Projects using Boost.Python
This is a partial list of projects using Boost.Python. If you are using Boost.Python as your Python/C++ binding solution, we'd be proud to list your project on this page. Just post a short description of your project and how Boost.Python helps you get the job done, and we'll add it to this page .
Tom Barket of Fortress writes:
We have a large C++ analytical library specialized for research in finance and economics, built for speed and mission critical stability. Yet Python offers us the flexibility to test out new ideas quickly and increase the productivity of our time versus working in C++. There are several key features which make Python stand out. Its elegance, stability, and breadth of resources on the web are all valuable, but the most important is its extensibility, due to its open source transparency. Boost.Python makes Python extensibility extremely simple and straightforward, yet preserves a great deal of power and control.
KDE Interactive Geometry is a high-school level educational tool, built for the KDE desktop. It is a nice tool to let students work with geometrical constructions. It is meant to be the most intuitive, yet featureful application of its kind.
Versions after 0.6.x (will) support objects built by the user himself in the Python language. The exporting of the relevant internal API's were done using Boost.Python, which made the process very easy.
Dan Nuffer writes:
I'm using Boost.Python to wrap the client API of OpenWBEM.This will make it easier to do rapid prototyping, testing, and scripting when developing management solutions that use WBEM.
Ben Young writes:
Boost.Python is used in an automated process to generate python bindings to our api which is exposed though multiple backends and frontends. This allows us to write quick tests and bespoke scripts to perform one off tasks without having to go through the full compilation cycle.
Before the web page came online, Paul F. Kunz wrote:
Don't have a web page for the project, but the organization's is http://www.slac.stanford.edu (the first web server site in America, I installed it).Which was just too cool a piece of trivia to omit.
Peter Bienstman writes:
Thanks for providing such a great tool!
The cctbx grew together with Boost.Python and is designed from the ground up as a hybrid Python/C++ system. With one minor exception, run-time polymorphism is completely handled by Python. C++ compile-time polymorphism is used to implement performance critical algorithms. The Python and C++ layers are seamlessly integrated using Boost.Python.
The SourceForge cctbx project is organized in modules to facilitate use in non-crystallographic applications. The scitbx module implements a general purpose array family for scientific applications and pure C++ ports of FFTPACK and the LBFGS conjugate gradient minimizer.
Pere Mato Vila writes:
We are using Boost.Python to provide scripting/interactive capability to our framework. We have a module called "GaudiPython" implemented using Boost.Python that allows the interaction with any framework service or algorithm from python. RootPython also uses Boost.Python to provide a generic "gateway" between the ROOT framework and python
Boost.Python is great. We managed very quickly to interface our framework to python, which is great language. We are trying to facilitate to our physicists (end-users) a rapid analysis application development environment based on python. For that, Boost.Python plays and essential role.
Bruno da Silva de Oliveira writes:
Recently we moved our work from working exclusively with C++ to an hybrid-language approach, using Python and C++, with Boost.Python providing the layer between the two. The results are great so far!
Two projects have been developed so far with this technology:
Simba provides 3D visualization of geological formations gattered from the simulation of the evolution of oil systems, allowing the user to analyse various aspects of the simulation, like deformation, pressure and fluids, along the time of the simulation.
Aero aims to construct a CFD with brazilian technology, which involves various companies and universities. ESSS is responsible for various of the application modules, including GUI and post-processing of results.
For our internal software, we implement core data structures in C and expose them to Python using Boost.Python. Algorithm development is done in Python and then translated to C if required (often it's not). This hybrid development approach not only greatly increases our productivity, but it also allows "non-developers" (people without C experience) to take part in method development. Learning C is a daunting task, but "Python fits your brain." (Thanks to Bruce Eckel for the quote.)
The core of the smart card reader management is written in C++ but all the development tools are written in the friendly Python language. Boost plays the fundamental role of binding the tools to our core smart card reader library.
Revised 15 July, 2003
© Copyright Dave Abrahams 2002-2003. All Rights Reserved.