Learn more about Python, ipython and the notebook

The ipython interpreter is basically a more user-friendly version of the standard Python interpreter with an enhanced interactive shell that makes it easy to visualize data. It also provides the ipython notebook, a browser-based notebook with support for text, mathematical expressions, inline plots and inline Python scripts. We really think it is a very powerful tool and recommend that you spend some time familiarising yourself with ipython and the notebook. Here are some useful links to learn about Python and associated libraries.

• A good starting point to learn about scientific computing with Python and related ideas is Software carpentry, which provides nice video/slides lectures on Python

• For an interactive overview, see the well-written set of lectures on scientific computing with Python using Ipython notebooks

• To learn the Python language itself the recommended starting point is the standard Python tutorial.

• A more detailed set of lectures is the Scipy lecture notes.

• Python has a large number of libraries, which can be used in combination with TRIQS. For example:

  • The Python standard library is already very rich.

  • Numpy allows to manipulate multidimensional arrays (cf also the tutorial).

  • Scipy includes many packages for scientific computing.

  • Matplotlib offers very nice plotting tools that can be integrated into your Python scripts.

  • SymPy provides symbolic algebra capabilities.