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TRNRun is a tool for running TRNSYS simulations, designed to make batch runs easy to automate, monitor, and orchestrate from Python, MATLAB, .NET, or the command line.

TRNRun Runner	Terminal Display	GUI
TRNRUN_Runner.mp4	TRNRUN_Python.mp4	TRNRUN_GUI.mp4

Components

Component	Role
TRNRun Runner	Runs and monitors one deck, emitting JSON Lines events.
TRNRun Daemon	Queues and tracks simulations for one client over a JSON pipe.
Type3830	Reports simulation progress for monitoring and stall detection.

Libraries

Library	Release	Compatibility	Install
Python			pip install trnrun or uv add trnrun
.NET			dotnet add package TRNRun
MATLAB			.mltbx from GitHub Releases

Each library runs concurrent simulation batches through the bundled daemon.

Requirements

• Windows x64
• TRNSYS 17 or 18
• Optional: the Type3830 Progress Tracker in each deck for progress reporting

Quick start

Python

from trnrun import SimulationManager

with SimulationManager(workers=1) as manager:
    simulation = manager.add(r"C:\path\to\deck.dck", keep_awake=True)
    manager.wait(simulation)

See the Python documentation for more details.

MATLAB

import trnrun.*
manager = SimulationManager(workers=1);

simulation = manager.add("C:\path\to\deck.dck", ...
    SimulationSettings(keepAwake=true), waitFor="FINISHED");

See the MATLAB documentation for more details.

.NET

using TRNRun;

await using TRNRunDaemon daemon = await TRNRunDaemon.StartAsync(workers: 1);
long simId = await daemon.AddAsync(@"C:\path\to\deck.dck", new SimulationSettings { KeepAwake = true });
Simulation simulation = await daemon.WaitForFinishedAsync(simId);

See the .NET documentation for more details.

License

TRNRun is available under the MIT License.