Better import error

pyoptsparse/pyALPSO/pyALPSO.py

@@ -10,6 +10,7 @@
 import numpy as np
 
 # Local modules
+from . import alpso
 from ..pyOpt_error import Error
 from ..pyOpt_optimizer import Optimizer
 
@@ -25,9 +26,7 @@ class ALPSO(Optimizer):
     - pll_type -> STR: ALPSO Parallel Implementation (None, SPM- Static, DPM- Dynamic, POA-Parallel Analysis), *Default* = None
     """
 
-    def __init__(self, raiseError=True, options={}):
-        from . import alpso
-
+    def __init__(self, options={}):
         self.alpso = alpso
 
         category = "Global Optimizer"

pyoptsparse/pyCONMIN/pyCONMIN.py

@@ -2,11 +2,6 @@
 pyCONMIN - A variation of the pyCONMIN wrapper specificially designed to
 work with sparse optimization problems.
 """
-# Compiled module
-try:
-    from . import conmin  # isort: skip
-except ImportError:
-    conmin = None
 # Standard Python modules
 import datetime
 import os
@@ -18,6 +13,11 @@
 # Local modules
 from ..pyOpt_error import Error
 from ..pyOpt_optimizer import Optimizer
+from ..pyOpt_utils import try_import_compiled_module_from_path
+
+# import the compiled module
+THIS_DIR = os.path.dirname(os.path.abspath(__file__))
+conmin = try_import_compiled_module_from_path("conmin", THIS_DIR)
 
 
 class CONMIN(Optimizer):
@@ -30,9 +30,8 @@ def __init__(self, raiseError=True, options={}):
         category = "Local Optimizer"
         defOpts = self._getDefaultOptions()
         informs = self._getInforms()
-        if conmin is None:
-            if raiseError:
-                raise Error("There was an error importing the compiled conmin module")
+        if isinstance(conmin, str) and raiseError:
+            raise ImportError(conmin)
 
         self.set_options = []
         super().__init__(name, category, defaultOptions=defOpts, informs=informs, options=options)

pyoptsparse/pyIPOPT/pyIPOPT.py

@@ -1,24 +1,31 @@
 """
 pyIPOPT - A python wrapper to the core IPOPT compiled module.
 """
-# Compiled module
-try:
-    from . import pyipoptcore  # isort: skip
-except ImportError:
-    pyipoptcore = None
 
 # Standard Python modules
 import copy
 import datetime
+import os
 import time
 
 # External modules
 import numpy as np
 
 # Local modules
-from ..pyOpt_error import Error
 from ..pyOpt_optimizer import Optimizer
-from ..pyOpt_utils import ICOL, INFINITY, IROW, convertToCOO, extractRows, scaleRows
+from ..pyOpt_utils import (
+    ICOL,
+    INFINITY,
+    IROW,
+    convertToCOO,
+    extractRows,
+    scaleRows,
+    try_import_compiled_module_from_path,
+)
+
+# import the compiled module
+THIS_DIR = os.path.dirname(os.path.abspath(__file__))
+pyipoptcore = try_import_compiled_module_from_path("pyipoptcore", THIS_DIR)
 
 
 class IPOPT(Optimizer):
@@ -36,9 +43,8 @@ def __init__(self, raiseError=True, options={}):
         defOpts = self._getDefaultOptions()
         informs = self._getInforms()
 
-        if pyipoptcore is None:
-            if raiseError:
-                raise Error("There was an error importing the compiled IPOPT module")
+        if isinstance(pyipoptcore, str) and raiseError:
+            raise ImportError(pyipoptcore)
 
         super().__init__(
             name,

pyoptsparse/pyNLPQLP/pyNLPQLP.py

@@ -2,11 +2,6 @@
 pyNLPQLP - A pyOptSparse wrapper for Schittkowski's NLPQLP
 optimization algorithm.
 """
-# Compiled module
-try:
-    from . import nlpqlp  # isort: skip
-except ImportError:
-    nlpqlp = None
 # Standard Python modules
 import datetime
 import os
@@ -18,6 +13,11 @@
 # Local modules
 from ..pyOpt_error import Error
 from ..pyOpt_optimizer import Optimizer
+from ..pyOpt_utils import try_import_compiled_module_from_path
+
+# import the compiled module
+THIS_DIR = os.path.dirname(os.path.abspath(__file__))
+nlpqlp = try_import_compiled_module_from_path("nlpqlp", THIS_DIR)
 
