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pyOpt Development Zone

pyOpt is an open-source Python package for formulating and solving nonlinear constrained optimization problems that integrates open and licensed gradient-based, gradient-free, and population-based optimization algorithms.

We seek community input for bug reports, feature suggestions, design feedback, code contributions and reviews.

Issue Tracker


pyOpt issue tracker will be available soon ...

For bug reports, feature suggestions, design feedback please use the pyOpt issue tracker:

Alternatively, you can contact directly the code developers.

Source Code Repository

The pyOpt master source repository uses Subversion

To check out the latest pyOpt sources use:

>>> svn co pyOpt

Contributing code

We accept code for new features, bug fixes, documentation, and tests. Any contributions to our program are always welcome, graciously acknowledged, and carefully documented.

The best way to contribute is to:

  1. Use the tracker to find an existing ticket or open a new ticket related to the contribution.

  2. Add code, patches, or pull requests to that ticket.

  3. After the ticket, and associated code contribution has been posted, the developers will review the ticket. If the code works correctly, passes checkout tests, and has clear documentation it will be pushed to the master pyOpt repository and the ticket will be closed.

    Note that reviewing code takes a lot of time and attention to detail. Everyone is welcome and encouraged to review tickets and suggest appropriate modifications or recommendation for inclusion into pyOpt. To speedup the review process please make sure the code contributions follow the Code Developing Guidelines.

On special circumstances, contributors can contact the developers to gain authenticated access to the source repository.

Developer Team

Contributing Developers

  • Sandy Mader
  • Gaetan Kenway
  • Andrew Lambe
  • Chris Marriage
  • Benjamin Chalovich
  • Joaquim Martins
  • Steve Choi