How do I create a variable where one index depends on the value of another index?

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Python

optimization

Hello guys. I'm having an issue with a Python PulP MILP problem. You can find the simplified code that reproduces the problem here:

from pulp import *
machines = 2
I = range(machines)
positions = 2
J = range(positions)
years = 10
T = range(years)
age = {0: 5, 1: 7}

IR = 0.06
df = 0.3

costs = {(0,0):300, (0,1):200, (1,0):500, (1,1):350}

factor = {}
finalcosts = {}
for i in I:
    for j in J:
        for t in T:
            for k in range(age[i]):
                factor[t,k] = ((1-df)**k)/((1+IR)**t)
                finalcosts[i,j,t,k] = costs[i,j]*factor[t,k]
                
prob = LpProblem("TrialProb",LpMinimize)


Prob_vars = LpVariable.dicts("probvars", ((Machine, Position,Year, Age) for Machine in I for Position in J for Year in T for Age in range(age[i])),0,None, LpInteger)

This gives me a 'finalcosts' variable with a size of 240 which is what I want, with all the correct values. But the 'Prob_vars' are of a size 260, counting the second index k for the first index i as well. Meaning that while in 'finalcosts' for i=0, k=0:4 and for i=2, k=0:6 (which is what I want), for the 'Prob_vars' decision variable index k=0:6 for both i=1 & i=2.

I'm fairly new to Python so I can't quite grasp where the problem lies.

What I have tried:

I've tried all combinations that I could think of for different expressions of the 'Prob_vars' but nothing works properly. Like taking the indices expressions out of the variable statement:

for i in I:
    for j in J:
        for t in T:
            for Age in range(lifetime[i]):
                Prob_vars = LpVariable.dicts("probvars", ((Machine, Position,Year, 
                Age), 0,None, LpInteger)

I also looked anywhere I could think of online but I can't find an answer to this.