How to find Expectation from continuous function with SymPy and Python?

I want to calculate Expectation and Variance in terms of μ and X, but I do not know what to fill the X below, since it is not a Normal distribution nor Poisson, but a pdf that is random.

from sympy import symbols, Integral
from sympy.stats import Normal, Expectation, Variance, Probability

mu = symbols("μ", positive=True)

sigma = symbols("σ", positive=True)

pdf = (15/512)*(x**2)*((4-x)**2)
X = ?

print('Var(X) =',Variance(X).evaluate_integral())

print('E(X-μ) =',Expectation((X - mu)**2).expand())
print('final computation:')
print('E(X-μ) =',Expectation((X - mu)**2).doit())

In addition to that, there is another condition 0<x<4. Thus E(X)=2 should be the right answer.

Thanks.

Perhaps you are looking for ContinuousRV?

>>> from sympy.stats import ContinuousRV, P, E
>>> from sympy import Interval, Symbol
>>> from sympy.abc import x
>>> mu = Symbol('mu', positive=True)
>>> pdf = 15*x**2*(4 - x)**2/512
>>> X = ContinuousRV(x, pdf, Interval(0, 4))
>>> P(And(X>-1,X<1))
53/512
>>> E(X - mu)  # E(X) == Expectation(X).doit()
2 - mu
>>> E((X - mu)**2)
mu**2 - 4*mu + 32/7