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sbmlsim: SBML simulation made easy

sbmlsim is a collection of python utilities for the simulation of models in the Systems Biology Markup Language (SBML), built on libroadrunner.

Features include

timecourse simulations — concatenated timecourses with changes of parameters and initial conditions, in the units of the model
parameter scans — simulations over the dimensions of parameter changes, with results as labeled N-dimensional arrays (xarray)
simulation experiments — models, datasets, simulations, tasks and figures of an experiment as one reproducible python object, with HTML and markdown reports
parameter fitting — optimization problems from experimental data with local and global optimizers, and PEtab archives
sensitivity analysis — local sensitivities and the global Morris, Sobol and FAST methods

The documentation is available at https://matthiaskoenig.github.io/sbmlsim.

If you have any questions or issues please open an issue.

How to cite

If you use sbmlsim please cite the archived software on Zenodo:

König, M. (2026). sbmlsim: SBML simulation made easy (Version 0.6.0) [Computer software]. Zenodo. https://zenodo.org/badge/latestdoi/55952847

@software{konig_sbmlsim,
  author    = {König, Matthias},
  title     = {sbmlsim: SBML simulation made easy},
  year      = {2026},
  month     = sep,
  version   = {0.6.0},
  publisher = {Zenodo},
  url       = {https://zenodo.org/badge/latestdoi/55952847},
}

License

Source Code: MIT
Documentation: CC BY-SA 4.0

Funding

Matthias König is supported by the German Research Foundation (DFG) within the Research Unit Programme FOR 5151 "QuaLiPerF (Quantifying Liver Perfusion-Function Relationship in Complex Resection - A Systems Medicine Approach)" by grant number 436883643 and by grant number 465194077 (Priority Programme SPP 2311, Subproject SimLivA).

Matthias König was supported by the Federal Ministry of Education and Research (BMBF, Germany) within the research network Systems Medicine of the Liver (LiSyM, grant number 031L0054). Matthias König has received funding from the EOSCsecretariat.eu which has received funding from the European Union's Horizon Programme call H2020-INFRAEOSC-05-2018-2019, grant Agreement number 831644.

Metadata

Release files for sbmlsim 0.6.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for sbmlsim 0.6.1
File	Size	Uploaded
sbmlsim-0.6.1.tar.gz	809.4 kB	Sep 10, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for sbmlsim 0.6.1
File	Interpreter	ABI	Platform	Reset
sbmlsim-0.6.1-py3-none-any.whl 262.9 kB Sep 10, 2026	Python 3	none	any	Details

Total release size: 1.1 MB

Release files / sbmlsim-0.6.1.tar.gz

Download URL	sbmlsim-0.6.1.tar.gz
Size	809.4 kB
Tags	Source
SHA-256 checksum How to use checksums	`0cf4c56c4f1ed0bf11efe9463f904275cf06547df329f5c7221406047c424ed0`
BLAKE2b-256 checksum How to use checksums	`658e030a1722ffb1c67edb28c0cb23e6017e29b48fd09874c804aea8681346e7`
Upload date	Sep 10, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/matthiaskoenig/sbmlsim
Publishing commit: github.com/matthiaskoenig/sbmlsim/tree/7cd64c1f3572af2c9e667dbe29c628dbbbb79cdf

Workflow

Publishing configuration: github.com/matthiaskoenig/sbmlsim/blob/7cd64c1f3572af2c9e667dbe29c628dbbbb79cdf/.github/workflows/ci-cd.yml
Publishing logs: github.com/matthiaskoenig/sbmlsim/actions/runs/34423908540/attempts/1

Artifact

Subject: sbmlsim-0.6.1.tar.gz
SHA-256 checksum: 0cf4c56c4f1ed0bf11efe9463f904275cf06547df329f5c7221406047c424ed0 Verifying attestations

Release files / sbmlsim-0.6.1-py3-none-any.whl

Download URL	sbmlsim-0.6.1-py3-none-any.whl
Size	262.9 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`f1e3c1db5b635dc844f1e84d1c477172c4a88f8bf70c879283f7ace31bec49fb`
BLAKE2b-256 checksum How to use checksums	`1ea398799846dd070a69de1e38d288c46a7772d2b5be39472c5cd3e2efb0a28f`
Upload date	Sep 10, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/matthiaskoenig/sbmlsim
Publishing commit: github.com/matthiaskoenig/sbmlsim/tree/7cd64c1f3572af2c9e667dbe29c628dbbbb79cdf

Workflow

Publishing configuration: github.com/matthiaskoenig/sbmlsim/blob/7cd64c1f3572af2c9e667dbe29c628dbbbb79cdf/.github/workflows/ci-cd.yml
Publishing logs: github.com/matthiaskoenig/sbmlsim/actions/runs/34423908540/attempts/1

Artifact

Subject: sbmlsim-0.6.1-py3-none-any.whl
SHA-256 checksum: f1e3c1db5b635dc844f1e84d1c477172c4a88f8bf70c879283f7ace31bec49fb Verifying attestations