PyGEP: Python Interface for GeneExpressionProgramming.jl

A Python interface for GeneExpressionProgramming.jl package.

This package provides a Python wrapper for the Julia implementation, which performs symbolic regression using Gene Expression Programming.

Features

• Underlying Julia implementation for fast optimization
• Standard GEP symbolic regression
• Multi-objective optimization (not available yet for the interface)
• Physics-aware regression with dimensional constraints (not available yet for the interface)
• Tensor/matrix regression support (not available yet for the interface)

Installation

1. Install Julia

First, install Julia from https://julialang.org/downloads/

2. Install PyGEP

cd pygep
pip install .

3. Install Julia Dependencies

pygep-setup

or

import pygep
pygep.install_julia_dependencies()

Quick Start

Basic Symbolic Regression

import numpy as np
from pygep import GepRegressor

# Generate test data
X = np.random.randn(100, 2)
y = X[:, 0]**2 + X[:, 0] * X[:, 1] - 2 * X[:, 0] * X[:, 1]

# Create and fit regressor
regressor = GepRegressor(number_features=2)
regressor.fit(X, y, epochs=1000, population_size=1000, loss_function="mse")

# Make predictions
predictions = regressor.predict(X)

# Get results
print(f"Best expression: {regressor.best_expression_}")
print(f"Best fitness: {regressor.best_fitness_}")

API Reference

GepRegressor

Main class for symbolic regression.

Parameters:

• number_features (int): Number of input features

Methods:

• fit(X, y, epochs=1000, population_size=1000, loss_function="mse", ...): Fit the regressor
• predict(X): Make predictions
• get_best_models(n=1): Get n best models

Properties:

• best_expression_: Best symbolic expression as string
• best_fitness_: Fitness of best expression

Requirements

• Python ≥ 3.8
• Julia ≥ 1.6
• numpy ≥ 1.20.0
• julia ≥ 0.6.0 (Python package)

Troubleshooting

Julia Not Found

# Make sure Julia is in your PATH
julia --version

# If not found, add Julia to PATH or install from:
# https://julialang.org/downloads/

PyCall Issues

# In Julia REPL:
using Pkg
Pkg.add("PyCall")
Pkg.build("PyCall")

Package Installation Issues

# Force reinstall Julia dependencies
import pygep
pygep.install_julia_dependencies()

Citation

If you use this package, please cite the original Julia implementation:

@article{Reissmann2025,
  author   = {Maximilian Reissmann and Yuan Fang and Andrew S. H. Ooi and Richard D. Sandberg},
  title    = {Constraining Genetic Symbolic Regression via Semantic Backpropagation},
  journal  = {Genetic Programming and Evolvable Machines},
  year     = {2025},
  volume   = {26},
  number   = {1},
  pages    = {12},
  doi      = {10.1007/s10710-025-09510-z}
}

License

MIT License - see LICENSE file for details.