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diff --git a/python-pydojoml.spec b/python-pydojoml.spec new file mode 100644 index 0000000..bd9457a --- /dev/null +++ b/python-pydojoml.spec @@ -0,0 +1,347 @@ +%global _empty_manifest_terminate_build 0 +Name: python-PyDojoML +Version: 0.4.5 +Release: 1 +Summary: A General Purpose Machine Learning Library for Python +License: MIT License +URL: https://github.com/VIVelev/PyDojoML +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/cf/84/206bed622d9b5df8605308329d244c7d6c8944df0ac5cc9401917d0cb11c/PyDojoML-0.4.5.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-scipy +Requires: python3-matplotlib +Requires: python3-progressbar +Requires: python3-terminaltables + +%description +# Dojo + + +Dojo is a Machine Learning library for Python + +## Getting Started + +These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. + +### Prerequisites + +* [Python](https://www.python.org/) - The Programming Language used. +* [Pipenv](https://github.com/pypa/pipenv) - Dependency and Virtual Environment Management + +***Download for Mac OSX using Homebrew*** +``` +brew install python +brew install pipenv +``` + +### Installing for development + +A step by step series of examples that tell you how to get a development env running + +1) Since we are using the **Python** programming language as a main language, you will need to download it. +You can do so from the official **Python** [website](https://www.python.org/). + +2) Once you have **Python** up and running we then need to setup our development env. For that +we are using **Pipenv**. You will need to install it. Check out [these](https://pipenv.readthedocs.io/en/latest/install/#installing-pipenv) instructions to see how is done. + +3) Now, that you have the prerequisites the only part left is too install all the other **Pyhton** packages +that **Dojo** depends on. To do run the following: + ``` + pipenv install --dev + ``` + The `--dev` tag is used in order **Pipenv** to know to install also the packages that are used in the + package development process. + +### Installing for use + +If you plan just to use **Dojo** as a Machine Learning library you can install it using **pip** like so: +``` +pip install pydojoml +``` + +## Running the tests + +Coming soon... + +### Break down into end to end tests + +Coming soon... + +### And coding style tests + +Coming soon... + +## Built With + +* [NumPy](http://www.numpy.org/) - Fundamental package for scientific computing with Python +* [SciPy](http://www.scipy.org/) - Package that provides many user-friendly and efficient numerical routines +* [Matplotlib](http://www.matplotlib.org/) - Python 2D plotting library +* [progressbar](https://pypi.org/project/progressbar/) - Text progress bar library for Python +* [terminaltables](https://pypi.org/project/terminaltables/) - Easily draw tables in terminal/console applications + +## Contributing + +Please read [CONTRIBUTING.md](https://github.com/VIVelev/PyDojoML/CONTRIBUTING.md) for details on our code of conduct, and the process for submitting pull requests to us. + +## Versioning + +For the versions available, see the [tags on this repository](https://github.com/VIVelev/PyDojoML/tags). + +## Authors + +* **Victor Velev** - *Initial work* - [VIVelev](https://github.com/VIVelev) + +See also the list of [contributors](https://github.com/VIVelev/PyDojoML/contributors) who participated in this project. + +## License + +This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details + +## Acknowledgments + +* **Eric Jones and Travis Oliphant and Pearu Peterson and others** for writing such great packages - the [SciPy](http://www.scipy.org/) ecosystem. +* **Nilton Volpato** for writing [progressbar](https://pypi.org/project/progressbar/) +* **Robpol86** for writing [terminaltables](https://pypi.org/project/terminaltables/) + + + + +%package -n python3-PyDojoML +Summary: A General Purpose Machine Learning Library for Python +Provides: python-PyDojoML +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-PyDojoML +# Dojo + + +Dojo is a Machine Learning library for Python + +## Getting Started + +These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. + +### Prerequisites + +* [Python](https://www.python.org/) - The Programming Language used. +* [Pipenv](https://github.com/pypa/pipenv) - Dependency and Virtual Environment Management + +***Download for Mac OSX using Homebrew*** +``` +brew install python +brew install pipenv +``` + +### Installing for development + +A step by step series of examples that tell you how to get a development env running + +1) Since we are using the **Python** programming language as a main language, you will need to download it. +You can do so from the official **Python** [website](https://www.python.org/). + +2) Once you have **Python** up and running we then need to setup our development env. For that +we are using **Pipenv**. You will need to install it. Check out [these](https://pipenv.readthedocs.io/en/latest/install/#installing-pipenv) instructions to see how is done. + +3) Now, that you have the prerequisites the only part left is too install all the other **Pyhton** packages +that **Dojo** depends on. To do run the following: + ``` + pipenv install --dev + ``` + The `--dev` tag is used in order **Pipenv** to know to install also the packages