promptingcompany/nv-skills

cuopt-routing-api-python

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

First seen Jun 12, 2026

Installation

$ npx skills add promptingcompany/nv-skills --skill cuopt-routing-api-python

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from promptingcompany/nv-skills · top by installs.

npx skills add promptingcompany/nv-skills

Browse all from promptingcompany/nv-skills

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Also listed on

Alternate registries and mirrors of this skill.

Repository health

License LICENSE
Default branch main
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version26.08.00
LicenseApache-2.0
More metadata
author
NVIDIA cuOpt Team
tags
["cuopt","routing","vrp","tsp","python"]

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,697 B
  • docs SUMMARY.md 155 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 39 installs

SKILL.md

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

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

# 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

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)

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

Solver Settings

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 addtransittime_matrix()
Wrong cost Check cost_matrix is symmetric
computewaypointsequence 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.geterrormessage()) and print(solution.getinfeasibleorders().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
  • [serverexamples.md](references/serverexamples.md) — REST client (curl, Python)
  • Reference models: This skill's assets/ — [vrpbasic](assets/vrpbasic/), [pdpbasic](assets/pdpbasic/). See [assets/README.md](assets/README.md).

Escalate

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