Ruff fixes

.github/build_real.sh

@@ -14,4 +14,4 @@ touch  ~/.config/pip/constraints.txt
 pip install .[optview,testing] -v
 
 # move pip constraints file back
-mv ~/.config/pip/constraints.txt.bkup ~/.config/pip/constraints.txt
+mv ~/.config/pip/constraints.txt.bkup ~/.config/pip/constraints.txt

.github/workflows/linux-build.yml

@@ -18,7 +18,7 @@ jobs:
         versions: [{python: "3.10", numpy: "1.22"}, {python: "3.11", numpy: "1.25"}, {python: "3.12", numpy: "2.1"}]
     steps:
       - uses: actions/checkout@v4
-      - uses: actions/setup-python@v5 
+      - uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.versions.python }}
       - name: Install runtime numpy ${{ matrix.versions.numpy }}

.gitignore

@@ -1,4 +1,8 @@
 syntax: glob
+
+# Ignore ruff and pre-commit config files
+.pre-commit-config.yaml
+
 build
 doc/_build
 *.pyc

.zenodo.json

@@ -16,4 +16,4 @@
             "name": "Joaquim R. R. A. Martins"
         }
     ]
-}
+}

doc/changes.rst

@@ -15,8 +15,8 @@ The following list summarizes some of the changes/improvements made to pyOpt to
 * User specification of design variable scaling
 * User specification of constraint scaling
 * Design variable returns in dictionary format only
-* Specification of linear constraints, dense or sparse 
-* Sparse non-linear Jacobians 
+* Specification of linear constraints, dense or sparse
+* Sparse non-linear Jacobians
 * New history file format. Uses SQLite dictionaries.
 * Fixed hot start bug where first call to user functions is a gradient. It is now guaranteed, that the first call is to the function evaluation, not the gradient.
 * Various bug fixes in SNOPT

doc/guide.rst

@@ -210,7 +210,7 @@ Linear constraints in pyOptSparse are defined exclusively by ``jac``, ``lower``,
 For linear constraint :math:`g_L \leq Ax + b \leq g_U`, the constraint definition would look like:
 
 .. code-block:: python
-  
+
   optProb.addConGroup("con", num_cons, linear=True, wrt=["xvars"], jac={"xvars": A}, lower=gL - b, upper=gU - b)
 
 Users should not provide the linear constraint values (i.e., :math:`g = Ax + b`) in a user-defined objective/constraint function.
@@ -310,4 +310,4 @@ See the optimizer-specific documentation page for more details.
 
 Postprocessing
 ++++++++++++++
-The result of the optimization is returned in a :class:`pyoptsparse.pyOpt_solution.Solution` object.
+The result of the optimization is returned in a :class:`pyoptsparse.pyOpt_solution.Solution` object.

doc/index.rst

@@ -12,7 +12,7 @@ Some key features of pyOptSparse include:
 
 
 pyOptSparse is a fork of `pyOpt <http://www.pyopt.org/>`_.
-However, it is not backwards compatible with pyOpt and thus optimization scripts will need to be modified to use pyOptSparse. 
+However, it is not backwards compatible with pyOpt and thus optimization scripts will need to be modified to use pyOptSparse.
 
 Getting Started
 ===============

doc/install.rst

@@ -93,7 +93,7 @@ To install pyOptSparse including those dependencies, run
 
     pip install .[optview]
 
-If you encounter a ``no module named tkinter`` error when trying to run optview, you may need to `install tkinter on your system <https://stackoverflow.com/questions/25905540/importerror-no-module-named-tkinter>`__. 
+If you encounter a ``no module named tkinter`` error when trying to run optview, you may need to `install tkinter on your system <https://stackoverflow.com/questions/25905540/importerror-no-module-named-tkinter>`__.
 
