Fix to decouple thin client requirements from cuopt main module

ci/test_self_hosted_service.sh

@@ -111,16 +111,16 @@ if [ "$doservertest" -eq 1 ]; then
     run_cli_test "'status': 0" cuopt_sh -s -c "$CLIENT_CERT" -p $CUOPT_SERVER_PORT -f cuopt_problem_data.json
 
     # Success, small LP problem with pure JSON
-    run_cli_test "'status': 1" cuopt_sh -s -c "$CLIENT_CERT" -p $CUOPT_SERVER_PORT -t LP ../../datasets/cuopt_service_data/good_lp.json
+    run_cli_test "'status': 'Optimal'" cuopt_sh -s -c "$CLIENT_CERT" -p $CUOPT_SERVER_PORT -t LP ../../datasets/cuopt_service_data/good_lp.json
 
     # Success, small MILP problem with pure JSON which returns a solution with Optimal status
-    run_cli_test "'status': 1" cuopt_sh -s -c $CLIENT_CERT -p $CUOPT_SERVER_PORT -t LP ../../datasets/mixed_integer_programming/milp_data.json
+    run_cli_test "'status': 'Optimal'" cuopt_sh -s -c $CLIENT_CERT -p $CUOPT_SERVER_PORT -t LP ../../datasets/mixed_integer_programming/milp_data.json
 
     # Succes, small LP problem with mps. Data will be transformed to JSON
-    run_cli_test "'status': 1" cuopt_sh -s -c "$CLIENT_CERT" -p $CUOPT_SERVER_PORT -t LP ../../datasets/linear_programming/good-mps-1.mps
+    run_cli_test "'status': 'Optimal'" cuopt_sh -s -c "$CLIENT_CERT" -p $CUOPT_SERVER_PORT -t LP ../../datasets/linear_programming/good-mps-1.mps
 
     # Succes, small Batch LP problem with mps. Data will be transformed to JSON
-    run_cli_test "'status': 1" cuopt_sh -s -c "$CLIENT_CERT" -p $CUOPT_SERVER_PORT -t LP ../../datasets/linear_programming/good-mps-1.mps ../../datasets/linear_programming/good-mps-1.mps
+    run_cli_test "'status': 'Optimal'" cuopt_sh -s -c "$CLIENT_CERT" -p $CUOPT_SERVER_PORT -t LP ../../datasets/linear_programming/good-mps-1.mps ../../datasets/linear_programming/good-mps-1.mps
 
     # Error, local file mode is not allowed with mps
     run_cli_test "Cannot use local file mode with MPS data" cuopt_sh -s -c "$CLIENT_CERT" -p $CUOPT_SERVER_PORT -t LP -f good-mps-1.mps
@@ -166,8 +166,8 @@ if [ "$doservertest" -eq 1 ]; then
     run_cli_test "Check for status with the following command" cuopt_sh -s -c "$CLIENT_CERT" -p "$CUOPT_SERVER_PORT" -pt 0 ../../datasets/cuopt_service_data/good_lp.json -k
     requestid=$(echo "$cli_test" | tail -1)
     requestid=$(echo ${requestid#cuopt_sh } | sed "s/-p $CUOPT_SERVER_PORT//g" | tr -d "'" | tr -d " ")
-    run_cli_test "'status': 1" cuopt_sh -s -c $CLIENT_CERT -p $CUOPT_SERVER_PORT $requestid -k
-    run_cli_test "'status': 1" cuopt_sh -s -c $CLIENT_CERT -p $CUOPT_SERVER_PORT ../../datasets/cuopt_service_data/good_lp.json -wid $requestid
+    run_cli_test "'status': 'Optimal'" cuopt_sh -s -c $CLIENT_CERT -p $CUOPT_SERVER_PORT $requestid -k
+    run_cli_test "'status': 'Optimal'" cuopt_sh -s -c $CLIENT_CERT -p $CUOPT_SERVER_PORT ../../datasets/cuopt_service_data/good_lp.json -wid $requestid
 
     # Success, larger problem, result comes back in results dir
     run_cli_test "'result_file': 'data.result'" cuopt_sh -s -c "$CLIENT_CERT" -p $CUOPT_SERVER_PORT ../../datasets/cuopt_service_data/service_data_200r.json -o data.result

docs/cuopt/source/cuopt-server/client-api/sh-cli-api.rst

@@ -25,11 +25,6 @@ LP Supporting Classes
     :undoc-members:
     :no-inherited-members:
 
