bngsim

Embeddable simulation engine for biochemical reaction networks.

bngsim is a high-performance C++ simulation kernel with Python bindings that replaces BioNetGen's subprocess-based run_network driver. The library also includes two network-free simulators. It loads BioNetGen .net and .xml files, runs deterministic and stochastic simulations in-process, and returns results as NumPy arrays — no file I/O, no subprocess spawning, no Perl dependency.

Highlights

Fast — in-process execution with the GIL released during simulation; thread-parallel batch sweeps
No toolchain at runtime — import bngsim; no compilers, no BNGPATH, no Perl
Modern SUNDIALS — v7.x CVODE/CVODES with re-entrant SUNContext
Multi-format — loads BioNetGen .net and .xml, Antimony (.ant), and SBML (.xml) models SBML Test Suite results, plus rule-based BNGL (.bngl) via BNG2.pl with bngsim[bngl]
Rich results — NumPy arrays, named observable access, pandas/xarray, HDF5 save/load
Standards interchange — .net/cBNGL ⇄ SBML and SED-ML + OMEX packaging, every conversion verified faithful
Gradient-ready — CVODES forward sensitivities, Fisher information
Validated — matches run_network to ~10⁻¹² (ODE) and cross-checked against RoadRunner and the SBML semantic test suite

Installation

pip install bngsim

Prebuilt wheels ship for common platforms; large models may benefit from the optional sparse (KLU) solver. See the installation guide for source builds, the KLU dependency, and optional extras.

Quickstart

import bngsim

# Load a model (BioNetGen .net/.xml, Antimony, or SBML) and run an ODE simulation
model = bngsim.Model.from_net("model.net")
sim = bngsim.Simulator(model, method="ode")
result = sim.run(t_span=(0.0, 100.0), n_points=1001)

result.time               # (1001,) NumPy array of time points
result.observables["A"]   # trajectory of observable "A"
result.dataframe          # pandas DataFrame of time + all observables

Other formats load through the sibling constructors — Model.from_sbml, Model.from_antimony, and their *_string variants.

Stochastic (method="ssa" / "psa"), network-free (NFsim / RuleMonkey), sensitivity analysis, steady-state, and events are all covered in the quickstart and user guide.

Documentation

Full documentation is hosted at bngsim.readthedocs.io and lives in docs/:

Installation · Quickstart
User guide — loading models, simulation, network-free, results, events, sensitivities, steady state, compiled RHS and its artifact cache, SBML/SED-ML/OMEX interchange
Reference — API · expression language
Architecture · benchmarks & validation

The package ships one console script, bngsim-cache (equivalently python -m bngsim.cache): it reports on and prunes the compiled-artifact cache that codegen fills, which nothing empties on its own. See managing the artifact cache.

Benchmarks & validation

bngsim beats run_network on every SSA/PSA model measured (geometric-mean speedup ~8.7× SSA), agrees with libRoadRunner across the full BioModels ODE corpus, and scores 1577 Match on the SBML semantic test suite with zero wrong-but-plausible answers. The numbers, methodology, and reproducible harnesses are in benchmarks & validation, with the committed cross-engine snapshots under parity_checks/. To re-run the suites and reproduce the numbers — the pinned-fetch model, corpus provenance, tool versions, and a no-download smoke path — see REPRODUCING.md. The supported-construct matrix is in SUPPORT_MATRIX.md.

Contributing

Build-from-source, test, and CI instructions are in CONTRIBUTING.md and the development docs. Release history is in CHANGELOG.md.

License

MIT. See LICENSE for the full text and the Triad/LANL copyright notice.

Third-party code and model/test-data corpora that BNGsim redistributes are listed, with their licenses, in NOTICE.

Citation

If you use bngsim in your research, please cite:

Preprint coming soon!

Acknowledgments

BNGsim was developed and validated against RoadRunner, AMICI, COPASI, BioNetGen, and the SBML/DSMTS test suites. See ACKNOWLEDGMENTS.md for citations.

Metadata

Release files for bngsim 0.16.0

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

Source distribution (sdist)

Source distribution for bngsim 0.16.0
File	Size	Uploaded
bngsim-0.16.0.tar.gz	7.6 MB	Sep 22, 2026	Details

Built distributions (wheels)

