[QST]Simple_LP_pulp.ipynb on Colab, PulpSolverError: CUOPT: Not available

[yishuanglnvidiacom-netizen]

status = prob.solve(CUOPT(msg=0)) always returns PulpSolverError: CUOPT: Not available

Below is the code, how can I get this simple example run on Colab? Thanks

!pip install pulp==3.2.0
!pip install --extra-index-url=https://pypi.nvidia.com  nvidia-cuda-runtime-cu12==12.8.*   cuopt-server-cu12==25.8.* cuopt-sh-client==25.8.*

# Import packages.
from pulp import *
import numpy as np

# Generate a random non-trivial linear program.
m = 15
n = 10
np.random.seed(1)
s0 = np.random.randn(m)
lamb0 = np.maximum(-s0, 0)
s0 = np.maximum(s0, 0)
x0 = np.random.randn(n)
A = np.random.randn(m, n)
b = A @ x0 + s0
c = -A.T @ lamb0

# Define and solve the Pulp problem
prob = LpProblem("LP_example", LpMinimize)
x = [LpVariable(f"x{i}", lowBound=None) for i in range(n)]
prob += lpSum([c[i] * x[i] for i in range(n)]), "Objective"

for i in range(m):
    prob += lpSum([A[i, j] * x[j] for j in range(n)]) <= b[i], f"Constraint_{i}"

status = prob.solve(CUOPT(msg=0))

# Print results
print("\nThe optimal value is", value(prob.objective))
x_vals = np.array([x[i].varValue for i in range(n)])
np.set_printoptions(precision=8, suppress=True)
print("A solution x is")
print(x_vals)

PulpSolverError                           Traceback (most recent call last)
[/tmp/ipython-input-1803750161.py](https://localhost:8080/#) in <cell line: 0>()
----> 1 status = prob.solve(CUOPT(msg=0))
      2 
      3 # Print results
      4 print("\nThe optimal value is", value(prob.objective))
      5 x_vals = np.array([x[i].varValue for i in range(n)])

1 frames
[/usr/local/lib/python3.12/dist-packages/pulp/apis/cuopt_api.py](https://localhost:8080/#) in actualSolve(self, lp, callback)
     58         def actualSolve(self, lp, callback=None):
     59             """Solve a well formulated lp problem"""
---> 60             raise PulpSolverError("CUOPT: Not available")
     61 
     62     else:

PulpSolverError: CUOPT: Not available