API Reference

Complete reference for all Optyx classes and functions

1 Overview

Optyx provides a symbolic optimization interface with automatic differentiation. This reference documents all public classes, functions, and modules.

3 Usage Pattern

from optyx import Variable, Problem, sin, exp

# Create variables
x = Variable("x", lb=-10, ub=10)
y = Variable("y", lb=0)

# Build objective
objective = (x - 3)**2 + (y - 2)**2

# Create and solve problem
problem = Problem()
problem.minimize(objective)
problem.subject_to(x + y >= 1)
problem.subject_to(sin(x) + exp(-y) <= 2)

solution = problem.solve()
print(f"x = {solution['x']:.4f}")
print(f"y = {solution['y']:.4f}")

4 Detailed Documentation

4.1 Guides (with examples)

  • Expressions - Variables, constants, and building expressions
  • Constraints - Equality and inequality constraints
  • Problem - Creating and solving optimization problems
  • Solution - Accessing results and diagnostics
  • Autodiff - How automatic differentiation works

4.2 Auto-Generated Reference

For complete API documentation generated directly from source code docstrings:

→ Full API Reference

5 Importing

# Import everything you need
from optyx import (
    # Core classes
    Variable, Constant, Expression,
    Constraint, Problem, Solution,
    
    # Mathematical functions
    sin, cos, tan,
    exp, log, log2, log10,
    sqrt, abs_,
    sinh, cosh, tanh,
    asin, acos, atan,
    asinh, acosh, atanh,
    
    # Solver status
    SolverStatus,
)

# Check version
import optyx
print(optyx.__version__)