PySquonk

Python client for Squonk REST API

PySquonk is a Python 3 client that wraps the Squonk JobExecutor REST API, making it simple to execute Squonk services from Python. This project was started at the Diamond Light Source and then transferred to the implementation challenge where the initial implementation was completed. The software is available as a Python module from the PyPi repository at https://pypi.org/project/im-pysquonk/ with the source code and documentation in GitHub at https://github.com/InformaticsMatters/pysquonk

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For developers

Type:

Software

Categories:

Processing and analysis

Applicability domain:

Computational modelling

Topic:

Chemical properties, Predictive modelling

Targeted industry:

Drugs

Targeted users:

Software Developers

Relevant OpenRiskNet case studies:

DataCure - Data curation and creation of pre-reasoned datasets and searching
MetaP - Metabolism Prediction
ModelRX - Modelling for Prediction or Read Across

Provided by:

Informatics Matters

Technology readiness level:

TRL 3 – experimental proof of concept

Integration status:

Integrated application

Service integration operations completed:

Utilises the OpenRiskNet APIs to ensure that each service is accessible to our proposed interoperability layer.

Is annotated according to the semantic interoperability layer concept using defined ontologies.

Is containerised for easy deployment in virtual environments of OpenRiskNet instances.

Has documented scientific and technical background.

Is deployed into the OpenRiskNet reference environment.

Is listed in the OpenRiskNet discovery services.

Is listed in other central repositories like eInfraCentral, bio.tools and TeSS (ELIXIR).

Provides legal and ethical statements on how the service can be used.