Updated 14/02/2024
Core DTE Modules

PyOphidia

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Description

Providing the Python bindings for Ophidia, a High-Performance Data Analytics framework

PyOphidia provides the Python bindings for Ophidia, a High-Performance Data Analytics framework. PyOphidia provides the Python bindings for the Ophidia framework, an open-source solution for the analysis of scientific multi-dimensional data, joining HPC paradigms and Big Data approaches. It provides an environment targeting High Performance Data Analytics through parallel and in-memory data processing, data-driven task scheduling and server-side analysis. The framework supports the execution of complex analytics workflows in the form of DAGs of Ophidia operators. The PyOphidia module brings HPDA capabilities within the scientific Python ecosystem through a high-level interface that allows handling distributed datasets, running parallel analysis and interacting with High Performance Computing (HPC) infrastructures.

 

Target Audience
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  • Digital Twin Developers
  • Data Scientists
License
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GPLv3

Created by
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Release Notes

The latest release of the Ophidia framework components, and in particular the Ophidia server and PyOphidia, includes all the extensions developed within the project. These extensions cover two main features: support for Common Workflow Language (CWL) based workflows and provenance tracking.

For the former development, stronger integration of Ophidia workflows written in CWL within the PyOphidia modules has been achieved. Now CWL-based workflows can be directly imported through a method in the Python module and handled similarly to workflows written in the native Ophidia JSON-based format.

Concerning the latter, the support for tracking and generating provenance documents of workflows has been introduced in Ophidia. In particular, the Ophidia server has been extended to track and send back to the client modules additional information related to task execution. On the client side, PyOphidia has been extended with the capabilities: (i) to collect the information concerning the workflow execution at runtime, and (ii) to generate related provenance documents compliant with the W3C PROV standard.

Moreover, the capabilities for validating the workflow structure have also been improved and fully integrated into the related PyOphidia modules.

Besides code developments, notebooks with usage examples of the new features have been included in the PyOphidia package. The documentation is also being updated to describe the latest capabilities introduced (see table above).

Future Plans

The focus will be on the integration of Ophidia/PyOphidia with DT applications from WP4, for example, those concerning climate-related extreme events. For example, the capabilities for handling CWL/JSON workflows will be further enhanced to better address requirements from the use cases. Moreover, integration with SQAaaS for the validation of Ophidia workflow syntax is envisioned.