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| author | CoprDistGit <infra@openeuler.org> | 2023-05-05 04:35:55 +0000 |
|---|---|---|
| committer | CoprDistGit <infra@openeuler.org> | 2023-05-05 04:35:55 +0000 |
| commit | 78ab8237261dedff61a0cab25a7944891ddb02e1 (patch) | |
| tree | 7e4c8937c1665e96fc4d5cf49520655abd3f7a65 /python-whylogs.spec | |
| parent | a7b6bde95526487447fb63cebf9a955f73c516e3 (diff) | |
automatic import of python-whylogsopeneuler20.03
Diffstat (limited to 'python-whylogs.spec')
| -rw-r--r-- | python-whylogs.spec | 327 |
1 files changed, 327 insertions, 0 deletions
diff --git a/python-whylogs.spec b/python-whylogs.spec new file mode 100644 index 0000000..5d900b1 --- /dev/null +++ b/python-whylogs.spec @@ -0,0 +1,327 @@ +%global _empty_manifest_terminate_build 0 +Name: python-whylogs +Version: 1.1.39 +Release: 1 +Summary: Profile and monitor your ML data pipeline end-to-end +License: Apache-2.0 +URL: https://docs.whylabs.ai +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/a0/d2/50c3c523d2cf5cc61c0fdb387f677b367cc37afb60f174a2345f7e0d0094/whylogs-1.1.39.tar.gz +BuildArch: noarch + +Requires: python3-Pillow +Requires: python3-boto3 +Requires: python3-fugue +Requires: python3-furo +Requires: python3-google-cloud-storage +Requires: python3-importlib-metadata +Requires: python3-ipython +Requires: python3-ipython_genutils +Requires: python3-mlflow-skinny +Requires: python3-myst-parser[sphinx] +Requires: python3-nbconvert +Requires: python3-nbsphinx +Requires: python3-numpy +Requires: python3-numpy +Requires: python3-pandas +Requires: python3-protobuf +Requires: python3-pyarrow +Requires: python3-pybars3 +Requires: python3-pyspark +Requires: python3-requests +Requires: python3-scikit-learn +Requires: python3-scikit-learn +Requires: python3-scipy +Requires: python3-scipy +Requires: python3-sphinx +Requires: python3-sphinx-autoapi +Requires: python3-sphinx-autobuild +Requires: python3-sphinx-copybutton +Requires: python3-sphinx-inline-tabs +Requires: python3-sphinxext-opengraph +Requires: python3-typing-extensions +Requires: python3-whylabs-client +Requires: python3-whylogs-sketching + +%description +<img src="https://static.scarf.sh/a.png?x-pxid=bc3c57b0-9a65-49fe-b8ea-f711c4d35b82" /><p align="center"> +<img src="https://i.imgur.com/nv33goV.png" width="35%"/> +</br> + +<h1 align="center">The open standard for data logging + + </h1> + <h3 align="center"> + <a href="https://whylogs.readthedocs.io/"><b>Documentation</b></a> • + <a href="https://bit.ly/whylogsslack"><b>Slack Community</b></a> • + <a href="https://github.com/whylabs/whylogs#python-quickstart"><b>Python Quickstart</b></a> • + <a href="https://whylogs.readthedocs.io/en/latest/examples/integrations/writers/Writing_to_WhyLabs.html"><b>WhyLabs Quickstart</b></a> + </h3> + +<p align="center"> +<a href="https://github.com/whylabs/whylogs-python/blob/mainline/LICENSE" target="_blank"> + <img src="http://img.shields.io/:license-Apache%202-blue.svg" alt="License"> +</a> +<a href="https://badge.fury.io/py/whylogs" target="_blank"> + <img src="https://badge.fury.io/py/whylogs.svg" alt="PyPi Version"> +</a> +<a href="https://github.com/python/black" target="_blank"> + <img src="https://img.shields.io/badge/code%20style-black-000000.svg" alt="Code style: black"> +</a> +<a href="https://pepy.tech/project/whylogs" target="_blank"> + <img src="https://pepy.tech/badge/whylogs" alt="PyPi Downloads"> +</a> +<a href="bit.ly/whylogs" target="_blank"> + <img src="https://github.com/whylabs/whylogs-python/workflows/whylogs%20CI/badge.svg" alt="CI"> +</a> +<a href="https://codeclimate.com/github/whylabs/whylogs-python/maintainability" target="_blank"> + <img src="https://api.codeclimate.com/v1/badges/442f6ca3dca1e583a488/maintainability" alt="Maintainability"> +</a> +</p> + +## What is whylogs + +whylogs is an open source library for logging any kind of data. With whylogs, users are able to generate summaries of their datasets (called _whylogs profiles_) which they can use to: + +1. Track changes in their dataset +2. Create _data constraints_ to