latx — Symbolic Expression Compiler

Build symbolic expression trees from variables, constants, arithmetic, and transcendental functions. Compile them to fast callable functions. Pure stdlib, zero dependencies.

Why it exists: latx bridges the gap between symbolic algebra and numerical computation. Define an expression symbolically, use operator overloading (+, *, sin, etc.), then compile it to a Python function that evaluates the expression for given inputs. This is useful for defining mathematical models, computing gradients by hand, and separating model specification from evaluation.

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Primitives

from latpy.latx import Var, Const

Class	Description
Var(name)	Symbolic variable with a string name
Const(value)	Constant value (converted to float)

x = Var("x")
c = Const(3.14)

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Expressions

from latpy.latx import (
    Expr, Add, Sub, Mul, Div, Pow, Neg,
    Sin, Cos, Exp, Log,
)

All expression types support operator overloading:

Python Expression	latx Node	Description
a + b	Add(a, b)	Addition
a - b	Sub(a, b)	Subtraction
a * b	Mul(a, b)	Multiplication
a / b	Div(a, b)	Division
a ** b	Pow(a, b)	Power
-a	Neg(a)	Negation
Sin(x)	Sin(x)	Sine (radians)
Cos(x)	Cos(x)	Cosine
Exp(x)	Exp(x)	Exponential
Log(x)	Log(x)	Natural logarithm

Expressions compose naturally:

x = Var("x")
expr = x * x + 2.0 * x + 1.0   # (x² + 2x + 1)

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Compilation

from latpy.latx import compile

Signature	Description
compile(expr, *variables) -> Callable	Compile expression tree to callable function

The compiled function takes positional arguments matching the variables in order, and returns a single float.

x = Var("x")
expr = Sin(x) + Cos(x)
f = compile(expr, x)
print(f(0.0))  # sin(0) + cos(0) = 1.0

# Multi-variable
x = Var("x")
y = Var("y")
f = compile(x * x + y * y, x, y)
print(f(3.0, 4.0))  # 25.0

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Complete Example

from latpy.latx import Var, Sin, compile, pi

x = Var("x")
# Define a damped oscillator model
expr = Sin(x) * Exp(-x / 3.0)
f = compile(expr, x)

for val in [0.0, 1.0, 2.0, 5.0]:
    print(f"f({val:.1f}) = {f(val):.4f}")