%global _empty_manifest_terminate_build 0 Name: python-mloq Version: 0.0.75 Release: 1 Summary: Package for initializing ML projects following ML Ops best practices. License: MIT URL: https://github.com/FragileTech/ml-ops-quickstart Source0: https://mirrors.nju.edu.cn/pypi/web/packages/d5/6b/9f81a334398bcaff16c0fba8de8b878e7bdd0a8331872069e36626a2bee5/mloq-0.0.75.tar.gz BuildArch: noarch Requires: python3-flogging Requires: python3-jinja2 Requires: python3-click Requires: python3-invoke Requires: python3-hydra-core Requires: python3-param Requires: python3-pre-commit Requires: python3-typing-extensions %description # ML Ops Quickstart [![Documentation Status](https://readthedocs.org/projects/mloq/badge/?version=latest)](https://mloq.readthedocs.io/en/latest/?badge=latest) [![Code coverage](https://codecov.io/github/fragiletech/ml-ops-quickstart/coverage.svg)](https://codecov.io/github/fragiletech/ml-ops-quickstart) [![PyPI package](https://badgen.net/pypi/v/mloq)](https://pypi.org/project/mloq/) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black) [![license: MIT](https://img.shields.io/badge/license-MIT-green.svg)](https://opensource.org/licenses/MIT) ML Ops Quickstart is a tool for initializing Machine Learning projects following ML Ops best practices. Setting up new repositories is a time-consuming task that involves creating different files and configuring tools such as linters, docker containers and continuous integration pipelines. The goal of `mloq` is to simplify that process, so you can start writing code as fast as possible. `mloq` generates customized templates for Python projects with focus on Maching Learning. An example of the generated templates can be found in [mloq-template](https://github.com/FragileTech/mloq-template). ## [1.](#Index) Installation `mloq` is tested on Ubuntu 18.04+, and supports Python 3.6+. ### Install from pypi ```bash pip install mloq ``` ### Install from source ```bash git clone https://github.com/FragileTech/ml-ops-quickstart.git cd ml-ops-quickstart pip install -e . ``` ## [2.](#Index) Usage ### [2.1](#Index) Command line interface Options: * `--file` `-f`: Name of the configuration file. If `file` it's a directory it will load the `mloq.yml` file present in it. * `--overwrite` `-o`: Rewrite files that already exist in the target project. * `--interactive` `-i`: Missing configuration data can be defined interactively from the CLI. #### Usage examples Arguments: * `OUTPUT_DIRECTORY`: Path to the target project. To set up a new repository from scratch interactively in the curren working directory: ```bash mloq setup -i . ``` To load a `mloq.yml` configuration file from the current repository, and initialize the directory `example`, and overwrite all existing files with no interactivity: ```bash mloq setup -f . -o example ``` ![ci python](docs/images/mloq_setup.png) ## [5.](#Index) License ML Ops Quickstart is released under the [MIT](LICENSE) license. ## [6.](#Index) Contributing Contributions are very welcome! Please check the [contributing guidelines](CONTRIBUTING.md) before opening a pull request. %package -n python3-mloq Summary: Package for initializing ML projects following ML Ops best practices. Provides: python-mloq BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-mloq # ML Ops Quickstart [![Documentation Status](https://readthedocs.org/projects/mloq/badge/?version=latest)](https://mloq.readthedocs.io/en/latest/?badge=latest) [![Code coverage](https://codecov.io/github/fragiletech/ml-ops-quickstart/coverage.svg)](https://codecov.io/github/fragiletech/ml-ops-quickstart) [![PyPI package](https://badgen.net/pypi/v/mloq)](https://pypi.org/project/mloq/) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black) [![license: MIT](https://img.shields.io/badge/license-MIT-green.svg)](https://opensource.org/licenses/MIT) ML Ops Quickstart is a tool for initializing Machine Learning projects following ML Ops best practices. Setting up new repositories is a time-consuming task that involves creating different files and configuring tools such as linters, docker containers and continuous integration pipelines. The goal of `mloq` is to simplify that process, so you can start writing code as fast as possible. `mloq` generates customized templates for Python