PyEarthTools is a Python framework, containing modules for loading data; pre-processing, normalising and standardising data; defining machine learning (ML) models; training ML models; performing inference with ML models; and evaluating ML models. It contains specialised support for weather and climate data sources and models. It has an emphasis on reproducibility, shareable pipelines, and human-readable low-code pipeline definition.

<-- we are working towards 100% test coverage of PyEarthTools code

We have information for:

• New user guides and introduction to the concepts in PyEarthTools
• Installation instructions for different usage scenarios
• Data catalogue setup for facility managers or individuals to establish their research data catalogue
• A shiny tutorial gallery full of neat examples
• Much more, including how-to guides, project setup guide, information on accessing data, guides to evaluation, orientiation for physical scientists and data scientists at our documentation homepage (you may be reading this now or you may be visiting the README from elsewhere)