Improve and standardize the cuPDLPx Python API

.gitignore

@@ -58,12 +58,18 @@ dkms.conf
 # ignored files
 build/*
 test/*
+!test/*.py
 /.vscode
 /.venv
 /_b
 *.whl
 *.pyc
 
+# coverage / pytest artifacts
+.coverage
+coverage.xml
+htmlcov/
+.pytest_cache/
 
 *.txt
 *.sh

pyproject.toml

@@ -52,7 +52,7 @@ test = [
 ]
 
 [tool.pytest.ini_options]
-testpaths = ["tests"]
+testpaths = ["test"]
 addopts = """
 -q
 -ra

python/README.md

@@ -75,7 +75,7 @@ m.setParams(OutputFlag=True, OptimalityTol=1e-8)
 m.optimize()
 
 # Retrieve results
-print("Status:", m.Status)
+print("Status:", m.StatusName)
 print("Objective:", m.ObjVal)
 print("Primal solution:", m.X)
 print("Dual solution:", m.Pi)
@@ -98,7 +98,7 @@ $$
 - **constraint_matrix** (`A`): Coefficient matrix for the constraints. Both dense (`numpy.ndarray`) and sparse (`scipy.sparse.csr_matrix`) inputs are supported. Internally stored in double precision (`float64`).
 - **constraint_lower_bound** (`l`): Lower bounds for each constraint. Use `-np.inf` or `None` for no lower bound.
 - **constraint_upper_bound** (`u`): Upper bounds for each constraint. Use `+np.inf` or `None` for no upper bound.
-- **variable_lower_bound** (`lb`, optional): Lower bounds for the decision variables. Defaults to `0` for all variables if not provided.
+- **variable_lower_bound** (`lb`, optional): Lower bounds for the decision variables. Defaults to `-np.inf` for all variables if not provided.
 - **variable_upper_bound** (`ub`, optional): Upper bounds for the decision variables. Defaults to `+np.inf` for all variables if not provided.
 - **objective_constant** (`c0`, optional): Constant offset in the objective function. Defaults to `0.0`.
 
@@ -125,7 +125,7 @@ m = Model(objective_vector=c,
 
 ### Reading from MPS Files
 
-A `Model` can also be created directly from an MPS file (plain or gzip-compressed) with `cupdlpx.read`, similar to `gurobipy.read`:
+A `Model` can also be created directly from an MPS file (plain or gzip-compressed) with `cupdlpx.read`:
 
 ```python
 import cupdlpx
@@ -174,7 +174,7 @@ Below is a list of commonly used parameters, their internal keys, and descriptio
 | `ReflectionCoeff` | `reflection_coefficient` | float | `1.0` | Reflection coefficient. |
 | `SVMaxIter` | `sv_max_iter` | int | 5000 | Maximum number of iterations for the power method |
 | `SVTol`| `sv_tol` | float | `1e-4` | Termination tolerance for the power method |
-| `Presolve`| `presolve` | float | `True` | Whether to use presolve. |
+| `Presolve`| `presolve` | bool | `True` | Whether to use presolve. |
 | `FeasibilityPolishing` | `feasibility_polishing` | bool | `False` | Run feasibility polishing process.|
 | `FeasibilityPolishingTol` | `eps_feas_polish_relative` | float | `1e-6` | Relative tolerance for primal/dual residual.  |
 
@@ -191,18 +191,21 @@ m.setParams(TimeLimit=300, FeasibilityTol=1e-6)
 # Method 3: attribute-style access
 m.Params.TimeLimit = 300
 m.Params.FeasibilityTol = 1e-6
+
+# Reset all parameters to backend defaults
+m.resetParams()
 ```
 
 ## Solution Attributes
 
-After calling `m.optimize()`, the solver stores results in a set of read-only attributes. These attributes provide access to primal/dual solutions, objective values, residuals, and runtime statistics.
+After calling `m.optimize()`, the solver stores results in a set of read-only attributes. `optimize()` returns the model itself, so chained access like `m.optimize().Status` is also supported. These attributes provide access to primal/dual solutions, objective values, residuals, and runtime statistics.
 
