%global _empty_manifest_terminate_build 0 Name: python-adtk Version: 0.6.2 Release: 1 Summary: A package for unsupervised time series anomaly detection License: Mozilla Public License 2.0 (MPL 2.0) URL: https://github.com/arundo/adtk Source0: https://mirrors.nju.edu.cn/pypi/web/packages/dc/72/ba10b935b4941a5d7e54edce86354ec389d08d06b53aae4e7fa464fed0e3/adtk-0.6.2.tar.gz BuildArch: noarch Requires: python3-numpy Requires: python3-pandas Requires: python3-matplotlib Requires: python3-scikit-learn Requires: python3-statsmodels Requires: python3-packaging Requires: python3-tabulate Requires: python3-black Requires: python3-isort Requires: python3-sphinx Requires: python3-sphinx-rtd-theme Requires: python3-nbsphinx Requires: python3-dateutil Requires: python3-jupyter Requires: python3-pytest Requires: python3-tox Requires: python3-coverage Requires: python3-pytest-cov Requires: python3-coveralls Requires: python3-mypy %description # Anomaly Detection Toolkit (ADTK) [![Build Status](https://travis-ci.com/arundo/adtk.svg?branch=master)](https://travis-ci.com/arundo/adtk) [![Documentation Status](https://readthedocs.org/projects/adtk/badge/?version=stable)](https://adtk.readthedocs.io/en/stable) [![Coverage Status](https://coveralls.io/repos/github/arundo/adtk/badge.svg?branch=master&service=github)](https://coveralls.io/github/arundo/adtk?branch=master) [![PyPI](https://img.shields.io/pypi/v/adtk)](https://pypi.org/project/adtk/) [![Downloads](https://pepy.tech/badge/adtk)](https://pepy.tech/project/adtk) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/arundo/adtk/master?filepath=docs%2Fnotebooks%2Fdemo.ipynb) Anomaly Detection Toolkit (ADTK) is a Python package for unsupervised / rule-based time series anomaly detection. As the nature of anomaly varies over different cases, a model may not work universally for all anomaly detection problems. Choosing and combining detection algorithms (detectors), feature engineering methods (transformers), and ensemble methods (aggregators) properly is the key to build an effective anomaly detection model. This package offers a set of common detectors, transformers and aggregators with unified APIs, as well as pipe classes that connect them together into models. It also provides some functions to process and visualize time series and anomaly events. See https://adtk.readthedocs.io for complete documentation. ## Installation Prerequisites: Python 3.5 or later. It is recommended to install the most recent **stable** release of ADTK from PyPI. ```shell pip install adtk ``` Alternatively, you could install from source code. This will give you the **latest**, but unstable, version of ADTK. ```shell git clone https://github.com/arundo/adtk.git cd adtk/ git checkout develop pip install ./ ``` ## Examples Please see [Quick Start](https://adtk.readthedocs.io/en/stable/quickstart.html) for a simple example. For more detailed examples of each module of ADTK, please refer to [Examples](https://adtk.readthedocs.io/en/stable/examples.html) section in the documentation or [an interactive demo notebook](https://mybinder.org/v2/gh/arundo/adtk/master?filepath=docs%2Fnotebooks%2Fdemo.ipynb). ## Contributing Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please make sure to update unit tests as appropriate. Please see [Contributing](https://adtk.readthedocs.io/en/stable/developer.html) for more details. ## License ADTK is licensed under the Mozilla Public License 2.0 (MPL 2.0). See the [LICENSE](LICENSE) file for details. %package -n python3-adtk Summary: A package for unsupervised time series anomaly detection Provides: python-adtk BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-adtk # Anomaly Detection Toolkit (ADTK) [![Build Status](https://travis-ci.com/arundo/adtk.svg?branch=master)](https://travis-ci.com/arundo/adtk) [![Documentation Status](https://readthedocs.org/projects/adtk/badge/?version=stable)](https://adtk.readthedocs.io/en/stable) [![Coverage Status](https://coveralls.io/repos/github/arundo/adtk/badge.svg?branch=master&service=github)](https://coveralls.io/github/arundo/adtk?branch=master) [![PyPI](https://img.shields.io/pypi/v/adtk)](https://pypi.org/project/adtk/) [![Downloads](https://pepy.tech/badge/adtk)](https://pepy.tech/project/adtk) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/arundo/adtk/master?filepath=docs%2Fnotebooks%2Fdemo.ipynb) Anomaly Detection Toolkit (ADTK) is a Python package for unsupervised / rule-based time series anomaly detection. As the nature of anomaly varies over different cases, a model may not work