A simple CLI for BioNetGen

This is a simple CLI and a library for BioNetGen modeling language. PyBioNetGen also includes a heavily updated version of Atomizer which allows for conversion of models written in Systems Biology Markup Language (SBML) into BioNetGen language (BNGL) format.

Please see the documentation to learn how to use PyBioNetGen.

Installation

You will need both python (3.7 and above) and perl installed. Once both are available you can use the following pip command to install the package

$ pip install bionetgen

Optional: in-process simulation with BNGsim

PyBioNetGen can optionally use BNGsim as an in-process simulation engine (ODE/SSA/NFsim, multi-format input). This is fully opt-in: if BNGsim is not installed, every simulation uses the existing subprocess BNG2.pl path and behavior is unchanged. BNGsim is never a required dependency.

BNGsim is a compiled extension and is not on PyPI yet, so pip install bionetgen[bngsim] will not resolve until it is published. To try it now, install a prebuilt wheel from the release assets (macOS / Python 3.12; build from source on other platforms). PyBioNetGen requires BNGsim 0.9.10 or newer. Set BIONETGEN_NO_BNGSIM=1 to force the legacy subprocess path even when BNGsim is installed. See the BNGsim documentation page for details.

Features

PyBioNetGen comes with a command line interface (CLI), based on cement framework, as well as a functional library that can be imported. The CLI can be used to run BNGL models, generate Jupyter notebooks and do rudimentary plotting.

The library side provides a simple BNGL model runner as well as a model object that can be manipulated and used to get libRoadRunner simulators for the model.

PyBioNetGen also includes a heavily updated version of Atomizer which allows for conversion of SBML models into BNGL format. Atomizer can also be used to automatically try to infer the internal structure of SBML species during the conversion, see here for more information. Please note that this version of Atomizer is the main supported version and the version distributed with BioNetGen will eventually be deprecated.

The model object requires a system call to BioNetGen so the initialization can be relatively costly, in case you would like to use it for parallel applications, use the libRoadRunner simulator instead, unless you are doing NFSim simulations.

Usage

Sample CLI usage

$ bionetgen -h # help on every subcommand
$ bionetgen run -h # help on run subcommand
$ bionetgen run -i mymodel.bngl -o output_folder # this runs the model in output_folder

Sample library usage

import bionetgen 

ret = bionetgen.run("/path/to/mymodel.bngl", out="/path/to/output/folder")
# out keyword is optional, if not given, 
# generated files will be deleted after running
res = ret.results['mymodel']
# res will be a numpy record array of your gdat results

model = bionetgen.bngmodel("/path/to/mymodel.bngl")
# model will be a python object that contains all model information
print(model.parameters) # this will print only the parameter block in BNGL format
print(model) # this will print the entire BNGL
model.parameters.k = 1 # setting parameter k to 1
with open("new_model.bngl", "w") as f:
    f.write(str(model)) # writes the changed model to new_model file

# this will give you a libRoadRunner instance of the model
librr_sim = model.setup_simulator()

You can find more tutorials here.

Environment Setup

The following demonstrates setting up and working with a development environment:

### create a virtualenv for development

$ make virtualenv

$ source env/bin/activate


### run bionetgen cli application

$ bionetgen --help


### run pytest / coverage

$ make test

Docker

Included is a basic Dockerfile for building and distributing BioNetGen CLI, and can be built with the included make helper:

$ make docker

$ docker run -it bionetgen --help

Publishing to PyPI

You can use make dist command to make the distribution and push to PyPI with

python -m twine upload dist/*

You'll need to have a PyPI API token created, see here for more information.

Release files for bionetgen 0.8.7

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

Source distribution (sdist)

Source distribution for bionetgen 0.8.7
File	Size	Uploaded
bionetgen-0.8.7.tar.gz	11.9 MB	Sep 4, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for bionetgen 0.8.7
File	Interpreter	ABI	Platform	Reset
bionetgen-0.8.7-py3-none-any.whl 12.0 MB Sep 4, 2026	Python 3	none	any	Details

Total release size: 23.9 MB

Release files / bionetgen-0.8.7.tar.gz

Download URL	bionetgen-0.8.7.tar.gz
Size	11.9 MB
Tags	Source
SHA-256 checksum How to use checksums	`4cb84c427948627b79032c34a10784b449667a17cabbe69ae23109f5ebde71f6`
BLAKE2b-256 checksum How to use checksums	`1c910c8785008f802d311d52b4fe9f8906b26b0c6a5d6af28d95e64706530a70`
Upload date	Sep 4, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.1.0 CPython/3.12.3`

Release files / bionetgen-0.8.7-py3-none-any.whl

Download URL	bionetgen-0.8.7-py3-none-any.whl
Size	12.0 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`95c6ff9cf2349dd20280dcd2388a723df72f2283783d0d233a780874ba3628a8`
BLAKE2b-256 checksum How to use checksums	`93c8309cd3f0ec83aae0316ebb20c521e5934c9dd393f87687c55ae332b221f3`
Upload date	Sep 4, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.1.0 CPython/3.12.3`