```json
{
  "sym_variables": [
    ("x0", "blueberry pies"),
    ("x1", "pickles"),
    ("x2", "bowls of pasta"),
    ("x3", "sashimi")
  ],
  "objective_function": "9*x0 + 5*x1 + 1*x2 + 7*x3",
  "constraints": [
    "2*x0 + 7*x3 >= 36",
    "2*x0 + 5*x1 >= 18",
    "5*x1 + 3*x2 >= 31",
    "3*x2 + 7*x3 >= 24",
    "5*x1 + 7*x3 >= 47",
    "2*x0 + 5*x1 + 7*x3 >= 36",
    "2*x0 + 3*x2 + 7*x3 >= 36",
    "2*x0 + 5*x1 + 7*x3 >= 43",
    "2*x0 + 3*x2 + 7*x3 >= 43",
    "2*x0 + 5*x1 + 3*x2 + 7*x3 >= 43",
    "-2*x0 + 2*x1 >= 0",
    "5*x1 + 7*x3 <= 57",
    "2*x0 + 5*x1 + 3*x2 <= 143",
    "2*x0 + 3*x2 + 7*x3 <= 181",
    "5*x1 + 3*x2 + 7*x3 <= 125",
    "2*x0 + 5*x1 + 3*x2 + 7*x3 <= 207" 
  ]
}
```

```python
import gurobipy as gp

try:
    # Create a new model
    m = gp.Model("carbohydrate_optimization")

    # Create variables
    blueberry_pies = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="blueberry_pies")
    pickles = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="pickles")
    bowls_of_pasta = m.addVar(lb=0, vtype=gp.GRB.INTEGER, name="bowls_of_pasta")
    sashimi = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="sashimi")

    # Set objective function
    m.setObjective(9 * blueberry_pies + 5 * pickles + 1 * bowls_of_pasta + 7 * sashimi, gp.GRB.MINIMIZE)

    # Add constraints
    m.addConstr(2 * blueberry_pies + 7 * sashimi >= 36)
    m.addConstr(2 * blueberry_pies + 5 * pickles >= 18)
    m.addConstr(5 * pickles + 3 * bowls_of_pasta >= 31)
    m.addConstr(3 * bowls_of_pasta + 7 * sashimi >= 24)
    m.addConstr(5 * pickles + 7 * sashimi >= 47)
    m.addConstr(2 * blueberry_pies + 5 * pickles + 7 * sashimi >= 36)
    m.addConstr(2 * blueberry_pies + 3 * bowls_of_pasta + 7 * sashimi >= 36)
    m.addConstr(2 * blueberry_pies + 5 * pickles + 7 * sashimi >= 43)
    m.addConstr(2 * blueberry_pies + 3 * bowls_of_pasta + 7 * sashimi >= 43)
    m.addConstr(2 * blueberry_pies + 5 * pickles + 3 * bowls_of_pasta + 7 * sashimi >= 43)
    m.addConstr(-2 * blueberry_pies + 2 * pickles >= 0)
    m.addConstr(5 * pickles + 7 * sashimi <= 57)
    m.addConstr(2 * blueberry_pies + 5 * pickles + 3 * bowls_of_pasta <= 143)
    m.addConstr(2 * blueberry_pies + 3 * bowls_of_pasta + 7 * sashimi <= 181)
    m.addConstr(5 * pickles + 3 * bowls_of_pasta + 7 * sashimi <= 125)
    m.addConstr(2 * blueberry_pies + 5 * pickles + 3 * bowls_of_pasta + 7 * sashimi <= 207)


    # Optimize model
    m.optimize()

    if m.status == gp.GRB.OPTIMAL:
        print('Obj: %g' % m.objVal)
        for v in m.getVars():
            print('%s %g' % (v.varName, v.x))
    elif m.status == gp.GRB.INFEASIBLE:
        print('Optimization problem is infeasible.')


except gp.GurobiError as e:
    print('Error code ' + str(e.errno) + ': ' + str(e))

except AttributeError:
    print('Encountered an attribute error')
```