-.. autoclass:: solution.solution.PDLPWarmStartData
-    :members:
-    :undoc-members:
-    :no-inherited-members:
-
 .. autoclass:: data_model.DataModel
     :members:
     :undoc-members:
@@ -38,11 +33,10 @@ LP Supporting Classes
     :members:
     :undoc-members:
 
-.. autoclass:: solution.Solution
+.. autoclass:: cuopt_sh_client.ThinClientSolution
     :members:
     :undoc-members:
 
-
 Self-Hosted Client CLI
 ----------------------
 

docs/cuopt/source/cuopt-server/examples/lp-examples.rst

@@ -115,9 +115,9 @@ Normal mode response:
     {
         "response": {
             "solver_response": {
-                "status": 1,
+                "status": "Optimal",
                 "solution": {
-                    "problem_category": 0,
+                    "problem_category": "LP",
                     "primal_solution": [
                         1.8,
                         0.0
@@ -159,9 +159,9 @@ Batch mode response:
         "response": {
             "solver_response": [
                 {
-                    "status": 1,
+                    "status": "Optimal",
                     "solution": {
-                        "problem_category": 0,
+                        "problem_category": "LP",
                         "primal_solution": [
                             1.8,
                             0.0
@@ -188,9 +188,9 @@ Batch mode response:
                     }
                 },
                 {
-                    "status": 1,
+                    "status": "Optimal",
                     "solution": {
-                        "problem_category": 0,
+                        "problem_category": "LP",
                         "primal_solution": [
                             1.8,
                             0.0
@@ -294,9 +294,9 @@ The response would be as follows:
     {
         "response": {
             "solver_response": {
-                "status": 1,
+                "status": "Optimal",
                 "solution": {
-                    "problem_category": 0,
+                    "problem_category": "LP",
                     "primal_solution": [
                         1.8,
                         0.0
@@ -388,9 +388,9 @@ The response is:
     {
         "response": {
             "solver_response": {
-                "status": 1,
+                "status": "Optimal",
                 "solution": {
-                    "problem_category": 0,
+                    "problem_category": "LP",
                     "primal_solution": [
                         1.8,
                         0.0
@@ -515,23 +515,22 @@ Use a datamodel generated from mps file as input; this yields a solution object
     solution_obj = solution["response"]["solver_response"]["solution"]
 
     # Check Termination Reason
-    # For more detail on termination reasons: checkout `Solution.get_termination_reason()`
-    print("Termination Reason: (1 is Optimal)")
+    print("Termination Reason: ")
     print(solution_status)
 
     # Check found objective value
     print("Objective Value:")
-    print(solution_obj["primal_objective"])
+    print(solution_obj.get_primal_objective())
 
     # Check the MPS parse time
     print(f"Mps Parse time: {parse_time:.3f} sec")
 
     # Check network time (client call - solve time)
-    network_time = network_time - (solution_obj["solver_time"])
+    network_time = network_time - (solution_obj.get_solve_time())
     print(f"Network time: {network_time:.3f} sec")
 
     # Check solver time
-    solve_time = solution_obj["solver_time"]
+    solve_time = solution_obj.get_solve_time()
     print(f"Engine Solve time: {solve_time:.3f} sec")
 
     # Check the total end to end time (mps parsing + network + solve time)
@@ -540,7 +539,7 @@ Use a datamodel generated from mps file as input; this yields a solution object
 
     # Print the found decision variables
     print("Variables Values:")
-    print(solution_obj["vars"])
+    print(solution_obj.get_vars())
 
 
 The response would be as follows:
@@ -625,9 +624,9 @@ Response is as follows:
     {
         "response": {
             "solver_response": {
-                "status": 1,
+                "status": "Optimal",
                 "solution": {
-                    "problem_category": 0,
+                    "problem_category": "LP",
                     "primal_solution": [1.8, 0.0],
                     "dual_solution": [-0.06666666666666668, 0.0],
                     "primal_objective": -0.36000000000000004,
@@ -713,4 +712,4 @@ Aborting a Running Job In CLI
 Please refer to the `MILP Example <milp-examples.html#aborting-a-running-job-in-cli>`_ for more details.
 
