this](https://medium.com/@apls/how-to-train-deep-learning-models-on-aws-spot-instances-using-spotty-8d9e0543d365) 
+   article for a real-world example.
+
+2. Start an instance:
+
+    ```bash
+    $ spotty start
+    ```
+
+    It will run a Spot Instance, restore snapshots if any, synchronize the project with the running instance 
+    and start the Docker container with the environment.
+
+3. Train a model or run notebooks.
+
+    To connect to the running container via SSH, use the following command:
+
+    ```bash
+    $ spotty sh
+    ```
+
+    It runs a [tmux](https://github.com/tmux/tmux/wiki) session, so you can always detach this session using
+    __`Ctrl + b`__, then __`d`__ combination of keys. To be attached to that session later, just use the
+    `spotty sh` command again.
+
+    Also, you can run your custom scripts inside the Docker container using the `spotty run <SCRIPT_NAME>` command. Read more
+    about custom scripts in the documentation: 
+    [Configuration: "scripts" section](https://spotty.cloud/docs/configuration-file/#scripts-section-optional).
+
+## Contributions
+
+Any feedback or contributions are welcome! Please check out the [guidelines](CONTRIBUTING.md).
+
+## License
+
+[MIT License](LICENSE)
+
+
+
+
+%package -n python3-spotty
+Summary:	Training deep learning models on AWS and GCP instances
+Provides:	python-spotty
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-spotty
+<img src="https://spotty.cloud/_static/images/logo_740x240.png" width="370" height="120" />
+
+[![Documentation](https://img.shields.io/badge/documentation-reference-brightgreen.svg)](https://spotty.cloud)
+[![PyPI](https://img.shields.io/pypi/v/spotty.svg)](https://pypi.org/project/spotty/)
+![PyPI - Python Version](https://img.shields.io/pypi/pyversions/spotty.svg)
+![PyPI - License](https://img.shields.io/pypi/l/spotty.svg)
+
+Spotty drastically simplifies training of deep learning models on [AWS](https://aws.amazon.com/) 
+and [GCP](https://cloud.google.com/):
+
+- it makes training on GPU instances as simple as training on your local machine
+- it automatically manages all necessary cloud resources including images, volumes, snapshots and SSH keys
+- it makes your model trainable in the cloud by everyone with a couple of commands
+- it uses [tmux](https://en.wikipedia.org/wiki/Tmux) to easily detach remote processes from their terminals
+- it saves you up to 70% of the costs by using [AWS Spot Instances](https://aws.amazon.com/ec2/spot/) 
+and [GCP Preemtible VMs](https://cloud.google.com/preemptible-vms/)
+
+## Documentation
+
+- See the [documentation page](https://spotty.cloud).
+- Read [this](https://medium.com/@apls/how-to-train-deep-learning-models-on-aws-spot-instances-using-spotty-8d9e0543d365) 
+article on Medium for a real-world example.
+
+## Installation
+
+Requirements:
+  * Python >=3.6
+  * AWS CLI (see [Installing the AWS Command Line Interface](http://docs.aws.amazon.com/cli/latest/userguide/installing.html)) 
+  if you're using AWS
+  * Google Cloud SDK (see [Installing Google Cloud SDK](https://cloud.google.com/sdk/install)) 
+  if you're using GCP
+
+Use [pip](http://www.pip-installer.org/en/latest/) to install or upgrade Spotty:
+
+    $ pip install -U spotty
+
+## Get Started
+
+1. Prepare a `spotty.yaml` file and put it to the root directory of your project:
+
+   - See the file specification [here](https://spotty.cloud/docs/user-guide/configuration-file.html).
+   - Read [this](https://medium.com/@apls/how-to-train-deep-learning-models-on-aws-spot-instances-using-spotty-8d9e0543d365) 
+   article for a real-world example.
+
+2. Start an instance:
+
+    ```bash
+    $ spotty start
+    ```
+
+    It will run a Spot Instance, restore snapshots if any, synchronize the project with the running instance 
+    and start the Docker container with the environment.
+
+3. Train a model or run notebooks.
+
+    To connect to the running container via SSH, use the following command:
+
+    ```bash
+    $ spotty sh
+    ```
+
+    It runs a [tmux](https://github.com/tmux/tmux/wiki) session, so you can always detach this session using
+    __`Ctrl + b`__, then __`d`__ combination of keys. To be attached to that session later, just use the
+    `spotty sh` command again.
