Metadata-Version: 2.1
Name: netapp-dataops-traditional
Version: 2.5.0b2
Summary: NetApp DataOps Toolkit for Traditional Environments
Home-page: https://github.com/NetApp/netapp-data-science-toolkit/
Author: Mike Oglesby
Author-email: mike.oglesby@netapp.com
Maintainer: NetApp
Maintainer-email: ng-ai-inquiry@netapp.com
License: BSD-3-Clause
Project-URL: Bug Tracker, https://github.com/NetApp/netapp-data-science-toolkit/issues
Project-URL: Documentation, https://github.com/NetApp/netapp-data-science-toolkit/blob/main/README.md
Project-URL: Source Code, https://github.com/NetApp/netapp-data-science-toolkit/
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: <3.13,>=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: netapp-ontap
Requires-Dist: pandas
Requires-Dist: tabulate
Requires-Dist: numpy>=1.22.0
Requires-Dist: requests
Requires-Dist: boto3
Requires-Dist: pyyaml

The NetApp DataOps Toolkit for Traditional Environments is a Python library that makes it simple for developers, data scientists, DevOps engineers, and data engineers to perform various data management tasks, such as provisioning a new data volume, near-instantaneously cloning a data volume, and near-instantaneously snapshotting a data volume for traceability/baselining. This Python library can function as either a command line utility or a library of functions that can be imported into any Python program or Jupyter Notebook.<br><br>Refer to the documentation for a full list of available functionality.
