SweetBean
A declarative programming language built in Python, designed for the synthesis of behavioral experiments. It allows researchers to specify experiments once and seamlessly compile them into a jsPsych experiment for conducting studies with human participants or text-based simulations with synthetic participants using large-language models.
Features
- Declarative language: Specify experiments once and compile them into a jsPsych experiment for conducting studies with human participants or text-based simulations with synthetic participants using large-language models.
- Python-based: SweetBean is built in Python, making it accessible and easy to use for researchers and educators.
Integrate with other packages
This package seamlessly integrates with other packages aimed at running online behavioral experiments:
- AutoRA: For closed loop research, automatic experiment deployment, participant recruitment, and data collection.
- SweetPea: For experimental design.
But it can also be used as a standalone product.
Installation
The package is available on PyPI and can be installed via pip:
pip install sweetbean
Compatibility
SweetBean is compatible with the following version of jsPsych:
- jsPsych:
7.x
Dependencies
Sweetbean has the following dependencies that need to be installed on your system:
- Python:
>=3.9, <4.0 - java
Other versions may work but are not officially supported. If you experience issues, please report them!
Python Dependencies
The following Python packages are required and will be installed automatically via pip:
jinja2transcryptpyppeteerpillow
jsPsych Plugins
SweetBean does not support all jsPsych plugins, but new plugins are added regularly.
If you need support for a specific jsPsych plugin, please open an issue here.
Documentation
You can find examples and documentation here: https://autoresearch.github.io/sweetbean/
Issues
Please report any issues with this software or its documentation here.
Contributing
We are open to contributions to SweetBean. More information can be found here.
Collaborating
We are always interested in collaborating! If you like our work but need some tailoring for your specific use case, please contact ystrittmatter@princeton.edu.
Citation
If you would like to reference SweetBean in a publication, you can use the following BibTeX entry referencing the associated publication in the Journal of Open Source Software:
@article{Strittmatter2025, doi = {10.21105/joss.07703},
author = {Younes Strittmatter and Sebastian Musslick},
title = {SweetBean: A declarative language for behavioral experiments with human and artificial participants},
url = {https://doi.org/10.21105/joss.07703},
year = {2025},
publisher = {The Open Journal},
volume = {10},
number = {107},
pages = {7703},
journal = {Journal of Open Source Software},
doi = {10.21105/joss.07703}
}
About
This project is in active development by the Autonomous Empirical Research Group, Lead Designer Younes Strittmatter, led by Sebastian Musslick.
This research program was supported by Schmidt Science Fellows, in partnership with the Rhodes Trust, as well as the Carney BRAINSTORM program at Brown University.
1 maintainer
Metadata
1 maintainer
Release files for sweetbean 1.3.17
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sweetbean-1.3.17.tar.gz | 2.1 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sweetbean-1.3.17-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.2 MB
Release files / sweetbean-1.3.17.tar.gz
| Download URL | sweetbean-1.3.17.tar.gz |
|---|---|
| Size | 2.1 MB |
| Tags | Source |
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Release files / sweetbean-1.3.17-py3-none-any.whl
| Download URL | sweetbean-1.3.17-py3-none-any.whl |
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| Size | 55.9 kB |
| Tags | Python 3 |
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twine/6.2.0 CPython/3.9.24
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