+
+    Also, you can run your custom scripts inside the Docker container using the `spotty run <SCRIPT_NAME>` command. Read more
+    about custom scripts in the documentation: 
+    [Configuration: "scripts" section](https://spotty.cloud/docs/configuration-file/#scripts-section-optional).
+
+## Contributions
+
+Any feedback or contributions are welcome! Please check out the [guidelines](CONTRIBUTING.md).
+
+## License
+
+[MIT License](LICENSE)
+
+
+
+
+%package help
+Summary:	Development documents and examples for spotty
+Provides:	python3-spotty-doc
+%description help
+<img src="https://spotty.cloud/_static/images/logo_740x240.png" width="370" height="120" />
+
+[![Documentation](https://img.shields.io/badge/documentation-reference-brightgreen.svg)](https://spotty.cloud)
+[![PyPI](https://img.shields.io/pypi/v/spotty.svg)](https://pypi.org/project/spotty/)
+![PyPI - Python Version](https://img.shields.io/pypi/pyversions/spotty.svg)
+![PyPI - License](https://img.shields.io/pypi/l/spotty.svg)
+
+Spotty drastically simplifies training of deep learning models on [AWS](https://aws.amazon.com/) 
+and [GCP](https://cloud.google.com/):
+
+- it makes training on GPU instances as simple as training on your local machine
+- it automatically manages all necessary cloud resources including images, volumes, snapshots and SSH keys
+- it makes your model trainable in the cloud by everyone with a couple of commands
+- it uses [tmux](https://en.wikipedia.org/wiki/Tmux) to easily detach remote processes from their terminals
+- it saves you up to 70% of the costs by using [AWS Spot Instances](https://aws.amazon.com/ec2/spot/) 
+and [GCP Preemtible VMs](https://cloud.google.com/preemptible-vms/)
+
+## Documentation
+
+- See the [documentation page](https://spotty.cloud).
+- Read [this](https://medium.com/@apls/how-to-train-deep-learning-models-on-aws-spot-instances-using-spotty-8d9e0543d365) 
+article on Medium for a real-world example.
+
+## Installation
+
+Requirements:
+  * Python >=3.6
+  * AWS CLI (see [Installing the AWS Command Line Interface](http://docs.aws.amazon.com/cli/latest/userguide/installing.html)) 
+  if you're using AWS
+  * Google Cloud SDK (see [Installing Google Cloud SDK](https://cloud.google.com/sdk/install)) 
+  if you're using GCP
+
+Use [pip](http://www.pip-installer.org/en/latest/) to install or upgrade Spotty:
+
+    $ pip install -U spotty
+
+## Get Started
+
+1. Prepare a `spotty.yaml` file and put it to the root directory of your project:
+
+   - See the file specification [here](https://spotty.cloud/docs/user-guide/configuration-file.html).
+   - Read [this](https://medium.com/@apls/how-to-train-deep-learning-models-on-aws-spot-instances-using-spotty-8d9e0543d365) 
+   article for a real-world example.
+
+2. Start an instance:
+
+    ```bash
+    $ spotty start
+    ```
+
+    It will run a Spot Instance, restore snapshots if any, synchronize the project with the running instance 
+    and start the Docker container with the environment.
+
+3. Train a model or run notebooks.
+
+    To connect to the running container via SSH, use the following command:
+
+    ```bash
+    $ spotty sh
+    ```
+
+    It runs a [tmux](https://github.com/tmux/tmux/wiki) session, so you can always detach this session using
+    __`Ctrl + b`__, then __`d`__ combination of keys. To be attached to that session later, just use the
+    `spotty sh` command again.
+
+    Also, you can run your custom scripts inside the Docker container using the `spotty run <SCRIPT_NAME>` command. Read more
+    about custom scripts in the documentation: 
+    [Configuration: "scripts" section](https://spotty.cloud/docs/configuration-file/#scripts-section-optional).
+
+## Contributions
+
+Any feedback or contributions are welcome! Please check out the [guidelines](CONTRIBUTING.md).
+
+## License
+
+[MIT License](LICENSE)
+
+
+
+
+%prep
+%autosetup -n spotty-1.3.3
+
+%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-spotty -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 1.3.3-1
+- Package Spec generated