How to populate a variable/expression in CVXPY

Question

I am trying to translate cvx code to cvxpy. The major problem I am having is finding something similar to expressions. I used expressions to set values for an entire list of len(n). From my understanding the attributes in a variable in cvx cannot be modified while an expression can. In cvx I would do this by:

n = 100;
init = 10;
cvx begin 
   variables A(n), B(n), C(n)
   expression X(n)
   X(1) = init;
   for t=2:n
       X(t) = X(t - 1) + A(t - 1) + B(t - 1) + C(t - 1)
   end

   minimize(sum(A) + max(B))
   subject to 
     for t = 1:n
       A(t) >= 1;
       B(t) <= 1;
       C(t) >= 1;
     end
cvx end   

According to a previous post(How to set cvxpy n-dim variable first value?)there seems to be no equivalent to expressions in cvxpy afaik, so I would need to create that variable to a constraint like so.

   import cvxpy as cp
   n = 100
   init = 10
   A = cp.variable(n)
   B = cp.variable(n)
   C = cp.variable(n)
   X = cp.variable(n)
   
   obj = cp.Minimize(sum(A) + max(B))
   # TODO automate introduction of variables.
   cons = [
      X[0] == init,
      A[0] >= 1,
      B[0] <= 1,
      C[0] >= 1
   ]

   cons2 = [
      X[t] == X[t - 1] + A[t - 1] + B[t - 1] + C[t - 1],
      A[t] >= 1,
      B[t] <= 1,
      C[t] >= 1
      for t in range(1,n)
   ]
   cons.append(cons2)
   prob = cp.Problem(obj, cons)  

I get this error message: "NotImplementedError: Strict inequalities are not allowed." Apparently cvxpy does not like == in the constraints, but I am not sure how to populate X otherwise. Also, I think I might be off with my list creation for the constraints as well. Thank you for the help.

Alternate cvxpy code:

   import cvxpy as cp
   n = 100
   init = 10
   A = cp.variable(n)
   B = cp.variable(n)
   C = cp.variable(n)
   X = cp.variable(n)
   
   obj = cp.Minimize(sum(A) + max(B))
   # TODO automate introduction of variables.
   cons = [
      X[0] == init,
      A[0] >= 1,
      B[0] <= 1,
      C[0] >= 1
   ]

   for t in range(1,n)
      cons2 = [
          X[t] == X[t - 1] + A[t - 1] + B[t - 1] + C[t - 1],
          A[t] >= 1,
          B[t] <= 1,
          C[t] >= 1
      ]
      cons.append(cons2)
   prob = cp.Problem(obj, cons)