flixopt.tutorials ¶

Datasets and example systems for the flixopt tutorials and notebooks.

Two tiers, so every notebook is standalone after pip install flixopt - no need to clone the repository or copy files out of GitHub:

Synthetic data (notebooks 01-07) - generated on the fly from numpy/pandas, no files and no network. Access by name with :func:get_data; see :func:list_data.
Pre-built example systems (notebooks 08-09) - downloaded (and cached) from the project's GitHub releases with :func:load_example; see :func:list_examples. Needs pooch (pip install flixopt[tutorials]).

Functions:¶

list_examples() -> list[str]

Return the names of the example systems available via :func:load_example.

load_example(name: ExampleName) -> FlowSystem

Download (and cache) a pre-built example FlowSystem and return it.

Parameters:

Name	Type	Description	Default
`name`	`ExampleName`	One of :func:`list_examples` (e.g. `'district_heating'`).	required

Returns:

Type	Description
`FlowSystem`	The deserialised :class:`flixopt.FlowSystem`.

Raises:

Type	Description
`ValueError`	If `name` is not a known example.
`ModuleNotFoundError`	If `pooch` is not installed.

Note

The first call for a given example downloads the artefact from the project's GitHub releases; subsequent calls read it from the local cache.

get_data(name: DataName) -> dict

Return the synthetic tutorial dataset name as a dict of arrays.

Generated from numpy/pandas, so this works offline with no extra dependencies.

Parameters:

Name	Type	Description	Default
`name`	`DataName`	One of :func:`list_data` (e.g. `'heat_system'`).	required

Raises:

Type	Description
`ValueError`	If `name` is not a known dataset.

list_data() -> list[str]

Return the names accepted by :func:get_data.