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|
%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.aliyun.com/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
[](https://mloq.readthedocs.io/en/latest/?badge=latest)
[](https://codecov.io/github/fragiletech/ml-ops-quickstart)
[](https://pypi.org/project/mloq/)
[](https://github.com/ambv/black)
[](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
```
## [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
[](https://mloq.readthedocs.io/en/latest/?badge=latest)
[](https://codecov.io/github/fragiletech/ml-ops-quickstart)
[](https://pypi.org/project/mloq/)
[](https://github.com/ambv/black)
[](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
```
## [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
[](https://mloq.readthedocs.io/en/latest/?badge=latest)
[](https://codecov.io/github/fragiletech/ml-ops-quickstart)
[](https://pypi.org/project/mloq/)
[](https://github.com/ambv/black)
[](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
```
## [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
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.75-1
- Package Spec generated
|
