Dynamically adjusting index in a function

I have the following problem. I have this code. The whole code can be found here.

from gurobipy import *import gurobipy as guimport pandas as pd# Create DF out of SetsI_list = [1, 2, 3]T_list = [1, 2, 3, 4, 5, 6, 7]K_list = [1, 2, 3]I_list1 = pd.DataFrame(I_list, columns=['I'])T_list1 = pd.DataFrame(T_list, columns=['T'])K_list1 = pd.DataFrame(K_list, columns=['K'])DataDF = pd.concat([I_list1, T_list1, K_list1], axis=1)Demand_Dict = {(1, 1): 2, (1, 2): 1, (1, 3): 0, (2, 1): 1, (2, 2): 2, (2, 3): 0, (3, 1): 1, (3, 2): 1, (3, 3): 1,               (4, 1): 1, (4, 2): 2, (4, 3): 0, (5, 1): 2, (5, 2): 0, (5, 3): 1, (6, 1): 1, (6, 2): 1, (6, 3): 1,               (7, 1): 0, (7, 2): 3, (7, 3): 0}class MasterProblem:    def __init__(self, dfData, DemandDF, iteration, current_iteration):        self.iteration = iteration        self.current_iteration = current_iteration        self.nurses = dfData['I'].dropna().astype(int).unique().tolist()        self.days = dfData['T'].dropna().astype(int).unique().tolist()        self.shifts = dfData['K'].dropna().astype(int).unique().tolist()        self.roster = list(range(1, self.current_iteration + 2))        self.demand = DemandDF        self.model = gu.Model("MasterProblem")        self.cons_demand = {}        self.newvar = {}        self.cons_lmbda = {}    def buildModel(self):        self.generateVariables()        self.generateConstraints()        self.model.update()        self.generateObjective()        self.model.update()        print(f"Roster-Index: {self.roster}")...    def addColumn(self, newSchedule):        self.newvar = {}        colName = f"Schedule[{self.nurses},{self.roster}]"        newScheduleList = []        for i, t, s, r in newSchedule:            newScheduleList.append(newSchedule[i, t, s, r])        Column = gu.Column([], [])        self.newvar = self.model.addVar(vtype=gu.GRB.CONTINUOUS, lb=0, column=Column, name=colName)        self.current_iteration = itr        print(f"Roster-Index: {self.current_iteration}")        self.model.update()    def solveModel(self, timeLimit, EPS):        self.model.setParam('TimeLimit', timeLimit)        self.model.setParam('MIPGap', EPS)        self.model.Params.QCPDual = 1        self.model.Params.OutputFlag = 0        self.model.optimize()    def modifyConstraint(self, index, itr):        self.nurseIndex = index        self.rosterIndex = itr        for t in self.days:            for s in self.shifts:                self.newcoef = 1.0                current_cons = self.cons_demand[t, s]                qexpr = self.model.getQCRow(current_cons)                new_var = self.newvar                new_coef = self.newcoef                qexpr.add(new_var * self.lmbda[self.nurseIndex, self.rosterIndex + 1], new_coef)                rhs = current_cons.getAttr('QCRHS')                sense = current_cons.getAttr('QCSense')                name = current_cons.getAttr('QCName')                newcon = self.model.addQConstr(qexpr, sense, rhs, name)                self.model.remove(current_cons)                self.cons_demand[t, s] = newcon                return newconclass Subproblem:    def __init__(self, duals_i, duals_ts, dfData, i, M, iteration):.....    def getNewSchedule(self):        return self.model.getAttr("X", self.motivation)....#### Column Generation# CG PrerequisitesmodelImprovable = Truet0 = time.time()max_itr = 2itr = 0# Build & Solve MPmaster = MasterProblem(DataDF, Demand_Dict, max_itr, itr)master.buildModel()print('*         *****Column Generation Iteration*****          \n*')while (modelImprovable) and itr < max_itr:    # Start    itr += 1    # Solve RMP    master.solveRelaxModel()    # Solve SPs    modelImprovable = False    for index in I_list:        subproblem = Subproblem(duals_i, duals_ts, DataDF, index, 1e6, itr)        subproblem.buildModel()        subproblem.solveModel(3600, 1e-6)        status = subproblem.getStatus()        if status != 2:            raise Exception("Pricing-Problem can not reach optimality!")        reducedCost = subproblem.getObjVal()        if reducedCost < -1e-6:            ScheduleCuts = subproblem.getNewSchedule()            master.addColumn(ScheduleCuts)            master.modifyConstraint(index, itr)            master.updateModel()            modelImprovable = True    master.updateModel()

Now to my problem. I initialize my MasterProblem where the index self.roster is formed based on the iterations. Since itr=0 during initialization, self.roster is initially [1]. Now I want this index to increase by one for each additional iteration, so in the case of itr=1, self.roster = [1,2] and so on. Unfortunately, I don't know how I can achieve this without "building" the model anew each time using the buildModel() function. Thanks for your help. Since this is a Python problem, I'll post it here.