polar-high 1.2.0

Python library for building indexed linear and mixed-integer programs in polars; assembles into HiGHS, exportable as MPS.

polar-high

A Python library for building and solving large linear and mixed-integer optimisation programs, i.e. domain specific language (DSL) for algebraic modelling. Variables and parameters are polars DataFrames, expressions are joined and grouped lazily, and the matrix is assembled directly through HiGHS — or exported as MPS for any other LP/MIP solver. The kernel is intentionally domain-free: it has no opinions about energy systems, supply chains, or any specific application.

Install

pip install polar-high

Requires Python 3.11+. HiGHS ships in highspy, no separate install.

Quickstart

A tiny dispatch LP — wind + coal over three hours, minimise cost subject to capacity and per-hour demand.

--8<-- "tests/fixtures/quickstart_example.py:model"

Documentation

Full docs at https://nodal-tools.fi/polar-high/ — published with MkDocs + mike for per-version reads.

• Concepts — the indexed-frame mental model (Var, Param, Sum, Where, Lag, broadcasting/join semantics).
• Guide — warm-starting, Lagrangian decomposition, performance tuning, debugging.
• API reference — autogenerated from docstrings.
• Compare — how polar-high relates to Pyomo, JuMP, gurobipy, linopy, and GNU MathProg.

Build locally: pip install -e ".[docs]" && mkdocs serve.

Used by

polar-high is the build engine behind the FlexTool energy-system modelling toolkit (still in dev branch only, 7.5.2026 situation). FlexTool's fleet of system tests (from earlier GNU MathProg to HiGHS implementation) has been used to test polar-high in real modelling use cases. In addition polar-high kernel has its own set of unit and system tests.

Created by

polar-high was created by Juha Kiviluoma of Nodal-Tools using Claude Opus.

License

Apache-2.0 — see LICENSE and NOTICE. Changelog: CHANGELOG.md.