 Testing
 -------

doc/optimizers/CONMIN.rst

@@ -16,4 +16,3 @@ API
 
 .. autoclass:: CONMIN
    :members: __call__
-

doc/optimizers/IPOPT.rst

@@ -34,4 +34,3 @@ API
 
 .. autoclass:: IPOPT
    :members: __call__
-

doc/optimizers/NLPQLP.rst

@@ -32,4 +32,3 @@ API
 
 .. autoclass:: NLPQLP
    :members: __call__
-

doc/optimizers/NSGA2.rst

@@ -26,4 +26,3 @@ API
 
 .. autoclass:: NSGA2
    :members: __call__
-

doc/optimizers/PSQP.rst

@@ -22,4 +22,3 @@ API
 
 .. autoclass:: PSQP
    :members: __call__
-

doc/optimizers/SLSQP.rst

@@ -27,4 +27,3 @@ API
 
 .. autoclass:: SLSQP
    :members: __call__
-

doc/optimizers/SLSQP_options.yaml

@@ -1,10 +1,10 @@
-ACC: 
+ACC:
   desc: Convergence Accurancy
-MAXIT: 
+MAXIT:
   desc: Maximum Iterations
-IPRINT: 
+IPRINT:
   desc: Output Level (<0 - None, 0 - Screen, 1 - File)
-IOUT: 
+IOUT:
   desc: Output Unit Number
-IFILE: 
+IFILE:
   desc: Output File Name

doc/optimizers/SNOPT.rst

@@ -16,7 +16,7 @@ Installation
 
 Building from source
 ********************
-SNOPT is available for purchase `here 
+SNOPT is available for purchase `here
 <http://www.sbsi-sol-optimize.com/asp/sol_snopt.htm>`_. Upon purchase, you should receive a zip file. Within the zip file, there is a folder called ``src``. To use SNOPT with pyoptsparse, paste all files from ``src`` except snopth.f into ``pyoptsparse/pySNOPT/source``.
 
 From v2.0 onwards, only SNOPT v7.7.x is officially supported.
@@ -65,4 +65,3 @@ API
 
 .. autoclass:: SNOPT
    :members: __call__
-

doc/postprocessing.rst

@@ -26,7 +26,7 @@ Requirements
       \-axisartist (OptView)
     numpy (OptView)
 
-For installation instructions, see :ref:`install_optview`.  
+For installation instructions, see :ref:`install_optview`.
 Although not necessary for most usage, the ``dill`` package is needed if you wish to save an editable version of the graph produced in ``OptView``.
 ``dill`` can be installed via ``pip`` in a terminal using
 

doc/pyoptsparse.bib

@@ -608,4 +608,4 @@ @article{Lyu2015b
     volume   = {53},
     year     = {2015},
     keywords = {MACH}
-}
+}

doc/quickstart.rst

@@ -27,15 +27,15 @@ For the TP37, the objective function is a simple analytic function:
 
 Notes:
 
-*   The ``xdict`` variable is a dictionary whose keys are the names from each 
-    :meth:`~pyoptsparse.pyOpt_optimization.Optimization.addVar` and 
+*   The ``xdict`` variable is a dictionary whose keys are the names from each
+    :meth:`~pyoptsparse.pyOpt_optimization.Optimization.addVar` and
     :meth:`~pyoptsparse.pyOpt_optimization.Optimization.addVarGroup` call. The line
 
     .. code-block:: python
 
         x = xdict["xvars"]
 
-    retrieves an array of length 3 which are all the variables for this optimization. 
+    retrieves an array of length 3 which are all the variables for this optimization.
 
 *   The line
 
@@ -62,7 +62,7 @@ Now the optimization problem can be initialized:
     :end-before: # rst begin addVar
 
 This creates an instance of the optimization class with a name and a reference to the objective function.
-To complete the setup of the optimization problem, the design variables and constraints need to be defined. 
+To complete the setup of the optimization problem, the design variables and constraints need to be defined.
 
 Design variables and constraints can be added either one-by-one or as a group.
 Adding variables by group is generally recommended for related variables:
@@ -84,7 +84,7 @@ It is recommended that related constraints are added by group where possible:
     :end-before: # rst begin addObj
 
 This call adds two variables with name ``con``.
-There is no lower bound for the variables and the upper bound is 0.0. 
+There is no lower bound for the variables and the upper bound is 0.0.
 
