Python and Computational Modelling

I have introduced teaching of Python to undegraduate engineers in 2004/2005, and the role of Python in our teaching and research has increased since then.

A Python course that teaches programming from the beginning but with a view for use in computational modelling in science and engineering is taught to our first year undergraduate engineering students. Similar material, albeit at a different pace, is taught to PhD students that take part in our interdisciplinary doctoral training centre programme in Next Generation Computational Modelling.

As of 2016/2017, we use

• the Anaconda python distribution to provide Python, Spyder and useful tools

• the Spyder editor as the default working environment

We provide

• slides used in the lectures and

• a book providing further details and useful for self-study

Advanced modules explore linking of compiled languages with Python, and parallel code.

Essential Software Engineering for Computational Science and Research

• About 100 slides are available as part of FEEG6002

Python in Research

Python is used in a large number of research projects, ranging from occasional data processing and visualisation on desktops and dedicated hardware, to parallel code running on supercomputers.

Some projects are listed here.

Research on Python for education

Some publications on Python in teaching and education:

• H. Fangohr. Exploiting Real-Time 3d Visualisation to Enthuse Students: A Case Study of Using Visual Python in Engineering.

  Lecture Notes on Computational Science 3992, 136-146 (2006)

  (Online: journal, postprint pdf)

• H. Fangohr. A Comparison of C, Matlab and Python as Teaching Languages in Engineering.

  Lecture Notes on Computational Science 3039, 1210-1217 (2004)

  (Online: journal , soton-eprints, postprint pdf)

• Hans Fangohr, Neil O’Brien, Anil Prabhakar, Arti Kashyap. Teaching Python programming with automatic assessment and feedback provision (online: Arxiv, 24 pages, 2015)