 ### Attribute Reference
 
 | Attribute | Type | Description |
 |---|---|---|
-| `Status` | str | Human-readable solver status (`"OPTIMAL"`, `"INFEASIBLE"`, `"UNBOUNDED"`, `"TIME_LIMIT"`, etc.). |
-| `StatusCode` | int | Numeric status code (`OPTIMAL=1`, `INFEASIBLE=2`, `UNBOUNDED=3`, `ITERATION_LIMIT=4`, `TIME_LIMIT=5`, `UNSPECIFIED=-1`). |
+| `Status` | int | Integer termination status code; compare against `cupdlpx.PDLP` constants: `OPTIMAL=0`, `PRIMAL_INFEASIBLE=1`, `DUAL_INFEASIBLE=2`, `TIME_LIMIT=3`, `ITERATION_LIMIT=4`, `INFEASIBLE_OR_UNBOUNDED=5`, `FEAS_POLISH_SUCCESS=6`, `UNSPECIFIED=-1`. |
+| `StatusName` | str | Human-readable status name, e.g. `"OPTIMAL"`, `"PRIMAL_INFEASIBLE"`. |
 | `ObjVal` | float | Primal objective value at termination (sign-adjusted according to `ModelSense`). |
 | `DualObj` | float | Dual objective value at termination. |
 | `Gap` | float | Absolute primal-dual gap. |
@@ -225,7 +228,7 @@ All solution-related information can then be queried directly from the `Model` o
 ```python
 m.optimize()
 
-print("Status:", m.Status, "(code:", m.StatusCode, ")")
+print("Status:", m.StatusName, "(code:", m.Status, ")")
 print("Primal objective:", m.ObjVal)
 print("Dual objective:", m.DualObj)
 print("Relative gap:", m.RelGap)
@@ -268,7 +271,7 @@ m.setWarmStart(primal=x_init)
 m.setWarmStart(dual=pi_init)
 ```
 
-If the warm-start vectors have incorrect dimensions, the solver automatically falls back to a cold start and issues a warning.
+If the warm-start vectors have incorrect dimensions, `setWarmStart` raises a `ValueError`. Omitting an argument leaves that side unchanged; passing `None` clears it.
 
 To clear existing warm-start values:
 

python/cupdlpx/PDLP.py

@@ -12,17 +12,21 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Objective 
+"""Objective-sense and termination-status constants, plus parameter-name aliases."""
+
+# Objective
 MINIMIZE = 1
 MAXIMIZE = -1
 
-# Status codes
-OPTIMAL           = 0
-PRIMAL_INFEASIBLE = 1
-DUAL_INFEASIBLE   = 2
-TIME_LIMIT        = 3
-ITERATION_LIMIT   = 4
-UNSPECIFIED       = -1
+# Status codes (must match status_to_code in python_bindings/_core_bindings.cpp)
+OPTIMAL                 = 0
+PRIMAL_INFEASIBLE       = 1
+DUAL_INFEASIBLE         = 2
+TIME_LIMIT              = 3
+ITERATION_LIMIT         = 4
+INFEASIBLE_OR_UNBOUNDED = 5
+FEAS_POLISH_SUCCESS     = 6
+UNSPECIFIED             = -1
 
 
 # parameter name alias

python/cupdlpx/__init__.py

@@ -12,11 +12,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+"""cuPDLPx: Python bindings for the GPU-accelerated first-order LP solver."""
+
 import os
 import platform
 
 # Windows only: register CUDA bin for dependent DLL loading.
-if platform.system() == "Windows":
+if platform.system() == "Windows":  # pragma: no cover
     cuda_path = os.environ.get("CUDA_PATH")
     if cuda_path:
         bin_path = os.path.join(cuda_path, "bin")
@@ -26,12 +28,12 @@
 from .model import Model, read
 from . import PDLP
 
-__all__ = ["Model", "read"]
-
 # versioning
 from importlib.metadata import version, PackageNotFoundError
 # get version from package metadata (toml file)
 try:
     __version__ = version("cupdlpx")
-except PackageNotFoundError:
+except PackageNotFoundError:  # pragma: no cover
     __version__ = "0.0.0"
+
+__all__ = ["Model", "PDLP", "read", "__version__"]

python/cupdlpx/_core.py

@@ -12,4 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+"""Thin re-export of the compiled cuPDLPx core extension (_cupdlpx_core)."""
+
 from ._cupdlpx_core import solve_once, get_default_params, read_mps