Install Chrono::PyEngine

There are two options for installing Chrono::PyEngine on your computer, A) or B). The first is for users that are not interested in the C++ API.

A) Install precompiled Python modules

For users that do not want to install the entire Chrono::Engine API there is a precompiled installer. Do this:

  1. download and install Python (only Python version 3.2 or greater is supported)
  2. download and install the Chrono::PyEngine module for Python, using the installer in our download section.
You do not need to install the entire C++ API/SDK of Chrono, in this case.
Note that there are separate installers for the 32 bit or 64 bit distributions of Python. Do not mix 32bit with 64bit. We suggest you to use the 64 bit Python and, consequently, the 64 bit Chrono::PyEngine
Note that the releases of the installers in our download page might be lagging behind the most recent Chrono API: if you want to exploit the most recent features, you should use the following second method.

B) Build Python modules from the C++ API

Advanced users that use the entire Chrono::Engine C++ API can build Chrono::PyEngine from scratch. This is the preferred way to have the most updated Chrono::PyEngine, but it is more complicated. Do this:

  1. install the Chrono API with C++ source code and build it,
  2. install Python (only Python version 3.2 or greater is supported)
  3. build the Chrono::PyEngine module, following these instructions

Tips

We suggest you to use a specialized IDE editor that nicely handles the Python language (syntax highlighting, auto completion of text, etc.). The default IDE installed with most Python distribution is IDLE: it is nice but we suggest a suggest to install a more powerful editor: PyScripter, that is free.
We suggest to install also the following third party packages for expanding the capabilities of Python in mathematical ad plotting areas:

  • Numpy
  • Matplotlib.
    NOTE. Precompiled binaries of Numpy and Matplotlib for Python 3.2 can be downloaded from the unofficial repository. A faster option is to install the entire SciPy stack that includes both. Otherwise there is a custom Python distribution called Enthough that already includes the two packages.