Merge pull request #3563 from jsiirola/imports-and-tests

Defer `pathlib` import, remove test output file

Author: jsiirola

Diff for: pyomo/common/dependencies.py

@@ -1103,6 +1103,7 @@ def _pyutilib_importer():
     networkx, networkx_available = attempt_import('networkx')
     numpy, numpy_available = attempt_import('numpy', callback=_finalize_numpy)
     pandas, pandas_available = attempt_import('pandas')
+    pathlib, pathlib_available = attempt_import('pathlib')
     pint, pint_available = attempt_import(
         'pint',
         # TypeError for pint<=0.24.3 and python>=3.13

Diff for: pyomo/contrib/doe/doe.py

@@ -32,12 +32,11 @@
 import logging
 import math
 
-from pathlib import Path
-
 from pyomo.common.dependencies import (
     numpy as np,
     numpy_available,
     pandas as pd,
+    pathlib,
     matplotlib as plt,
 )
 from pyomo.common.modeling import unique_component_name
@@ -243,7 +242,7 @@ def run_doe(self, model=None, results_file=None):
         """
         # Check results file name
         if results_file is not None:
-            if type(results_file) not in [Path, str]:
+            if type(results_file) not in [pathlib.Path, str]:
                 raise ValueError(
                     "``results_file`` must be either a Path object or a string."
                 )
@@ -1827,7 +1826,7 @@ def _curve1D(
             plt.pyplot.show()
         else:
             plt.pyplot.savefig(
-                Path(figure_file_name + "_A_opt.png"), format="png", dpi=450
+                pathlib.Path(figure_file_name + "_A_opt.png"), format="png", dpi=450
             )
 
         # Draw D-optimality
@@ -1848,7 +1847,7 @@ def _curve1D(
             plt.pyplot.show()
         else:
             plt.pyplot.savefig(
-                Path(figure_file_name + "_D_opt.png"), format="png", dpi=450
+                pathlib.Path(figure_file_name + "_D_opt.png"), format="png", dpi=450
             )
 
         # Draw E-optimality
@@ -1869,7 +1868,7 @@ def _curve1D(
             plt.pyplot.show()
         else:
             plt.pyplot.savefig(
-                Path(figure_file_name + "_E_opt.png"), format="png", dpi=450
+                pathlib.Path(figure_file_name + "_E_opt.png"), format="png", dpi=450
             )
 
         # Draw Modified E-optimality
@@ -1890,7 +1889,7 @@ def _curve1D(
             plt.pyplot.show()
         else:
             plt.pyplot.savefig(
-                Path(figure_file_name + "_ME_opt.png"), format="png", dpi=450
+                pathlib.Path(figure_file_name + "_ME_opt.png"), format="png", dpi=450
             )
 
     def _heatmap(
@@ -1991,7 +1990,7 @@ def _heatmap(
             plt.pyplot.show()
         else:
             plt.pyplot.savefig(
-                Path(figure_file_name + "_A_opt.png"), format="png", dpi=450
+                pathlib.Path(figure_file_name + "_A_opt.png"), format="png", dpi=450
             )
 
         # D-optimality
@@ -2017,7 +2016,7 @@ def _heatmap(
             plt.pyplot.show()
         else:
             plt.pyplot.savefig(
-                Path(figure_file_name + "_D_opt.png"), format="png", dpi=450
+                pathlib.Path(figure_file_name + "_D_opt.png"), format="png", dpi=450
             )
 
         # E-optimality
@@ -2043,7 +2042,7 @@ def _heatmap(
             plt.pyplot.show()
         else:
             plt.pyplot.savefig(
-                Path(figure_file_name + "_E_opt.png"), format="png", dpi=450
+                pathlib.Path(figure_file_name + "_E_opt.png"), format="png", dpi=450
             )
 
         # Modified E-optimality
@@ -2069,7 +2068,7 @@ def _heatmap(
             plt.pyplot.show()
         else:
             plt.pyplot.savefig(
-                Path(figure_file_name + "_ME_opt.png"), format="png", dpi=450
+                pathlib.Path(figure_file_name + "_ME_opt.png"), format="png", dpi=450
             )
 
     # Gets the FIM from an existing model

Diff for: pyomo/contrib/doe/examples/reactor_compute_factorial_FIM.py

@@ -8,21 +8,20 @@
 #  rights in this software.
 #  This software is distributed under the 3-clause BSD License.
 #  ___________________________________________________________________________
-from pyomo.common.dependencies import numpy as np
+from pyomo.common.dependencies import numpy as np, pathlib
 
 from pyomo.contrib.doe.examples.reactor_experiment import ReactorExperiment
 from pyomo.contrib.doe import DesignOfExperiments
 
 import pyomo.environ as pyo
 
 import json
-from pathlib import Path
 
 
 # Example to run a DoE on the reactor
 def run_reactor_doe():
     # Read in file
-    DATA_DIR = Path(__file__).parent
+    DATA_DIR = pathlib.Path(__file__).parent
     file_path = DATA_DIR / "result.json"
 
     with open(file_path) as f:

Diff for: pyomo/contrib/doe/examples/reactor_example.py

@@ -8,22 +8,21 @@
 #  rights in this software.
 #  This software is distributed under the 3-clause BSD License.
 #  ___________________________________________________________________________
-from pyomo.common.dependencies import numpy as np
+from pyomo.common.dependencies import numpy as np, pathlib
 
 from pyomo.contrib.doe.examples.reactor_experiment import ReactorExperiment
 from pyomo.contrib.doe import DesignOfExperiments
 
 import pyomo.environ as pyo
 
 import json
-from pathlib import Path
 
 
 # Example for sensitivity analysis on the reactor experiment
 # After sensitivity analysis is done, we perform optimal DoE
 def run_reactor_doe():
     # Read in file
-    DATA_DIR = Path(__file__).parent
+    DATA_DIR = pathlib.Path(__file__).parent
     file_path = DATA_DIR / "result.json"
 
     with open(file_path) as f:

Diff for: pyomo/solvers/plugins/solvers/KNITROAMPL.py

@@ -9,10 +9,10 @@
 #  This software is distributed under the 3-clause BSD License.
 #  ___________________________________________________________________________
 import logging
-from pathlib import Path
 
 from pyomo.common import Executable
 from pyomo.common.collections import Bunch
+from pyomo.common.dependencies import pathlib
 from pyomo.opt.base.formats import ProblemFormat, ResultsFormat
 from pyomo.opt.base.solvers import SolverFactory, OptSolver
 from pyomo.solvers.plugins.solvers.ASL import ASL
@@ -71,7 +71,9 @@ def _default_executable(self):
             import knitro
 
             package_knitroampl_path = (
-                Path(knitro.__file__).resolve().parent / 'knitroampl' / 'knitroampl'
+                pathlib.Path(knitro.__file__).resolve().parent
+                / 'knitroampl'
+                / 'knitroampl'
             )
             executable = Executable(str(package_knitroampl_path))
         except ModuleNotFoundError: