Carousel ia a framework for simulating mathematical models that decouples the models from the simulation implementation. It takes care of boilerplate routines such as loading data from various sources into a key store that can be used from any calculation, determining the correct order of calculations, stepping through dynamic simulations and generating output reports and visualizations, so that you can focus on developing models and don't have to worry about how to add new models or how to integrate changes.

• Built in integration of units and uncertainty.
• Built in management of input data, calculated outputs and formulas in simple key store.
• Boilerplate designs for reading data from various sources.
• Automatic determination of calculation order.
• Boilerplate designs for progress display and output reports.
• All configuration files use human readable JSON serialization.

• Pint
• NumPy
• xlrd
• nose
• sphinx
• SciPy
• Python-Dateutil
• UncertaintyWrapper

Carousel releases are on PyPI and on GitHub. You can use either pip or distutils to install Carousel.

pip :

$ pip install Carousel

Extract the archive to use disutils :

$ python setup.py install

Carousel documentation is online. It's also included in the distribution and can be built by running the Makefile found in the docs folder of the Carousel package. Documentation uses Sphinx, and built documentation will be found in the _build folder under the tree corresponding to the type of documentation built. EG: HTML documentation is in docs/_build/html.

Carousel source code is online. Fork it and report issues, make suggestions or create pull requests. Discuss the roadmap or download presentations on the wiki

The change log for all releases is on GitHub.