```json
{
  "sym_variables": [
    ("x1", "dining tables"),
    ("x2", "desks")
  ],
  "objective_function": "maximize 350*x1 + 400*x2",
  "constraints": [
    "2*x1 + 3*x2 <= 100",
    "3*x1 + 4*x2 <= 75",
    "1*x1 + 2*x2 <= 80",
    "x1 >= 0",
    "x2 >= 0"
  ]
}
```

```python
import gurobipy as gp
from gurobipy import GRB

# Create a new model
m = gp.Model("woodshop")

# Create variables
tables = m.addVar(vtype=GRB.CONTINUOUS, name="tables")
desks = m.addVar(vtype=GRB.CONTINUOUS, name="desks")

# Set objective function
m.setObjective(350 * tables + 400 * desks, GRB.MAXIMIZE)

# Add constraints
m.addConstr(2 * tables + 3 * desks <= 100, "woodworking")
m.addConstr(3 * tables + 4 * desks <= 75, "nails")
m.addConstr(1 * tables + 2 * desks <= 80, "varnish")
m.addConstr(tables >=0)
m.addConstr(desks >= 0)


# Optimize model
m.optimize()

if m.status == GRB.OPTIMAL:
    print(f"Optimal solution found:")
    print(f"  Dining Tables: {tables.x}")
    print(f"  Desks: {desks.x}")
    print(f"  Profit: ${m.objVal}")
elif m.status == GRB.INFEASIBLE:
    print("The model is infeasible.")
else:
    print(f"Optimization terminated with status {m.status}")

```