Table of built distributions (wheels) for bngsim 0.16.0
File	Interpreter	ABI	Platform	Reset
bngsim-0.16.0-cp313-cp313-win_amd64.whl 4.3 MB Sep 22, 2026	CPython 3.13	CPython 3.13	Windows x86-64	Details
bngsim-0.16.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl 5.4 MB Sep 22, 2026	CPython 3.13	CPython 3.13	Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64	Details
bngsim-0.16.0-cp313-cp313-macosx_11_0_arm64.whl 3.7 MB Sep 22, 2026	CPython 3.13	CPython 3.13	macOS 11.0+ ARM64	Details
bngsim-0.16.0-cp313-cp313-macosx_10_15_x86_64.whl 4.0 MB Sep 22, 2026	CPython 3.13	CPython 3.13	macOS 10.15+ x86-64	Details
bngsim-0.16.0-cp312-cp312-win_amd64.whl 4.3 MB Sep 22, 2026	CPython 3.12	CPython 3.12	Windows x86-64	Details
bngsim-0.16.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl 5.4 MB Sep 22, 2026	CPython 3.12	CPython 3.12	Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64	Details
bngsim-0.16.0-cp312-cp312-macosx_11_0_arm64.whl 3.7 MB Sep 22, 2026	CPython 3.12	CPython 3.12	macOS 11.0+ ARM64	Details
bngsim-0.16.0-cp312-cp312-macosx_10_15_x86_64.whl 4.0 MB Sep 22, 2026	CPython 3.12	CPython 3.12	macOS 10.15+ x86-64	Details
bngsim-0.16.0-cp311-cp311-win_amd64.whl 4.3 MB Sep 22, 2026	CPython 3.11	CPython 3.11	Windows x86-64	Details
bngsim-0.16.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl 5.4 MB Sep 22, 2026	CPython 3.11	CPython 3.11	Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64	Details
bngsim-0.16.0-cp311-cp311-macosx_11_0_arm64.whl 3.7 MB Sep 22, 2026	CPython 3.11	CPython 3.11	macOS 11.0+ ARM64	Details
bngsim-0.16.0-cp311-cp311-macosx_10_15_x86_64.whl 4.0 MB Sep 22, 2026	CPython 3.11	CPython 3.11	macOS 10.15+ x86-64	Details
bngsim-0.16.0-cp310-cp310-win_amd64.whl 4.3 MB Sep 22, 2026	CPython 3.10	CPython 3.10	Windows x86-64	Details
bngsim-0.16.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl 5.4 MB Sep 22, 2026	CPython 3.10	CPython 3.10	Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64	Details
bngsim-0.16.0-cp310-cp310-macosx_11_0_arm64.whl 3.7 MB Sep 22, 2026	CPython 3.10	CPython 3.10	macOS 11.0+ ARM64	Details
bngsim-0.16.0-cp310-cp310-macosx_10_15_x86_64.whl 4.0 MB Sep 22, 2026	CPython 3.10	CPython 3.10	macOS 10.15+ x86-64	Details

Total release size: 76.8 MB

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Size	3.7 MB
Tags	CPython 3.11 macOS 11.0+ ARM64
SHA-256 checksum How to use checksums	`00b0d321e54b34a3fac537b140e81c5f53d038213472eb688ce91ae882ee0741`
BLAKE2b-256 checksum How to use checksums	`d65e2c5e45316001256997e1bdc3f4a7efca0773445bace4095832be36229abb`
Upload date	Sep 22, 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/lanl/bngsim
Publishing commit: github.com/lanl/bngsim/tree/34870703177c3c5b8d452d9eeab3cc211b1099fc

Workflow

Publishing configuration: github.com/lanl/bngsim/blob/34870703177c3c5b8d452d9eeab3cc211b1099fc/.github/workflows/release.yml
Publishing logs: github.com/lanl/bngsim/actions/runs/35671324259/attempts/1

Artifact

Subject: bngsim-0.16.0-cp311-cp311-macosx_11_0_arm64.whl
SHA-256 checksum: 00b0d321e54b34a3fac537b140e81c5f53d038213472eb688ce91ae882ee0741 Verifying attestations

Release files / bngsim-0.16.0-cp311-cp311-macosx_10_15_x86_64.whl

Download URL	bngsim-0.16.0-cp311-cp311-macosx_10_15_x86_64.whl
Size	4.0 MB
Tags	CPython 3.11 macOS 10.15+ x86-64
SHA-256 checksum How to use checksums	`330ca069c4107600c6e9c694e270985bc7bc07d7214e5fbd01c4eab7b7a2a7d9`
BLAKE2b-256 checksum How to use checksums	`61ef42a263c895bd007a3613e615e3b76963598172a7b417bedd75d69afd690e`
Upload date	Sep 22, 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/lanl/bngsim
Publishing commit: github.com/lanl/bngsim/tree/34870703177c3c5b8d452d9eeab3cc211b1099fc

Workflow

Publishing configuration: github.com/lanl/bngsim/blob/34870703177c3c5b8d452d9eeab3cc211b1099fc/.github/workflows/release.yml
Publishing logs: github.com/lanl/bngsim/actions/runs/35671324259/attempts/1

Artifact

Subject: bngsim-0.16.0-cp311-cp311-macosx_10_15_x86_64.whl
SHA-256 checksum: 330ca069c4107600c6e9c694e270985bc7bc07d7214e5fbd01c4eab7b7a2a7d9 Verifying attestations