 
 class NLPQLP(Optimizer):
@@ -30,9 +30,8 @@ def __init__(self, raiseError=True, options={}):
         category = "Local Optimizer"
         defOpts = self._getDefaultOptions()
         informs = self._getInforms()
-        if nlpqlp is None:
-            if raiseError:
-                raise Error("There was an error importing the compiled nlpqlp module")
+        if isinstance(nlpqlp, str) and raiseError:
+            raise ImportError(nlpqlp)
 
         super().__init__(name, category, defaultOptions=defOpts, informs=informs, options=options)
         # NLPQLP needs Jacobians in dense format

pyoptsparse/pyNSGA2/pyNSGA2.py

@@ -2,12 +2,8 @@
 pyNSGA2 - A variation of the pyNSGA2 wrapper specificially designed to
 work with sparse optimization problems.
 """
-# Compiled module
-try:
-    from . import nsga2  # isort: skip
-except ImportError:
-    nsga2 = None
 # Standard Python modules
+import os
 import time
 
 # External modules
@@ -16,6 +12,11 @@
 # Local modules
 from ..pyOpt_error import Error
 from ..pyOpt_optimizer import Optimizer
+from ..pyOpt_utils import try_import_compiled_module_from_path
+
+# import the compiled module
+THIS_DIR = os.path.dirname(os.path.abspath(__file__))
+nsga2 = try_import_compiled_module_from_path("nsga2", THIS_DIR)
 
 
 class NSGA2(Optimizer):
@@ -30,9 +31,8 @@ def __init__(self, raiseError=True, options={}):
         informs = self._getInforms()
         super().__init__(name, category, defaultOptions=defOpts, informs=informs, options=options)
 
-        if nsga2 is None:
-            if raiseError:
-                raise Error("There was an error importing the compiled nsga2 module")
+        if isinstance(nsga2, str) and raiseError:
+            raise ImportError(nsga2)
 
     @staticmethod
     def _getInforms():

pyoptsparse/pyOpt_utils.py

@@ -9,7 +9,11 @@
     mat = {'csc':[colp, rowind, data], 'shape':[nrow, ncols]} # A csc matrix
 """
 # Standard Python modules
-from typing import Tuple, Union
+import importlib
+import os
+import sys
+import types
+from typing import Optional, Tuple, Union
 import warnings
 
 # External modules
@@ -570,3 +574,38 @@ def _broadcast_to_array(name: str, value: ArrayType, n_values: int, allow_none:
     if not allow_none and any([i is None for i in value]):
         raise Error(f"The {name} argument cannot be 'None'.")
     return value
+
+
+def try_import_compiled_module_from_path(module_name: str, path: Optional[str] = None) -> Union[types.ModuleType, str]:
+    """
+    Attempt to import a module from a given path.
+
+    Parameters
+    ----------
+    module_name : str
+        The name of the module
+    path : Optional[str]
+        The path to import from. If None, the default ``sys.path`` is used.
+
+    Returns
+    -------
+    Union[types.ModuleType, str]
+        If importable, the imported module is returned.
+        If not importable, the error message is instead returned.
+    """
+    orig_path = sys.path
+    if path is not None:
+        path = os.path.abspath(os.path.expandvars(os.path.expanduser(path)))
+        sys.path = [path]
+    try:
+        module = importlib.import_module(module_name)
+    except ImportError as e:
+        if path is not None:
+            warnings.warn(
+                f"{module_name} module could not be imported from {path}.",
+                stacklevel=2,
+            )
+        module = str(e)
+    finally:
+        sys.path = orig_path
+    return module

pyoptsparse/pyPSQP/pyPSQP.py

@@ -1,11 +1,6 @@
 """
 pyPSQP - the pyPSQP wrapper
 """
-# Compiled module
-try:
-    from . import psqp  # isort: skip
-except ImportError:
-    psqp = None
 # Standard Python modules
 import datetime
 import os
@@ -17,6 +12,11 @@
 # Local modules
 from ..pyOpt_error import Error
 from ..pyOpt_optimizer import Optimizer
+from ..pyOpt_utils import try_import_compiled_module_from_path
+
+# import the compiled module
+THIS_DIR = os.path.dirname(os.path.abspath(__file__))
+psqp = try_import_compiled_module_from_path("psqp", THIS_DIR)
 
 
 class PSQP(Optimizer):
@@ -30,9 +30,8 @@ def __init__(self, raiseError=True, options={}):
         defOpts = self._getDefaultOptions()
         informs = self._getInforms()
 
