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the Platform for Automated Workflows by SSRL

Project description

Introduction

paws stands for the Platform for Automated Workflows by SSRL. It was conceived to serve as a lean and modular workflow manager for scientific data.

paws interfaces with an ever-growing number of packages and provides for users to add their own Operations, by writing isolated Python modules following a simple template.

The essential ingredients of paws are Operations, Workflows, and Plugins. A paws Operation is meant to take some inputs and produce some outputs- it is essentially a function, wrapped in a class, wrapped in a Python module. The class and module layers are used for certain conveniences in the implementation of paws Workflows. A paws Plugin is an object that should persist over time to repeatedly execute one or more activities, for example to monitor an experimental apparatus, or to expose functionalities of a complex object for Operations to use. A paws Workflow contains the logic necessary for stitching together Operations and Plugins, and despite the distinction in name, it implements the same interface as an Operation.

Disclaimer: paws is neither the first nor the most sophisticated way to build and manage data processing workflows. Its development was driven by a need for modularity and extensibility, for rapid development and deployment of stand-alone applications for a wide variety of experimental control and data processing tasks.

Documentation

The documentation for paws is hosted by readthedocs.org: http://paws.readthedocs.io/en/latest/. This documentation is continually under development. Please contact the developers at paws-developers@slac.stanford.edu if the documentation fails to answer your questions.

API Examples

The following are examples that explore the capabilities of the paws API.

TODO: write new examples

Installation

NOTE: all deployments are currently outdated or under heavy development. Please contact the development team if you are interested in this package.

paws is available on PyPI and Anaconda. Deployments to PyPI are performed regularly. Currently, we only deploy relatively stable versions to Anaconda.

To install from PyPI, invoke pip: pip install pypaws.

To install from Anaconda, use conda: conda install -c ssrl-paws pypaws

All of the dependencies of the paws Operations are not necessarily declared as dependencies of paws. This keeps the Python environment relatively lean and avoids obnoxious installation overhead, but it means that users will have to prepare their environments for the Operations they want to use.

The documentation of paws includes instructions for installing the dependencies of each Operation. NOTE: this is currently false.

Attribution

paws was written at SSRL by Chris Tassone’s research group. If you use paws in your published research, a citation would be appreciated.

Before citing paws, it is of primary importance that you cite the authors of the original work that produced your results: this is almost certainly separate from the authors of paws. Citations for your specific Operations should be found in the paws documentation. If you have trouble finding proper citations, please contact us at paws-developers@slac.stanford.edu, and we will do our best to help.

Contribution

Contribution to paws is encouraged and appreciated. Get in touch with the paws development team at paws-developers@slac.stanford.edu. If you are able to develop without assistance, feel free to submit a pull request against the dev branch at https://github.com/slaclab/paws.

License

The 3-clause BSD-like license attached to this software can be found in the LICENSE file in the source code root directory.

Project details


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