OpenPinch
OpenPinch is an open-source Python toolkit for advanced Pinch Analysis and Total Site Integration. It supports direct and indirect heat integration targeting, graph interpretation, Heat Pump and refrigeration screening, exergy and cogeneration post-processing, heat exchanger network synthesis, multi-period analysis, stream piece-wise linearisation (for variable heat capacity and phase change streams), and file-backed or schema-first workflows.
Full documentation is available at https://openpinch.readthedocs.io/en/latest/.
Install
Install the base package for validation, targeting, summaries, and schema-first Python workflows:
python -m pip install openpinch
Install optional extras only for the workflows that need them:
python -m pip install "openpinch[notebook]" # Jupyter, Plotly graphs, Excel I/O
python -m pip install "openpinch[dashboard]" # Streamlit dashboard
python -m pip install "openpinch[synthesis]" # HEN synthesis, then run: idaes get-extensions
python -m pip install "openpinch[brayton_cycle]" # TESPy-backed Brayton-cycle tooling
python -m pip install "openpinch[tespy]" # TESPy HPR targeting and performance maps
python -m pip install "openpinch[full]" # all optional surfaces, including synthesis
OpenPinch supports Python 3.12, 3.13 and 3.14 (>=3.12); development uses
the version in .python-version.
Both synthesis and full install the IDAES/Pyomo synthesis stack. Complete
the IDAES installation before running solver-backed workflows:
idaes get-extensions
First Solve
OpenPinch exposes two package-root workflow classes. Use PinchProblem for one
case and PinchWorkspace for named cases and scenarios.
from OpenPinch import PinchProblem
problem = PinchProblem(
{
"streams": [
{
"name": "Hot feed",
"zone": "Process",
"t_supply": 180.0,
"t_target": 80.0,
"heat_flow": 1000.0,
},
{
"name": "Cold feed",
"zone": "Process",
"t_supply": 20.0,
"t_target": 120.0,
"heat_flow": 800.0,
},
],
"utilities": [],
},
project_name="First solve",
)
problem.validate()
problem.target.all_heat_integration()
print(problem.summary_frame())
Analysis is explicit: named methods execute work, while summaries, reports, plots, and exports consume prepared or cached state.
Packaged Resources
OpenPinch ships maintained sample cases and notebook workflows. The resource helpers below are useful repository tooling, but are not compatibility protected:
from OpenPinch.resources import (
list_notebooks,
list_sample_cases,
notebook_metadata,
sample_case_metadata,
)
print(list_sample_cases())
print(sample_case_metadata("basic_pinch.json").description)
print(list_notebooks())
print(notebook_metadata("01_first_solve_and_core_curves.ipynb").title)
Copy the notebook series from the CLI:
openpinch notebook -o notebooks
Notebooks and sample cases live in OpenPinch/tutorials/notebooks and
OpenPinch/tutorials/sample_cases, with discovery and copying available through
OpenPinch.resources.
The nineteen-notebook series progresses from first solve through multiperiod HPR, cogeneration, HEN synthesis, and publication workflows.
The CLI intentionally copies notebooks only. Solves, validation, graph export, Excel export, dashboards, and advanced targeting happen through Python.
Documentation Map
- Getting started: https://openpinch.readthedocs.io/en/latest/getting-started.html
- Workflow choice: https://openpinch.readthedocs.io/en/latest/overview/workflow-map.html
- Guides: https://openpinch.readthedocs.io/en/latest/guides/index.html
- API reference: https://openpinch.readthedocs.io/en/latest/api/index.html
Testing
Run the same checks as CI on your own machine with one command:
scripts/ci_local.sh # lint, unit tests with 95% coverage, docs, build + wheel smoke test
scripts/ci_local.sh quick # lint + unit tests, stop at the first failure
scripts/ci_local.sh all # every lane, including TESPy, performance, solver and notebooks
scripts/ci_local.sh solver # any lane by name: lint unit docs tespy performance solver notebooks build
scripts/ci_local.sh --linux notebooks # run inside a Linux x86_64 container, like the CI runners (needs Docker)
CI runs on Linux x86_64. Numerical searches (for example the heat pump notebooks) can
behave slightly differently on macOS arm64, so use --linux to reproduce a CI-only failure;
on Apple silicon it runs under emulation and is slower.
It syncs the locked environment with uv first and prints a pass/fail summary per lane.
The solver lane downloads the IDAES solver binaries on first use.
To have this run automatically before every git push, enable the repository's
hooks once per clone (skip a run with git push --no-verify):
git config core.hooksPath .githooks
Before pushing work meant for main, also run scripts/ci_local.sh all, which adds the
TESPy, performance, solver and notebook lanes that CI runs for pull requests into main.
The script does not run every CI lane. CI also runs the Pyodide lane (the test suite
inside WebAssembly against the built wheel), the lowest-allowed-versions floors lane,
the Python 3.12 and 3.13 unit lanes, the wheel smoke tests of the optional surfaces
and other operating systems, and the dependency audit. To run a Pyodide shard, build
the wheel and run it under Node 22 (the shard paths and deselections are in
.github/workflows/ci.yml):
nvm use 22 && (cd scripts/pyodide && npm ci) && uv build --out-dir dist && node scripts/pyodide/run_tests.mjs dist/*.whl -q tests/domain
Ubuntu runs the complete CI suite. Windows and macOS install the generated
wheel and verify the core import, CLI, and packaged resources. Tests marked
solver require external solver binaries; CI installs the IDAES extensions
and runs them for pull requests into main and for every release.
Release Process
The first merge into develop after a release automatically bumps the patch
version (bump-version.yml); bump minor or major yourself with
uvx bump-my-version bump minor. Merge the develop → main pull request once
CI OK (main) is green. Every push to main runs the full CI suite; when the
version has no v<version> tag yet, release.yml publishes the wheel and sdist
that CI built to PyPI through the protected pypi environment, then creates
the tag and GitHub release. See
Releasing for details and recovery.
Build the documentation locally:
uv run scripts/build_docs.py
History and Citation
OpenPinch started in 2011 as an Excel workbook with macros. The Python implementation began in 2021 to make the workflows scriptable and testable.
In publications and forks, please cite and link the foundational article and this repository:
Timothy Gordon Walmsley, 2026. OpenPinch: An Open-Source Python Library for Advanced Pinch Analysis and Total Site Integration. Process Integration and Optimization for Sustainability. https://doi.org/10.1007/s41660-026-00729-6
Contributors
Founder: Tim Walmsley, University of Waikato
Stephen Burroughs, Benjamin Lincoln, Alex Geary, Harrison Whiting, Khang Tran, Roger Padulles, Jasper Walden, Caleb Archer
License
OpenPinch is released under the MIT License. See LICENSE for details.
3 maintainers
Metadata
3 maintainers
Release files for OpenPinch 0.7.2
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