-        if psqp is None:
-            if raiseError:
-                raise Error("There was an error importing the compiled psqp module")
+        if isinstance(psqp, str) and raiseError:
+            raise ImportError(psqp)
 
         super().__init__(name, category, defaultOptions=defOpts, informs=informs, options=options)
 

pyoptsparse/pyParOpt/ParOpt.py

@@ -6,34 +6,27 @@
 # External modules
 import numpy as np
 
-# isort: off
-# Attempt to import mpi4py.
+# Local modules
+from ..pyOpt_optimizer import Optimizer
+from ..pyOpt_utils import INFINITY, try_import_compiled_module_from_path
+
+# Attempt to import ParOpt/mpi4py
 # If PYOPTSPARSE_REQUIRE_MPI is set to a recognized positive value, attempt import
 # and raise exception on failure. If set to anything else, no import is attempted.
-if "PYOPTSPARSE_REQUIRE_MPI" in os.environ:
-    if os.environ["PYOPTSPARSE_REQUIRE_MPI"].lower() in ["always", "1", "true", "yes"]:
-        try:
-            from paropt import ParOpt as _ParOpt
-            from mpi4py import MPI
-        except ImportError:
-            _ParOpt = None
-    else:
-        _ParOpt = None
+if "PYOPTSPARSE_REQUIRE_MPI" in os.environ and os.environ["PYOPTSPARSE_REQUIRE_MPI"].lower() not in [
+    "always",
+    "1",
+    "true",
+    "yes",
+]:
+    _ParOpt = "ParOpt was not imported, as requested by the environment variable 'PYOPTSPARSE_REQUIRE_MPI'"
+    MPI = "mpi4py was not imported, as requested by the environment variable 'PYOPTSPARSE_REQUIRE_MPI'"
 # If PYOPTSPARSE_REQUIRE_MPI is unset, attempt to import mpi4py.
 # Since ParOpt requires mpi4py, if either _ParOpt or mpi4py is unavailable
 # we disable the optimizer.
 else:
-    try:
-        from paropt import ParOpt as _ParOpt
-        from mpi4py import MPI
-    except ImportError:
-        _ParOpt = None
-# isort: on
-
-# Local modules
-from ..pyOpt_error import Error
-from ..pyOpt_optimizer import Optimizer
-from ..pyOpt_utils import INFINITY
+    _ParOpt = try_import_compiled_module_from_path("paropt.ParOpt")
+    MPI = try_import_compiled_module_from_path("mpi4py.MPI")
 
 
 class ParOpt(Optimizer):
@@ -48,9 +41,9 @@ class ParOpt(Optimizer):
     def __init__(self, raiseError=True, options={}):
         name = "ParOpt"
         category = "Local Optimizer"
-        if _ParOpt is None:
-            if raiseError:
-                raise Error("There was an error importing ParOpt")
+        for mod in [_ParOpt, MPI]:
+            if isinstance(mod, str) and raiseError:
+                raise ImportError(mod)
 
         # Create and fill-in the dictionary of default option values
         self.defOpts = {}

pyoptsparse/pySLSQP/pySLSQP.py

@@ -2,11 +2,7 @@
 pySLSQP - A variation of the pySLSQP wrapper specificially designed to
 work with sparse optimization problems.
 """
-# Compiled module
-try:
-    from . import slsqp  # isort: skip
-except ImportError:
-    slsqp = None
+
 # Standard Python modules
 import datetime
 import os
@@ -16,8 +12,12 @@
 import numpy as np
 
 # Local modules
-from ..pyOpt_error import Error
 from ..pyOpt_optimizer import Optimizer
+from ..pyOpt_utils import try_import_compiled_module_from_path
+
+# import the compiled module
+THIS_DIR = os.path.dirname(os.path.abspath(__file__))
+slsqp = try_import_compiled_module_from_path("slsqp", THIS_DIR)
 
 
 class SLSQP(Optimizer):
@@ -30,9 +30,8 @@ def __init__(self, raiseError=True, options={}):
         category = "Local Optimizer"
         defOpts = self._getDefaultOptions()
         informs = self._getInforms()
-        if slsqp is None:
-            if raiseError:
-                raise Error("There was an error importing the compiled slsqp module")
+        if isinstance(slsqp, str) and raiseError:
+            raise ImportError(slsqp)
 
         self.set_options = []
         super().__init__(name, category, defaultOptions=defOpts, informs=informs, options=options)