API Reference#

This is the complete API reference for OpenSTEF. The API is organized into several packages:

Core Package

Core data structures, datasets, and utilities

Models Package

Machine learning models and feature engineering

BEAM Package

Backtesting, evaluation, analysis and metrics for forecasting models

Meta Package

Ensemble forecasting and preset workflows

Core Package (`openstef_core`)#

`datasets`	Time series datasets and versioned data access.
`utils`	Utility functions and helpers for OpenSTEF core functionality.
`base_model`	Configuration utilities for OpenSTEF Beam.
`exceptions`	Custom exceptions for OpenSTEF core functionality.
`mixins`	Core mixins for building reusable components.
`testing`	Testing utilities for comparing pandas objects.
`transforms`	Data transformation utilities for time series processing.
`types`	Core type definitions for OpenSTEF time series analysis.

`models`	Model implementations and model interfaces for OpenSTEF.
`workflows`	Pipeline orchestrations for OpenSTEF.
`presets`	Forecasting workflow presets package.
`explainability`	Explainability utilities for OpenSTEF.
`mixins`	Model-related mixins for machine learning workflows.
`integrations`	Integration components for extending OpenSTEF functionality.
`transforms`	Feature engineering utilities for OpenSTEF.
`utils`	Utility functions and modules for OpenSTEF model implementations.

`metrics`	Metrics for measuring how well energy forecasting models perform.
`backtesting`	Tests forecasting models by simulating how they would perform in real operations.
`analysis`	Turns evaluation results into visualizations and reports for decision making.
`evaluation`	Organizes forecasting results into structured performance reports.
`benchmarking`	Runs complete model comparison studies across multiple forecasting targets.

`models`	Meta Forecasting models.
`presets`	Package for preset forecasting workflows.
`utils`	Utility functions and classes for OpenSTEF Meta.