universally for all anomaly detection problems. Choosing and combining detection algorithms (detectors), feature engineering methods (transformers), and ensemble methods (aggregators) properly is the key to build an effective anomaly detection model. This package offers a set of common detectors, transformers and aggregators with unified APIs, as well as pipe classes that connect them together into models. It also provides some functions to process and visualize time series and anomaly events. See https://adtk.readthedocs.io for complete documentation. ## Installation Prerequisites: Python 3.5 or later. It is recommended to install the most recent **stable** release of ADTK from PyPI. ```shell pip install adtk ``` Alternatively, you could install from source code. This will give you the **latest**, but unstable, version of ADTK. ```shell git clone https://github.com/arundo/adtk.git cd adtk/ git checkout develop pip install ./ ``` ## Examples Please see [Quick Start](https://adtk.readthedocs.io/en/stable/quickstart.html) for a simple example. For more detailed examples of each module of ADTK, please refer to [Examples](https://adtk.readthedocs.io/en/stable/examples.html) section in the documentation or [an interactive demo notebook](https://mybinder.org/v2/gh/arundo/adtk/master?filepath=docs%2Fnotebooks%2Fdemo.ipynb). ## Contributing Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please make sure to update unit tests as appropriate. Please see [Contributing](https://adtk.readthedocs.io/en/stable/developer.html) for more details. ## License ADTK is licensed under the Mozilla Public License 2.0 (MPL 2.0). See the [LICENSE](LICENSE) file for details. %package help Summary: Development documents and examples for adtk Provides: python3-adtk-doc %description help # Anomaly Detection Toolkit (ADTK) [![Build Status](https://travis-ci.com/arundo/adtk.svg?branch=master)](https://travis-ci.com/arundo/adtk) [![Documentation Status](https://readthedocs.org/projects/adtk/badge/?version=stable)](https://adtk.readthedocs.io/en/stable) [![Coverage Status](https://coveralls.io/repos/github/arundo/adtk/badge.svg?branch=master&service=github)](https://coveralls.io/github/arundo/adtk?branch=master) [![PyPI](https://img.shields.io/pypi/v/adtk)](https://pypi.org/project/adtk/) [![Downloads](https://pepy.tech/badge/adtk)](https://pepy.tech/project/adtk) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/arundo/adtk/master?filepath=docs%2Fnotebooks%2Fdemo.ipynb) Anomaly Detection Toolkit (ADTK) is a Python package for unsupervised / rule-based time series anomaly detection. As the nature of anomaly varies over different cases, a model may not work universally for all anomaly detection problems. Choosing and combining detection algorithms (detectors), feature engineering methods (transformers), and ensemble methods (aggregators) properly is the key to build an effective anomaly detection model. This package offers a set of common detectors, transformers and aggregators with unified APIs, as well as pipe classes that connect them together into models. It also provides some functions to process and visualize time series and anomaly events. See https://adtk.readthedocs.io for complete documentation. ## Installation Prerequisites: Python 3.5 or later. It is recommended to install the most recent **stable** release of ADTK from PyPI. ```shell pip install adtk ``` Alternatively, you could install from source code. This will give you the **latest**, but unstable, version of ADTK. ```shell git clone https://github.com/arundo/adtk.git cd adtk/ git checkout develop pip install ./ ``` ## Examples Please see [Quick Start](https://adtk.readthedocs.io/en/stable/quickstart.html) for a simple example. For more detailed examples of each module of ADTK, please refer to [Examples](https://adtk.readthedocs.io/en/stable/examples.html) section in the documentation or [an interactive demo notebook](https://mybinder.org/v2/gh/arundo/adtk/master?filepath=docs%2Fnotebooks%2Fdemo.ipynb). ## Contributing Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please make sure to update unit tests as appropriate. Please see [Contributing](https://adtk.readthedocs.io/en/stable/developer.html) for more details. ## License ADTK is licensed under the Mozilla Public License 2.0 (MPL 2.0). See the [LICENSE](LICENSE) file for details. %prep %autosetup -n adtk-0.6.2 %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-adtk -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Mon Apr 10 2023 Python_Bot - 0.6.2-1 - Package Spec generated