%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_logo](./img/logo_transparent.png) 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_logo](./img/logo_transparent.png) 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_logo](./img/logo_transparent.png) 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 - 0.4.5-1 - Package Spec generated