automatic import of python-whylogsopeneuler20.03

3 files changed, 329 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..871a671 100644
--- a/.gitignore
+++ b/.gitignore
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+/whylogs-1.1.39.tar.gz
diff --git a/python-whylogs.spec b/python-whylogs.spec
new file mode 100644
index 0000000..5d900b1
--- /dev/null
+++ b/python-whylogs.spec
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+%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> &bull;
+   <a href="https://bit.ly/whylogsslack"><b>Slack Community</b></a> &bull;
+   <a href="https://github.com/whylabs/whylogs#python-quickstart"><b>Python Quickstart</b></a> &bull;
+   <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> &bull;
+   <a href="https://bit.ly/whylogsslack"><b>Slack Community</b></a> &bull;
+   <a href="https://github.com/whylabs/whylogs#python-quickstart"><b>Python Quickstart</b></a> &bull;
+   <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> &bull;
+   <a href="https://bit.ly/whylogsslack"><b>Slack Community</b></a> &bull;
+   <a href="https://github.com/whylabs/whylogs#python-quickstart"><b>Python Quickstart</b></a> &bull;
+   <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
diff --git a/sources b/sources
new file mode 100644
index 0000000..b58cdeb
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+aec85dcf891b5dd9c219246ddd81a28f  whylogs-1.1.39.tar.gz