https://github.com/autoresearch/sweetbean
A declarative programming language built in Python, designed for the synthesis of behavioral experiments
https://github.com/autoresearch/sweetbean
automated-documentation behavioral-experiments online-behavioral-experiments synthetic-participants
Last synced: 5 months ago
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A declarative programming language built in Python, designed for the synthesis of behavioral experiments
- Host: GitHub
- URL: https://github.com/autoresearch/sweetbean
- Owner: AutoResearch
- License: mit
- Created: 2022-11-15T16:54:03.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2025-10-21T14:57:55.000Z (8 months ago)
- Last Synced: 2025-11-18T02:39:00.933Z (7 months ago)
- Topics: automated-documentation, behavioral-experiments, online-behavioral-experiments, synthetic-participants
- Language: Python
- Homepage: https://autoresearch.github.io/sweetbean/
- Size: 6.6 MB
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 7
-
Metadata Files:
- Readme: README.md
- Contributing: docs/CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.cff
Awesome Lists containing this project
README
[](https://opensource.org/licenses/MIT)
[](https://doi.org/10.21105/joss.07703)
# 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](https://www.jspsych.org/) 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](https://autoresearch.github.io/autora/): For closed loop research, automatic experiment deployment, participant recruitment, and data collection.
- [SweetPea](http://sweetpea.ai/): 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:
```bash
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`:
- `jinja2`
- `transcrypt`
- `pyppeteer`
- `pillow`
### 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](https://github.com/AutoResearch/sweetbean/issues).**
## 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](https://github.com/AutoResearch/sweetbean/issues/new/choose).
## Contributing
We are open to contributions to SweetBean. More information can be found [here](https://autoresearch.github.io/sweetbean/CONTRIBUTING/).
## 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](mailto: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](https://joss.theoj.org/papers/10.21105/joss.07703):
```bibtex
@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](https://musslick.github.io/AER_website/Research.html), Lead
Designer [Younes Strittmatter](https://younesstrittmatter.github.io/), led
by [Sebastian Musslick](https://smusslick.com).
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.