Low entropy symbolic model definitions in Python

lesmd.py

import sympy

class DfunSymGen(dict):
    def __init__(self):
        self.symbols = []
    def __setitem__(self, key, val):
        dict.__setitem__(self, key, val)
        self.symbols.append(key)
    def __getitem__(self, key):
        if key not in self:
            if key in dir(sympy):
                obj = getattr(sympy, key)
            else:
                obj = sympy.Symbol(key)
            self.__setitem__(key, obj)
        return super().__getitem__(key)

class DfunMeta(type):
    @classmethod
    def __prepare__(metacls, name, bases, **kwds):
        return DfunSymGen()
    def __new__(cls, name, bases, classdict):
        result = type.__new__(cls, name, bases, dict(classdict))
        result.symbols = classdict.symbols
        return result

class Montbrio(metaclass=DfunMeta):
    dr = 1/tau * ( Delta / (pi * tau) + 2 * V * r)
    dV = 1/tau * ( V**2 - pi**2 * tau**2 * r**2 + eta + J * tau * r + I + cr * Coupling_Term_r + cv * Coupling_Term_V)

m = Montbrio()
print(m.dr) # -> (Delta/(pi*tau) + 2*V*r)/tau
print(m.dV) # 
print(m.symbols) # -> [..., 'cv', 'Coupling_Term_V', 'dV']