projects with focus on Maching Learning. An example of the generated templates can be found in [mloq-template](https://github.com/FragileTech/mloq-template). ## [1.](#Index) Installation `mloq` is tested on Ubuntu 18.04+, and supports Python 3.6+. ### Install from pypi ```bash pip install mloq ``` ### Install from source ```bash git clone https://github.com/FragileTech/ml-ops-quickstart.git cd ml-ops-quickstart pip install -e . ``` ## [2.](#Index) Usage ### [2.1](#Index) Command line interface Options: * `--file` `-f`: Name of the configuration file. If `file` it's a directory it will load the `mloq.yml` file present in it. * `--overwrite` `-o`: Rewrite files that already exist in the target project. * `--interactive` `-i`: Missing configuration data can be defined interactively from the CLI. #### Usage examples Arguments: * `OUTPUT_DIRECTORY`: Path to the target project. To set up a new repository from scratch interactively in the curren working directory: ```bash mloq setup -i . ``` To load a `mloq.yml` configuration file from the current repository, and initialize the directory `example`, and overwrite all existing files with no interactivity: ```bash mloq setup -f . -o example ``` ![ci python](docs/images/mloq_setup.png) ## [5.](#Index) License ML Ops Quickstart is released under the [MIT](LICENSE) license. ## [6.](#Index) Contributing Contributions are very welcome! Please check the [contributing guidelines](CONTRIBUTING.md) before opening a pull request. %package help Summary: Development documents and examples for mloq Provides: python3-mloq-doc %description help # ML Ops Quickstart [![Documentation Status](https://readthedocs.org/projects/mloq/badge/?version=latest)](https://mloq.readthedocs.io/en/latest/?badge=latest) [![Code coverage](https://codecov.io/github/fragiletech/ml-ops-quickstart/coverage.svg)](https://codecov.io/github/fragiletech/ml-ops-quickstart) [![PyPI package](https://badgen.net/pypi/v/mloq)](https://pypi.org/project/mloq/) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black) [![license: MIT](https://img.shields.io/badge/license-MIT-green.svg)](https://opensource.org/licenses/MIT) ML Ops Quickstart is a tool for initializing Machine Learning projects following ML Ops best practices. Setting up new repositories is a time-consuming task that involves creating different files and configuring tools such as linters, docker containers and continuous integration pipelines. The goal of `mloq` is to simplify that process, so you can start writing code as fast as possible. `mloq` generates customized templates for Python projects with focus on Maching Learning. An example of the generated templates can be found in [mloq-template](https://github.com/FragileTech/mloq-template). ## [1.](#Index) Installation `mloq` is tested on Ubuntu 18.04+, and supports Python 3.6+. ### Install from pypi ```bash pip install mloq ``` ### Install from source ```bash git clone https://github.com/FragileTech/ml-ops-quickstart.git cd ml-ops-quickstart pip install -e . ``` ## [2.](#Index) Usage ### [2.1](#Index) Command line interface Options: * `--file` `-f`: Name of the configuration file. If `file` it's a directory it will load the `mloq.yml` file present in it. * `--overwrite` `-o`: Rewrite files that already exist in the target project. * `--interactive` `-i`: Missing configuration data can be defined interactively from the CLI. #### Usage examples Arguments: * `OUTPUT_DIRECTORY`: Path to the target project. To set up a new repository from scratch interactively in the curren working directory: ```bash mloq setup -i . ``` To load a `mloq.yml` configuration file from the current repository, and initialize the directory `example`, and overwrite all existing files with no interactivity: ```bash mloq setup -f . -o example ``` ![ci python](docs/images/mloq_setup.png) ## [5.](#Index) License ML Ops Quickstart is released under the [MIT](LICENSE) license. ## [6.](#Index) Contributing Contributions are very welcome! Please check the [contributing guidelines](CONTRIBUTING.md) before opening a pull request. %prep %autosetup -n mloq-0.0.75 %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-mloq -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue May 30 2023 Python_Bot - 0.0.75-1 - Package Spec generated