know whether their data looks the way it should +3. Quickly visualize key summary statistics about their datasets + +These three functionalities enable a variety of use cases for data scientists, machine learning engineers, and data engineers: + +- Detect data drift in model input features +- Detect training-serving skew, concept drift, and model performance degradation +- Validate data quality in model inputs or in a data pipeline +- Perform exploratory data analysis of massive datasets +- Track data distributions & data quality for ML experiments +- Enable data auditing and governance across the organization +- Standardize data documentation practices across the organization +- And more + +## Quickstart + +Install whylogs using the pip package manager in a terminal by running: + +``` +pip install whylogs +``` + +Then you can log data in python as simply as this: + +```python +import whylogs as why +import pandas as pd + +df = pd.read_csv("path/to/file.csv") +results = why.log(df) +``` + +And voilà, you now have a whylogs profile. To learn more about what a whylogs profile is and what you can do with it, check out our [docs](https://whylogs.readthedocs.io/en/latest/) and our [examples](https://github.com/whylabs/whylogs/tree/mainline/python/examples). + + + +%package -n python3-whylogs +Summary: Profile and monitor your ML data pipeline end-to-end +Provides: python-whylogs +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-whylogs +<img src="https://static.scarf.sh/a.png?x-pxid=bc3c57b0-9a65-49fe-b8ea-f711c4d35b82" /><p align="center"> +<img src="https://i.imgur.com/nv33goV.png" width="35%"/> +</br> + +<h1 align="center">The open standard for data logging + + </h1> + <h3 align="center"> + <a href="https://whylogs.readthedocs.io/"><b>Documentation</b></a> • + <a href="https://bit.ly/whylogsslack"><b>Slack Community</b></a> • + <a href="https://github.com/whylabs/whylogs#python-quickstart"><b>Python Quickstart</b></a> • + <a href="https://whylogs.readthedocs.io/en/latest/examples/integrations/writers/Writing_to_WhyLabs.html"><b>WhyLabs Quickstart</b></a> + </h3> + +<p align="center"> +<a href="https://github.com/whylabs/whylogs-python/blob/mainline/LICENSE" target="_blank"> + <img src="http://img.shields.io/:license-Apache%202-blue.svg" alt="License"> +</a> +<a href="https://badge.fury.io/py/whylogs" target="_blank"> + <img src="https://badge.fury.io/py/whylogs.svg" alt="PyPi Version"> +</a> +<a href="https://github.com/python/black" target="_blank"> + <img src="https://img.shields.io/badge/code%20style-black-000000.svg" alt="Code style: black"> +</a> +<a href="https://pepy.tech/project/whylogs" target="_blank"> + <img src="https://pepy.tech/badge/whylogs" alt="PyPi Downloads"> +</a> +<a href="bit.ly/whylogs" target="_blank"> + <img src="https://github.com/whylabs/whylogs-python/workflows/whylogs%20CI/badge.svg" alt="CI"> +</a> +<a href="https://codeclimate.com/github/whylabs/whylogs-python/maintainability" target="_blank"> + <img src="https://api.codeclimate.com/v1/badges/442f6ca3dca1e583a488/maintainability" alt="Maintainability"> +</a> +</p> + +## What is whylogs + +whylogs is an open source library for logging any kind of data. With whylogs, users are able to generate summaries of their datasets (called _whylogs profiles_) which they can use to: + +1. Track changes in their dataset +2. Create _data constraints_ to know whether their data looks the way it should +3. Quickly visualize key summary statistics about their datasets + +These three functionalities enable a variety of use cases for data scientists, machine learning engineers, and data engineers: + +- Detect data drift in model input features +- Detect training-serving skew, concept drift, and model performance degradation +- Validate data quality in model inputs or in a data pipeline +- Perform exploratory data analysis of massive datasets +- Track data distributions & data quality for ML experiments +- Enable data auditing and governance across the organization +- Standardize data documentation practices across the organization +- And more + +## Quickstart + +Install whylogs using the pip package manager in a terminal by running: + +``` +pip install whylogs +``` + +Then you can log data in python as simply as this: + +```python +import whylogs as why +import pandas as pd + +df = pd.read_csv("path/to/file.csv") +results = why.log(df) +``` + +And voilà, you now have a whylogs profile. To learn more about what a whylogs profile is and what you can do with it, check out our [docs](https://whylogs.readthedocs.io/en/latest/) and our [examples](https://github.com/whylabs/whylogs/tree/mainline/python/examples). + + + +%package help +Summary: Development documents and examples for whylogs +Provides: python3-whylogs-doc +%description help +<img src="https://static.scarf.sh/a.png?x-pxid=bc3c57b0-9a65-49fe-b8ea-f711c4d35b82" /><p align="center"> +<img src="https://i.imgur.com/nv33goV.png" width="35%"/> +</br> + +<h1 align="center">The open standard for data logging + + </h1> + <h3 align="center"> + <a href="https://whylogs.readthedocs.io/"><b>Documentation</b></a> • + <a href="https://bit.ly/whylogsslack"><b>Slack Community</b></a> • + <a href="https://github.com/whylabs/whylogs#python-quickstart"><b>Python Quickstart</b></a> • + <a href="https://whylogs.readthedocs.io/en/latest/examples/integrations/writers/Writing_to_WhyLabs.html"><b>WhyLabs Quickstart</b></a> + </h3> + +<p align="center"> +<a href="https://github.com/whylabs/whylogs-python/blob/mainline/LICENSE" target="_blank"> + <img src="http://img.shields.io/:license-Apache%202-blue.svg" alt="License"> +</a> +<a href="https://badge.fury.io/py/whylogs" target="_blank"> + <img src="https://badge.fury.io/py/whylogs.svg" alt="PyPi Version"> +</a> +<a href="https://github.com/python/black" target="_blank"> + <img src="https://img.shields.io/badge/code%20style-black-000000.svg" alt="Code style: black"> +</a> +<a href="https://pepy.tech/project/whylogs" target="_blank"> + <img src="https://pepy.tech/badge/whylogs" alt="PyPi Downloads"> +</a> +<a href="bit.ly/whylogs" target="_blank"> + <img src="https://github.com/whylabs/whylogs-python/workflows/whylogs%20CI/badge.svg" alt="CI"> +</a> +<a href="https://codeclimate.com/github/whylabs/whylogs-python/maintainability" target="_blank"> + <img src="https://api.codeclimate.com/v1/badges/442f6ca3dca1e583a488/maintainability" alt="Maintainability"> +</a> +</p> + +## What is whylogs + +whylogs is an open source library for logging any kind of data. With whylogs, users are able to generate summaries of their datasets (called _whylogs profiles_) which they can use to: + +1. Track changes in their dataset +2. Create _data constraints_ to know whether their data looks the way it should +3. Quickly visualize key summary statistics about their datasets + +These three functionalities enable a variety of use cases for data scientists, machine learning engineers, and data engineers: + +- Detect data drift in model input features +- Detect training-serving skew, concept drift, and model performance degradation +- Validate data quality in model inputs or in a data pipeline +- Perform exploratory data analysis of massive datasets +- Track data distributions & data quality for ML experiments +- Enable data auditing and governance across the organization +- Standardize data documentation practices across the organization +- And more + +## Quickstart + +Install whylogs using the pip package manager in a terminal by running: + +``` +pip install whylogs +``` + +Then you can log data in python as simply as this: + +```python +import whylogs as why +import pandas as pd + +df = pd.read_csv("path/to/file.csv") +results = why.log(df) +``` + +And voilà, you now have a whylogs profile. To learn more about what a whylogs profile is and what you can do with it, check out our [docs](https://whylogs.readthedocs.io/en/latest/) and our [examples](https://github.com/whylabs/whylogs/tree/mainline/python/examples). + + + +%prep +%autosetup -n whylogs-1.1.39 + +%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-whylogs -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.39-1 +- Package Spec generated |
