Installation Instructions

Requirements

pyOptSparse has the following dependencies:

  • Python 3.7 or 3.8, though other Python 3 versions will likely work

  • C and Fortran compilers. We recommend gcc and gfortran which can be installed via the package manager for your operating system.

Please make sure these are installed and available for use. In order to use NSGA2, SWIG (v1.3+) is also required, which can be installed via the package manager. If those optimizers are not needed, then you do not need to install SWIG. Simply comment out the corresponding lines in pyoptsparse/pyoptsparse/setup.py so that they are not compiled. The corresponding lines in pyoptsparse/__init__.py must be commented out as well.

Python dependencies are automatically handled by pip, so they do not need to be installed separately. The only exception is numpy, which is required as part of the build process and therefore must be present before installing.

Note

  • In Linux, the python header files (python-dev) are also required.

  • We do not support operating systems other than Linux. If you want to run this on macOS or Windows, you are on your own.

Installation

The easiest and recommended way to install pyOptSparse is with pip. First clone the repository into a location which is not on the $PYTHONPATH, for example $HOME/packages/. Then in the root pyoptsparse folder type:

pip install .

For those not using virtual environments, a user install may be needed:

pip install . --user

If you plan to modify pyOptSparse, installing with the developer option, i.e. with -e, will save you from re-installing each time you modify the Python code.

It is also possible to install pyOptSparse by calling python setup.py install, but this is not recommended.

Note

Some optimizers are proprietary and their sources are not distributed with pyOptSparse. To use them, please follow the instructions on specific optimizer pages.

For those who intend to use pyOptSparse with IPOPT, OpenMDAO developers provide a bash script that simplifies the installation of the optimizer with different linear solvers.

Installing OptView

OptView and OptView-Dash have separate dependencies that must be installed. To install pyOptSparse including those dependencies, run:

pip install .[optview]

Testing

pyOptSparse provides a set of unit and regression tests to verify the installation. To run these tests, first install testflo which is a testing framework developed by the OpenMDAO team:

pip install testflo

Then, in the project root directory, type:

testflo . -v

to run all tests.

Update or Uninstall

To update pyOptSparse, first delete the build directory, then update the package using git. For stability, users are encouraged to stick to tagged releases. Install the package normally via pip.

To uninstall the package, type:

pip uninstall pyoptsparse

Note

pyOptSparse can optionally run in parallel if a suitable mpi4py installation exists. This will be automatically detected and imported at run-time.

If you only want to run in parallel, you can force pyOptSparse to do so by setting the environment variable PYOPTSPARSE_REQUIRE_MPI to anyone of these values: ['always', '1', 'true', 'yes'] If a suitable mpi4py is not available, an exception will be raised and the run terminated.

If you explicitly do not wish to use mpi4py, set the environment variable PYOPTSPARSE_REQUIRE_MPI to anything other than those values. This can come in handy, for example, if your MPI installation is not functioning properly, but you still need to run serial code.