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PyPath EwE

Python implementation of Ecopath with Ecosim (EwE) for food web modeling.

Python 3.10+ License: MIT PyPI

PyPath extends the R package Rpath with advanced features while maintaining full core compatibility.

Installation

pip install pypath-ewe

Optional Extras

pip install pypath-ewe[spatial]      # Ecospace spatial modeling
pip install pypath-ewe[interactive]  # Plotly interactive plots
pip install pypath-ewe[biodata]      # Species data from WoRMS/OBIS/FishBase
pip install pypath-ewe[numba]        # JIT-compiled ODE solver (~40% faster)
pip install pypath-ewe[all]          # Everything

Quick Example

from pypath import create_rpath_params, rpath, rsim_scenario, rsim_run

# Create a simple 3-group model
params = create_rpath_params(
    groups=["Phytoplankton", "Zooplankton", "Detritus"],
    types=[1, 0, 2],
)
# Set biomass, PB, QB, diet matrix...

# Balance the model
model = rpath(params)

# Run 50-year dynamic simulation
scenario = rsim_scenario(model, params, years=range(1, 51))
output = rsim_run(scenario)

Key Features

Feature Description
Ecopath Mass-balance food web modeling with multi-stanza support
Ecosim Dynamic simulation using foraging arena theory
Ecospace Spatially-explicit modeling with hexagonal grids
IBM Individual-based model coupling (bioenergetics, predation)
State-Variable Forcing Data assimilation and prescribed scenarios
Diet Rewiring Adaptive foraging and prey switching
Optimization Bayesian parameter calibration
Data Import EwE databases, EcoBase, WoRMS/OBIS/FishBase

Packages

This library is part of the PyPath monorepo:

  • pypath-ewe — Core algorithms (this package)
  • pypath-shiny — Interactive web frontend

Web Frontend

Install the Shiny dashboard for a graphical interface:

pip install pypath-shiny
pypath-shiny  # Launches at http://localhost:8000