Python interface for BeePop+, the EPA/USDA honey bee colony simulation model.
For more information about BeePop+ see Garber et al. 2022, Ecologies.
For more information about pybeepop+ see Minucci 2025, Journal of Open Research Software.
A Python interface for the USDA/EPA BeePop+ honey bee colony simulation model
pybeepop+ provides the Python implementation of BeePop+, an agent-based model for simulating honey bee (Apis mellifera L.) colony dynamics. The model is designed for ecological risk assessment and research applications.
References:
Minucci, J. (2025). “pybeepop+: A Python Interface for the BeePop+ Honey Bee Colony Model.” Journal of Open Research Software, 13(1). https://doi.org/10.5334/jors.550
Garber, K., et al. (2022). “Simulating the Effects of Pesticides on Honey Bee (Apis mellifera L.) Colonies with BeePop+.” Ecologies, 3(3), 22. https://doi.org/10.3390/ecologies3030022
Package author: Jeffrey Minucci, U.S. Environmental Protection Agency
pybeepop+ is pure Python and runs on Windows, Linux, and macOS.
| Package | Version | Purpose |
|---|---|---|
| Python | ≥ 3.10 | Runtime environment |
| pandas | > 2.0.0 | Data handling |
| matplotlib | > 3.1.0 | Visualization |
Note: The optional C++ engine was removed in version 0.3.0. If you previously passed
engine='cpp'orlib_file=..., remove those arguments — the Python engine is now the only option. See the release notes for details.
pip install pybeepop-plusfrom pybeepop import PyBeePop
# 1. Create a BeePop+ instance
beepop = PyBeePop()
# 2. Configure simulation parameters
params = {
"ICWorkerAdults": 10000,
"ICWorkerBrood": 8000,
"SimStart": "04/13/2015",
"SimEnd": "09/15/2015",
"AIAdultLD50": 0.04
}
beepop.set_parameters(params)
# 3. Load weather data
beepop.load_weather('path/to/weather.txt')
# 4. (Optional) Load pesticide exposure data
beepop.load_residue_file('path/to/residues.txt')
# 5. Run simulation
results = beepop.run_model()
print(results)# Get results as DataFrame
results_df = beepop.get_output()
# Get results as JSON
results_json = beepop.get_output(json_str=True)
# Visualize time series
beepop.plot_output() # default columns
beepop.plot_output(["Colony Size", "Adult Workers"]) # custom columns# Update specific parameters (others remain unchanged)
beepop.set_parameters({"ICWorkerAdults": 22200, "InitColPollen": 4000})
results_updated = beepop.run_model()# Parameters file format (key=value per line)
# Example: my_parameters.txt
# RQEggLayDelay=10
# RQReQueenDate=06/25/2015
# RQEnableReQueen=False
beepop.load_parameter_file('my_parameters.txt')
params = beepop.get_parameters()Note: Parameters not explicitly set will use BeePop+ default values. See the parameter list for details.
Note: Numeric parameters are validated when they are set. A value outside the range listed for it in the parameter reference, or a fractional value for an integer parameter, raises
BeepopParameterErrorand leaves the previously set parameters unchanged.
from pybeepop import PyBeePop
import tempfile
import os
# Create minimal synthetic weather data
weather_data = """04/01/2023, 20.0, 10.0, 15.0, 3.0, 0.0, 12.0
04/02/2023, 22.0, 12.0, 17.0, 2.5, 0.0, 12.1
04/03/2023, 21.0, 11.0, 16.0, 3.2, 2.0, 12.2
04/04/2023, 19.0, 9.0, 14.0, 2.8, 0.0, 12.3
04/05/2023, 23.0, 13.0, 18.0, 2.1, 0.0, 12.4"""
# Write to temporary file
with tempfile.NamedTemporaryFile(mode="w", suffix=".txt", delete=False) as f:
f.write(weather_data)
temp_weather_file = f.name
try:
# Create BeePop+ instance and run simulation
beepop = PyBeePop()
beepop.set_parameters(
{"ICWorkerAdults": 10000, "ICWorkerBrood": 5000, "SimStart": "04/01/2023", "SimEnd": "04/05/2023"}
)
beepop.load_weather(temp_weather_file)
# Run model and display results
results = beepop.run_model()
print(results[["Date", "Colony Size", "Adult Workers"]].head())
finally:
# Clean up temporary file
os.unlink(temp_weather_file)A Jupyter notebook demonstrating pybeepop+ usage
is available here:
Complete API reference and usage guide:
→ https://usepa.github.io/pybeepop/
We welcome community contributions. Here’s how you can help:
Fork the repository and submit pull requests. All submissions will be reviewed by maintainers.
Found a bug? Please open an issue with: - Description of the problem - Steps to reproduce - Expected vs. actual behavior - System information (OS, Python version, etc.)
Need help? Open an issue on GitHub.
This software is provided “as is” without warranty of any kind. The views expressed in this package are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.