symbolic-math-verify 0.1.1

Symbolic math verification utilities built on SymPy.

Symbolic Math Verify

Symbolic math verification utilities built on SymPy.

This project checks whether equations are equivalent, whether a substitution step is valid, whether a uniform subscript rename is valid, whether a numeric calculation matches an expected value, and whether a YAML proof file is valid.

PyPI package: symbolic-math-verify

Install

pip install symbolic-math-verify

Import it as symbolic_math_verify.

Public API

from symbolic_math_verify import extract_variables
from symbolic_math_verify import is_calculation_correct
from symbolic_math_verify import is_equation_equal
from symbolic_math_verify import is_subscript_substitution_correct
from symbolic_math_verify import is_substitution_correct
from symbolic_math_verify import verify_yaml_file

What It Does

• is_equation_equal(symbol_list, lhs_equation, rhs_equation) -> bool Proves whether two equations define the same zero relation.
• is_substitution_correct(symbol_list, equation_before, substitute_equation, equation_after) -> bool Proves whether equation_after is a valid substitution result.
• is_subscript_substitution_correct(symbol_list, equation_before, subscript, equation_after) -> bool Proves whether the same suffix such as _i was applied consistently to every declared symbol.
• is_calculation_correct(symbol_list, symbol_val, equation, expected_value, tolerance) -> bool Evaluates an expression or equation residual numerically and compares it to an expected value.
• extract_variables(math_expression) -> list[str] Extracts variable names from math-like text while skipping known functions and constants.
• verify_yaml_file(file_path) -> str Validates YAML axioms, proof chains, substitution steps, subscript-substitution steps, and calculations.

Examples

Equation equivalence:

from symbolic_math_verify import is_equation_equal

is_equation_equal(["x"], "x + 2 = 5", "x = 3")
# True

Substitution:

from symbolic_math_verify import is_substitution_correct

is_substitution_correct(
    ["x", "y", "z"],
    "y = 1/x + 5*z",
    "x = z^3",
    "y = 1/(z^3) + 5*z",
)
# True

Subscript substitution:

from symbolic_math_verify import is_subscript_substitution_correct

is_subscript_substitution_correct(
    ["E", "m", "v"],
    "E = (1/2)*m*(v^2)",
    "_i",
    "E_i = (1/2)*m_i*(v_i^2)",
)
# True

Calculation:

from symbolic_math_verify import is_calculation_correct

is_calculation_correct(
    ["x", "y", "z"],
    [0.5, -0.2, 14.0],
    "x + y^2 + 1/z",
    0.61142,
    0.001,
)
# True

Variable extraction:

from symbolic_math_verify import extract_variables

extract_variables("P = I*V ; V = I*R -> P = R*I^2")
# ['P', 'I', 'V', 'R']

YAML verification:

from symbolic_math_verify import verify_yaml_file

verify_yaml_file("test_yaml/valid_11_prompt_with_calculation.yaml")
# "Math proofs are valid"

YAML Support

verify_yaml_file() validates YAML files containing:

• axioms
• theorem/proof sections with ->, ;, and : proof steps
• optional calculations

For axioms and theorem sections, vars may be omitted and will be auto-detected from the math text. For calculations, vars is required.

See YAML_tutorial.md for a full YAML proof example and validation rules.

Notes

• The checker is conservative: True means proven, while False means wrong, invalid, ambiguous, or not proven.
• Equations may be written as lhs = rhs or as zero expressions such as x^2 - 1.
• Common Unicode math characters such as −, ×, ÷, and π are normalized before parsing.