 We must also assign the the key value for the objective using the
 :meth:`~pyoptsparse.pyOpt_optimization.Optimization.addObj` call:
@@ -112,9 +112,9 @@ which produces the following table::
 
       Variables (c - continuous, i - integer, d - discrete)
          Index  Name      Type      Lower Bound            Value      Upper Bound     Status
-            0  xvars_0      c     0.000000E+00     1.000000E+01     4.200000E+01           
-            1  xvars_1      c     0.000000E+00     1.000000E+01     4.200000E+01           
-            2  xvars_2      c     0.000000E+00     1.000000E+01     4.200000E+01           
+            0  xvars_0      c     0.000000E+00     1.000000E+01     4.200000E+01
+            1  xvars_1      c     0.000000E+00     1.000000E+01     4.200000E+01
+            2  xvars_2      c     0.000000E+00     1.000000E+01     4.200000E+01
 
       Constraints (i - inequality, e - equality)
          Index  Name Type          Lower           Value           Upper    Status  Lagrange Multiplier (N/A)
@@ -152,7 +152,7 @@ which produces the following output::
    ================================================================================
       Objective Function: objfunc
 
-      Solution: 
+      Solution:
    --------------------------------------------------------------------------------
       Total Time:                    0.0062
          User Objective Time :       0.0001
@@ -169,9 +169,9 @@ which produces the following output::
 
       Variables (c - continuous, i - integer, d - discrete)
          Index  Name      Type      Lower Bound            Value      Upper Bound     Status
-            0  xvars_0      c     0.000000E+00     2.399997E+01     4.200000E+01           
-            1  xvars_1      c     0.000000E+00     1.200001E+01     4.200000E+01           
-            2  xvars_2      c     0.000000E+00     1.200000E+01     4.200000E+01           
+            0  xvars_0      c     0.000000E+00     2.399997E+01     4.200000E+01
+            1  xvars_1      c     0.000000E+00     1.200001E+01     4.200000E+01
+            2  xvars_2      c     0.000000E+00     1.200000E+01     4.200000E+01
 
       Constraints (i - inequality, e - equality)
          Index  Name Type          Lower           Value           Upper    Status  Lagrange Multiplier (N/A)

doc/requirements.txt

@@ -1,2 +1,2 @@
 sphinx_mdolab_theme>=1.2
-sphinx-codeautolink
+sphinx-codeautolink

meson.build

@@ -42,4 +42,4 @@ else
 endif
 py3_dep = py3_target.dependency()
 
-subdir('pyoptsparse')
+subdir('pyoptsparse')

meson_options.txt

@@ -6,4 +6,4 @@ option('python_target', type: 'string', value: '',
     to be built for is different than the Python installation that is used to run Meson. For example, Meson may be installed
     on the user's system which is run using the system Python installation, but the user may want build PyOptSparse for
     a Python installation in a virtual environment. Leave as an empty string to build for Python installation running
-    Meson.''')
+    Meson.''')

paper/paper.md

@@ -49,7 +49,7 @@ At time of writing, the latest released version of pyOptSparse is v2.2.0.
 pyOptSparse provides built-in support for several popular proprietary and open-source optimizers.
 Each optimizer usually has its own way to specify the problem:
 It might require different constraint ordering, have different ways of specifying equality constraints, or use a sparse matrix format to represent the constraint Jacobian.
-pyOptSparse provides a common Python interface for the various optimizers that hides these differences from the user. 
+pyOptSparse provides a common Python interface for the various optimizers that hides these differences from the user.
 By isolating the optimization problem definition from the optimizer, the user can easily switch between different optimizers applied to the same optimization problem.
 The optimizer can be switched by editing a single line of code.
 

