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Alpaca is a Python package for the capture of provenance information during the execution of Python scripts that process data.

Project description

alpaca

Automated Lightweight Provenance Capture

tests Documentation Status

Alpaca is a Python package for the capture of provenance information during the execution of Python scripts that process data.

Alpaca provides a simple API for recording the details of the functions being executed, the data flow, and a description of parameters used. This is accomplished with minimal code instrumentation and user intervention.

Provenance information is structured and serialized according to a model based on the W3C PROV format.

Table of contents

Prerequisites

Requirements

Alpaca requires Python 3.8 or higher and the packages specified in requirements.txt.

Installation

Use the package manager pip to install Alpaca.

Package on pypi

pip install alpaca-prov

More detailed instructions on how to setup conda environments and additional install options can be checked in the Installation page.

Documentation

See https://alpaca-prov.readthedocs.io/en/latest/.

How to run

Examples showing how to use Alpaca can be found in the examples folder. Detailed instructions on how to set up and run are here.

Colaborators

All the contributors to the development of Alpaca can be found in the Authors and contributors page.

How to contribute

If you want to suggest new features, changes, or make a contribution, please first open an issue on the project page on GitHub to discuss your idea.

Pull requests are welcome. Any contribution should also be covered by appropriate unit tests in the tests folder.

Get support

If you experience any issue or wish to report a bug, please open an issue on the project page on GitHub.

Acknowledgments

See acknowledgments.

License

BSD 3-Clause License, see LICENSE.txt for details.

Copyright

:copyright: 2022-2023, Forschungszentrum Jülich GmbH, INM-6, IAS-6. All rights reserved.

Project details


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Source Distribution

alpaca-prov-0.2.0.tar.gz (1.2 MB view hashes)

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