that are used in the + package development process. + +### Installing for use + +If you plan just to use **Dojo** as a Machine Learning library you can install it using **pip** like so: +``` +pip install pydojoml +``` + +## Running the tests + +Coming soon... + +### Break down into end to end tests + +Coming soon... + +### And coding style tests + +Coming soon... + +## Built With + +* [NumPy](http://www.numpy.org/) - Fundamental package for scientific computing with Python +* [SciPy](http://www.scipy.org/) - Package that provides many user-friendly and efficient numerical routines +* [Matplotlib](http://www.matplotlib.org/) - Python 2D plotting library +* [progressbar](https://pypi.org/project/progressbar/) - Text progress bar library for Python +* [terminaltables](https://pypi.org/project/terminaltables/) - Easily draw tables in terminal/console applications + +## Contributing + +Please read [CONTRIBUTING.md](https://github.com/VIVelev/PyDojoML/CONTRIBUTING.md) for details on our code of conduct, and the process for submitting pull requests to us. + +## Versioning + +For the versions available, see the [tags on this repository](https://github.com/VIVelev/PyDojoML/tags). + +## Authors + +* **Victor Velev** - *Initial work* - [VIVelev](https://github.com/VIVelev) + +See also the list of [contributors](https://github.com/VIVelev/PyDojoML/contributors) who participated in this project. + +## License + +This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details + +## Acknowledgments + +* **Eric Jones and Travis Oliphant and Pearu Peterson and others** for writing such great packages - the [SciPy](http://www.scipy.org/) ecosystem. +* **Nilton Volpato** for writing [progressbar](https://pypi.org/project/progressbar/) +* **Robpol86** for writing [terminaltables](https://pypi.org/project/terminaltables/) + + + + +%package help +Summary: Development documents and examples for PyDojoML +Provides: python3-PyDojoML-doc +%description help +# Dojo + + +Dojo is a Machine Learning library for Python + +## Getting Started + +These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. + +### Prerequisites + +* [Python](https://www.python.org/) - The Programming Language used. +* [Pipenv](https://github.com/pypa/pipenv) - Dependency and Virtual Environment Management + +***Download for Mac OSX using Homebrew*** +``` +brew install python +brew install pipenv +``` + +### Installing for development + +A step by step series of examples that tell you how to get a development env running + +1) Since we are using the **Python** programming language as a main language, you will need to download it. +You can do so from the official **Python** [website](https://www.python.org/). + +2) Once you have **Python** up and running we then need to setup our development env. For that +we are using **Pipenv**. You will need to install it. Check out [these](https://pipenv.readthedocs.io/en/latest/install/#installing-pipenv) instructions to see how is done. + +3) Now, that you have the prerequisites the only part left is too install all the other **Pyhton** packages +that **Dojo** depends on. To do run the following: + ``` + pipenv install --dev + ``` + The `--dev` tag is used in order **Pipenv** to know to install also the packages that are used in the + package development process. + +### Installing for use + +If you plan just to use **Dojo** as a Machine Learning library you can install it using **pip** like so: +``` +pip install pydojoml +``` + +## Running the tests + +Coming soon... + +### Break down into end to end tests + +Coming soon... + +### And coding style tests + +Coming soon... + +## Built With + +* [NumPy](http://www.numpy.org/) - Fundamental package for scientific computing with Python +* [SciPy](http://www.scipy.org/) - Package that provides many user-friendly and efficient numerical routines +* [Matplotlib](http://www.matplotlib.org/) - Python 2D plotting library +* [progressbar](https://pypi.org/project/progressbar/) - Text progress bar library for Python +* [terminaltables](https://pypi.org/project/terminaltables/) - Easily draw tables in terminal/console applications + +## Contributing + +Please read [CONTRIBUTING.md](https://github.com/VIVelev/PyDojoML/CONTRIBUTING.md) for details on our code of conduct, and the process for submitting pull requests to us. + +## Versioning + +For the versions available, see the [tags on this repository](https://github.com/VIVelev/PyDojoML/tags). + +## Authors + +* **Victor Velev** - *Initial work* - [VIVelev](https://github.com/VIVelev) + +See also the list of [contributors](https://github.com/VIVelev/PyDojoML/contributors) who participated in this project. + +## License + +This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details + +## Acknowledgments + +* **Eric Jones and Travis Oliphant and Pearu Peterson and others** for writing such great packages - the [SciPy](http://www.scipy.org/) ecosystem. +* **Nilton Volpato** for writing [progressbar](https://pypi.org/project/progressbar/) +* **Robpol86** for writing [terminaltables](https://pypi.org/project/terminaltables/) + + + + +%prep +%autosetup -n PyDojoML-0.4.5 + +%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-PyDojoML -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed May 17 2023 Python_Bot <Python_Bot@openeuler.org> - 0.4.5-1 +- Package Spec generated |