pyoptsparse/postprocessing/assets/base-styles.css

@@ -390,4 +390,4 @@ there.
 @media (min-width: 1000px) {}
 
 /* Larger than Desktop HD */
-@media (min-width: 1200px) {}
+@media (min-width: 1200px) {}

pyoptsparse/postprocessing/assets/custom-styles.css

@@ -12,4 +12,4 @@
 .plot-container {
     height: 90vh;
     width: 100vh;
-}
+}

pyoptsparse/postprocessing/meson.build

@@ -24,4 +24,4 @@ py3_target.install_sources(
   asset_sources,
   pure: true,
   subdir: 'pyoptsparse/postprocessing/assets'
-)
+)

pyoptsparse/pyALPSO/LICENSE

@@ -2,7 +2,7 @@ ALPSO - Augmented Lagrangian Particle Swarm Optimizer
 Copyright (c) 2011, Dr. Ruben E. Perez ([email protected])
                 and Peter W. Jansen ([email protected])
 
-ALPSO is free software: you can redistribute it and/or modify it 
+ALPSO is free software: you can redistribute it and/or modify it
 under the terms of the GNU General Public License as published by
 the Free Software Foundation, either version 3 of the License, or
 any later version.
@@ -15,19 +15,19 @@ GNU General Public License for more details.
 You should have received a copy of the GNU General Public License
 along with this program. If not, see <http://www.gnu.org/licenses/>.
 
-Non-free versions of ALPSO are available under terms different 
-from those of the General Public License. For more information 
-related to such a license, future developments and/or technical 
-support, contact Dr. Ruben E. Perez ([email protected]) or 
+Non-free versions of ALPSO are available under terms different
+from those of the General Public License. For more information
+related to such a license, future developments and/or technical
+support, contact Dr. Ruben E. Perez ([email protected]) or
 Peter W. Jansen ([email protected]).
 
-In addition, we kindly ask you to acknowledge the code authors in 
-any program, application or publication in which you use it. For 
+In addition, we kindly ask you to acknowledge the code authors in
+any program, application or publication in which you use it. For
 published works that use ALPSO we suggest referencing:
 
-P. Jansen and R. Perez, "Constrained Structural Design Optimization 
-via a Parallel Augmented Lagrangian Particle Swarm Optimization 
-Approach", International Journal of Computers and Structures, 
+P. Jansen and R. Perez, "Constrained Structural Design Optimization
+via a Parallel Augmented Lagrangian Particle Swarm Optimization
+Approach", International Journal of Computers and Structures,
 Vol. 89, No. 13-14, pp. 1352–1366, 2011.
 
 ----------------------------------------------------------------------

pyoptsparse/pyALPSO/meson.build

@@ -10,4 +10,4 @@ py3_target.install_sources(
   python_sources,
   pure: true,
   subdir: 'pyoptsparse/pyALPSO'
-)
+)

pyoptsparse/pyALPSO/pyALPSO.py

@@ -211,8 +211,8 @@ def _on_setOption(self, name, value):
                     from . import alpso_ext
 
                     self.alpso = alpso_ext
-                except ImportError:
-                    raise ImportError("pyALPSO: ALPSO EXT shared library failed to import.")
+                except ImportError as e:
+                    raise ImportError("pyALPSO: ALPSO EXT shared library failed to import.") from e
 
     def _communicateSolution(self, sol):
         if sol is not None:

pyoptsparse/pyCONMIN/LICENSE

@@ -14,7 +14,7 @@ GNU General Public License for more details.
 
 You should have received a copy of the GNU General Public License
 along with this program; if not, write to the Free Software
-Foundation, Inc., 59 Temple Place, Suite 330, Boston, 
+Foundation, Inc., 59 Temple Place, Suite 330, Boston,
 MA 02111-1307 USA.
 
 ----------------------------------------------------------------------

pyoptsparse/pyCONMIN/source/README

@@ -1,4 +1,4 @@
-This directory contains the Fortran 77 source for CONMIN 
-modified for pyOpt interfacing by Dr. Ruben E. Perez, 
-plus two helper files called openunit.f and closeunit.f 
+This directory contains the Fortran 77 source for CONMIN
+modified for pyOpt interfacing by Dr. Ruben E. Perez,
+plus two helper files called openunit.f and closeunit.f
 to manipulate Fortran units from Python.