Single-cut L-shape in python for one optimization problem - optimization

Question

I'm new to L-shape methodology for optimization with gurobi. I know how to solve the farming problem with the stochastic programming formulation but I still do not figure out how to solve it with implement the single-cut L-shape method. Could you please help me with it? Really appreciate it.
This is the problem.
Here is my current code and I don't know how to implement the single-cut L-shape methodology
import gurobipy as gp
from gurobipy import GRB
import itertools
scenarios = ['above avg', 'average', 'below avg']
cropsToPlant = ['wheat', 'corn', 'sb']
cropsToPurchase = ['wheat', 'corn']
cropsToSell = ['wheat', 'corn', 'sb', 'sb low']
plantCost = {'wheat' : 150, 'corn':230, 'sb':260}
salesPrice = {'wheat': 170, 'corn': 150, 'sb': 36, 'sb low': 10}
cattleDemand = {'wheat': 200, 'corn': 240}
purchasePrice = {'wheat': 238, 'corn': 210}
yieldMultiplier = {'above avg' : 1.2, 'average' : 1, 'below avg' : 0.8}
averageYield = {'wheat' : 2.5, 'corn' : 3, 'sb' : 20}
totalAcres = 500
sbQuota = 6000
p = {}
yields = {}
for s in scenarios:
p[s] = 1/len(scenarios)
for c in cropsToPlant:
yields[s, c] = averageYield[c] * yieldMultiplier[s]
print(yields)
m = gp.Model("FarmerSP")
m.setParam('OutputFlag', 0)
x = m.addVars(cropsToPlant, name = "planted")
w = m.addVars(itertools.product(cropsToSell,scenarios), name = "sold")
y = m.addVars(itertools.product(cropsToPurchase,scenarios), name = "purchased")
m.setObjective(-x.prod(plantCost) + p[s]*(gp.quicksum([salesPrice[c]*w[c,s] for c in cropsToSell for s in scenarios]) - gp.quicksum([purchasePrice[c]*y[c, s] for c in cropsToPurchase for s in scenarios])), GRB.MAXIMIZE)
m.addConstr(x.sum() <= totalAcres, "TotalAcres")
m.addConstrs((yields[s,i]*x[i] + y[i,s] - w[i,s] >= cattleDemand[i] for i in cropsToPurchase for s in scenarios), "min amount")
m.addConstrs((w['sb',s] + w['sb low',s] <= yields[s, 'sb']*x['sb'] for s in scenarios), "sugar beet sold")
m.addConstrs((w['sb',s] <= sbQuota for s in scenarios), "SugarBeetQuota")
m.optimize()
for v in m.getVars():
print('%s %g' % (v.VarName, v.X))
print('Obj: %g' % m.ObjVal)