Release files / bngsim-0.16.0-cp310-cp310-win_amd64.whl

Download URL	bngsim-0.16.0-cp310-cp310-win_amd64.whl
Size	4.3 MB
Tags	CPython 3.10 Windows x86-64
SHA-256 checksum How to use checksums	`3b533710a8bb6d5a107151566d75ab04ab7b796485911991d6763a6acf82a0cc`
BLAKE2b-256 checksum How to use checksums	`3ff6fabd498e71bea9de1d00bed031b1fef8ab405df4c76dfd0a7a6b3e27c03b`
Upload date	Sep 22, 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/lanl/bngsim
Publishing commit: github.com/lanl/bngsim/tree/34870703177c3c5b8d452d9eeab3cc211b1099fc

Workflow

Publishing configuration: github.com/lanl/bngsim/blob/34870703177c3c5b8d452d9eeab3cc211b1099fc/.github/workflows/release.yml
Publishing logs: github.com/lanl/bngsim/actions/runs/35671324259/attempts/1

Artifact

Subject: bngsim-0.16.0-cp310-cp310-win_amd64.whl
SHA-256 checksum: 3b533710a8bb6d5a107151566d75ab04ab7b796485911991d6763a6acf82a0cc Verifying attestations

Release files / bngsim-0.16.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl

Download URL	bngsim-0.16.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Size	5.4 MB
Tags	CPython 3.10 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum How to use checksums	`788fbfa86f79852722f0ada67243afdf3567fad7b934bdfe9ee30c63273aadbc`
BLAKE2b-256 checksum How to use checksums	`68b7eaf672afc294d674d1fe0c5cbf907e7c02b929286ee9f6b2ac68528e9cd2`
Upload date	Sep 22, 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/lanl/bngsim
Publishing commit: github.com/lanl/bngsim/tree/34870703177c3c5b8d452d9eeab3cc211b1099fc

Workflow

Publishing configuration: github.com/lanl/bngsim/blob/34870703177c3c5b8d452d9eeab3cc211b1099fc/.github/workflows/release.yml
Publishing logs: github.com/lanl/bngsim/actions/runs/35671324259/attempts/1

Artifact

Subject: bngsim-0.16.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
SHA-256 checksum: 788fbfa86f79852722f0ada67243afdf3567fad7b934bdfe9ee30c63273aadbc Verifying attestations

Release files / bngsim-0.16.0-cp310-cp310-macosx_11_0_arm64.whl

Download URL	bngsim-0.16.0-cp310-cp310-macosx_11_0_arm64.whl
Size	3.7 MB
Tags	CPython 3.10 macOS 11.0+ ARM64
SHA-256 checksum How to use checksums	`a07d05c0226f0b4734fc3555350c7b60d3a36ea19284817f82ca088dfd9f24d1`
BLAKE2b-256 checksum How to use checksums	`5198638faeaec5f7871b92ef1ef388e491603e1fac7fbf05c35fd4545c77bc2a`
Upload date	Sep 22, 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/lanl/bngsim
Publishing commit: github.com/lanl/bngsim/tree/34870703177c3c5b8d452d9eeab3cc211b1099fc

Workflow

Publishing configuration: github.com/lanl/bngsim/blob/34870703177c3c5b8d452d9eeab3cc211b1099fc/.github/workflows/release.yml
Publishing logs: github.com/lanl/bngsim/actions/runs/35671324259/attempts/1

Artifact

Subject: bngsim-0.16.0-cp310-cp310-macosx_11_0_arm64.whl
SHA-256 checksum: a07d05c0226f0b4734fc3555350c7b60d3a36ea19284817f82ca088dfd9f24d1 Verifying attestations

Release files / bngsim-0.16.0-cp310-cp310-macosx_10_15_x86_64.whl

Download URL	bngsim-0.16.0-cp310-cp310-macosx_10_15_x86_64.whl
Size	4.0 MB
Tags	CPython 3.10 macOS 10.15+ x86-64
SHA-256 checksum How to use checksums	`d7e6ff8701621d0ff1c10439590ada59b8fe948198f532a1129257f81b948f50`
BLAKE2b-256 checksum How to use checksums	`8034d8cc47b3342c24a94988717eca236ecef57ebe4c69a6ca7ecbd6d8493d88`
Upload date	Sep 22, 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/lanl/bngsim
Publishing commit: github.com/lanl/bngsim/tree/34870703177c3c5b8d452d9eeab3cc211b1099fc

Workflow

Publishing configuration: github.com/lanl/bngsim/blob/34870703177c3c5b8d452d9eeab3cc211b1099fc/.github/workflows/release.yml
Publishing logs: github.com/lanl/bngsim/actions/runs/35671324259/attempts/1

Artifact

Subject: bngsim-0.16.0-cp310-cp310-macosx_10_15_x86_64.whl
SHA-256 checksum: d7e6ff8701621d0ff1c10439590ada59b8fe948198f532a1129257f81b948f50 Verifying attestations