 .. note::
-   Please use solver settings while using .mps files.
+   Please use solver settings while using .mps files.

docs/cuopt/source/cuopt-server/examples/milp-examples.rst

@@ -86,9 +86,9 @@ The response would be as follows:
     {
         "response": {
             "solver_response": {
-                "status": 1,
+                "status": "Optimal",
                 "solution": {
-                    "problem_category": 1,
+                    "problem_category": "MIP",
                     "primal_solution": [
                         0.0,
                         5000.0
@@ -210,9 +210,9 @@ Incumbent callback response:
     {
         "response": {
             "solver_response": {
-                "status": 1,
+                "status": "Optimal",
                 "solution": {
-                    "problem_category": 1,
+                    "problem_category": "MIP",
                     "primal_solution": [
                         0.0,
                         5000.0

docs/cuopt/source/thirdparty_modeling_languages/index.rst

@@ -7,7 +7,7 @@ Third-Party Modeling Languages
 AMPL Support
 --------------------------
 
-AMPL can be used with near zero code changes: simply switch to cuOpt as a solver to solve linear and mixed-integer programming problems. Please refer to the `AMPL documentation <https://www.ampl.com/>`_ for more information.
+AMPL can be used with near zero code changes: simply switch to cuOpt as a solver to solve linear and mixed-integer programming problems. Please refer to the `AMPL documentation <https://www.ampl.com/>`_ for more information. Also, see the example notebook in the `colab <https://colab.research.google.com/drive/1eEQik_pae4g_tJQ61QJFlO1fFBXazpBr?usp=sharing>`_.
 
 --------------------------
 PuLP Support

python/cuopt/cuopt/linear_programming/pyproject.toml

@@ -55,7 +55,7 @@ cmake.version = "CMakeLists.txt"
 minimum-version = "build-system.requires"
 ninja.make-fallback = false
 sdist.reproducible = true
-wheel.packages=["data_model", "solution", "cuopt_mps_parser"]
+wheel.packages=["data_model", "cuopt_mps_parser"]
 
 [tool.scikit-build.metadata.version]
 provider = "scikit_build_core.metadata.regex"

python/cuopt_self_hosted/cuopt_sh_client/__init__.py

@@ -22,6 +22,7 @@
     mime_type,
     set_log_level,
 )
+from .thin_client_solution import ThinClientSolution
 from .thin_client_solver_settings import (
     PDLPSolverMode,
     SolverMethod,

python/cuopt_self_hosted/cuopt_sh_client/cuopt_self_host_client.py

@@ -28,9 +28,9 @@
 import msgpack_numpy
 import numpy as np
 import requests
-import solution
 
 from . import _version
+from .thin_client_solution import ThinClientSolution
 from .thin_client_solver_settings import ThinClientSolverSettings
 
 msgpack_numpy.patch()
@@ -173,8 +173,8 @@ def create_solution_obj(solver_response):
         problem_category = sol["problem_category"]
 
         # MILP
-        if problem_category in [1, 2]:
-            solution_obj = solution.Solution(
+        if problem_category in ["MIP", "IP"]:
+            solution_obj = ThinClientSolution(
                 problem_category,
                 sol["vars"],
                 solve_time=sol["solver_time"],
@@ -198,7 +198,7 @@ def create_solution_obj(solver_response):
                 ],
             )
         else:
-            solution_obj = solution.Solution(
+            solution_obj = ThinClientSolution(
                 problem_category,
                 sol["vars"],
                 solve_time=sol["solver_time"],
@@ -716,7 +716,7 @@ def get_LP_solve(
             See the LP documentation for details on solver settings.
         response_type : str
             Choose "dict" if response should be returned as a dictionary or
-            "obj" for Solution object. Defaults to "obj"
+            "obj" for ThinClientSolution object. Defaults to "obj"
         filepath : boolean
             Indicates that cuopt_problem_json_data
             is the relative path of a cuopt data file under the server's
@@ -750,7 +750,7 @@ def get_LP_solve(
             a list of strings. The LP solver will not return any
             incumbent solutions. Default is None.
 
-        Returns: dict or Solution object.
+        Returns: dict or ThinClientSolution object.
         """
 
         if incumbent_callback is not None and not callable(incumbent_callback):
@@ -923,7 +923,7 @@ def repoll(self, data, response_type="obj", delete_solution=True):
             containing the key 'reqId' where the value is the uuid.
         response_type: str
             For LP problem choose "dict" if response should be returned
-            as a dictionary or "obj" for Solution object.
+            as a dictionary or "obj" for ThinClientSolution object.
             Defaults to "obj".
             For VRP problem, response_type is ignored and always
             returns a dict.