cuopt-routing-api-python

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha d343c09f339b · 31 Oct 2026Report an issue or request a re-scan

• Publishernvidia GitHub organizationOwner of the repository this skill is read from
• Source foldernvidia/skills/skills/cuopt-routing-api-pythonThe exact folder we audited
• LicenceApache-2.0As the repository states it
• Commit pinned for this verdictd343c09f339bA new audit runs when the source changes
• Repository statusNot archivedPushed today
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Vehicle routing (VRP, TSP, PDP) with cuOpt — Python API only. Use when the user is building or solving routing in Python.

---
name: cuopt-routing-api-python
version: "26.10.00"
description: Vehicle routing (VRP, TSP, PDP) with cuOpt — Python API only. Use when the user is building or solving routing in Python.
license: Apache-2.0
metadata:
  author: NVIDIA cuOpt Team
  tags:
    - cuopt
    - routing
    - vrp
    - tsp
    - python
---




# cuOpt Routing — Python API

This skill is **Python only**. Routing has no C API in cuOpt.

## Required questions

Ask these if not already clear:

1. **Problem type** — TSP, VRP, or PDP?
2. **Locations** — How many? Depot(s)? Cost or distance between pairs (matrix or derived)?
3. **Orders / tasks** — Which locations must be visited? Demand or service per stop?
4. **Fleet** — Number of vehicles, capacity per vehicle (and per dimension if multiple), start/end locations?
5. **Constraints** — Time windows (earliest/latest arrival), service times, precedence (order A before B)?

## Minimal VRP Example

```python
import cudf
from cuopt import routing

cost_matrix = cudf.DataFrame([...], dtype="float32")
dm = routing.DataModel(n_locations=4, n_fleet=2, n_orders=3)
dm.add_cost_matrix(cost_matrix)
dm.set_order_locations(cudf.Series([1, 2, 3], dtype="int32"))
solution = routing.Solve(dm, routing.SolverSettings())

if solution.get_status() == 0:
    solution.display_routes()
```

## Adding Constraints

```python
# Time windows
dm.add_transit_time_matrix(transit_time_matrix)
dm.set_order_time_windows(earliest_series, latest_series)

# Capacities
dm.add_capacity_dimension("weight", demand_series, capacity_series)
dm.set_order_service_times(service_times)
dm.set_vehicle_locations(start_locations, end_locations)
dm.set_vehicle_time_windows(earliest_start, latest_return)

# Pickup-delivery pairs
dm.set_pickup_delivery_pairs(pickup_indices, delivery_indices)

# Precedence
dm.add_order_precedence(node_id=2, preceding_nodes=np.array([0, 1]))
```

## Solution Checking

```python
status = solution.get_status()  # 0=SUCCESS, 1=FAIL, 2=TIMEOUT, 3=EMPTY
if status == 0:
    route_df = solution.get_route()
    total_cost = solution.get_total_objective()
else:
    print(solution.get_error_message())
    print(solution.get_infeasible_orders().to_list())
```

## Data Types (use explicit dtypes)

```python
cost_matrix = cost_matrix.astype("float32")
order_locations = cudf.Series([...], dtype="int32")
demand = cudf.Series([...], dtype="int32")
```

## Solver Settings

```python
ss = routing.SolverSettings()
ss.set_time_limit(30)
ss.set_verbose_mode(True)
ss.set_error_logging_mode(True)
```

## Common Issues

| Problem | Fix |
|---------|-----|
| Empty solution | Widen time windows or check travel times |
| Infeasible orders | Increase fleet or capacity |
| Status != 0 with time windows | Add `add_transit_time_matrix()` |
| Wrong cost | Check cost_matrix is symmetric |
| `compute_waypoint_sequence` alters route_df | It replaces the `location` column with waypoint ids in place — pass `route_df.copy()` if you still need cost-matrix indices (e.g. when iterating per truck) |

## Debugging

**When status != 0:** `print(solution.get_error_message())` and `print(solution.get_infeasible_orders().to_list())` to see which orders are infeasible.

**Data types:** Use explicit dtypes (float32, int32) for matrices and series to avoid silent errors.

## Examples

- [examples.md](references/examples.md) — VRP, PDP, multi-depot
- [server_examples.md](references/server_examples.md) — REST client (curl, Python)
- **Reference models:** This skill's `assets/` — [vrp_basic](assets/vrp_basic/), [pdp_basic](assets/pdp_basic/). See [assets/README.md](assets/README.md).

## Escalate

For contribution or build-from-source, see the developer skill.

Excerpt, first 3,675 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

1. 2026-10-31
   ✓SAFE B 89 / 100

   first audit · source d343c09f339b

Questions about cuopt-routing-api-python

• github.com/nvidia/skills/tree/main/skills/cuopt-routing-api-pyth — the audited source at commit d343c09f339b and every finding aboveObserved · 31 Oct 2026

Spotted something wrong? Report a correction · Methodology