Advanced Scientific Programming in Python
a Summer School by the G-Node and the Physik-Institut, University of Zurich
Scientists spend more and more time writing, maintaining, and
debugging software. While techniques for doing this efficiently have
evolved, only few scientists actually use them. As a result, instead
of doing their research, they spend far too much time writing
deficient code and reinventing the wheel. In this course we will
present a selection of advanced programming techniques,
incorporating theoretical lectures and practical exercises tailored
to the needs of a programming scientist. New skills will be tested
in a real programming project: we will team up to develop an
entertaining scientific computer game.
We use the Python programming language for the entire course. Python
works as a simple programming language for beginners, but more
importantly, it also works great in scientific simulations and data
analysis. We show how clean language design, ease of extensibility,
and the great wealth of open source libraries for scientific
computing and data visualization are driving Python to become a
standard tool for the programming scientist.
This school is targeted at Master or PhD students and Post-docs from
all areas of science. Competence in Python or in another language
such as Java, C/C++, MATLAB, or Mathematica is absolutely required.
Basic knowledge of Python is assumed. Participants without any prior
experience with Python should work through the proposed introductory
materials before the course.
Date and Location
September 1—6, 2013. Zürich, Switzerland.
Day 0 (Sun Sept 1) — Best Programming Practices
- Best Practices, Development Methodologies and the Zen of Python
- Version control with git
- Object-oriented programming & design patterns
Day 1 (Mon Sept 2) — Software Carpentry
- Test-driven development, unit testing & quality assurance
- Debugging, profiling and benchmarking techniques
- Best practices in data visualization
- Programming in teams
Day 2 (Tue Sept 3) — Scientific Tools for Python
- Advanced NumPy
- The Quest for Speed (intro): Interfacing to C with Cython
- Advanced Python I: idioms, useful built-in data structures, generators
Day 3 (Wed Sept 4) — The Quest for Speed
- Writing parallel applications in Python
- Programming project
Day 4 (Thu Sept 5) — Efficient Memory Management
- When parallelization does not help:
the starving CPUs problem
- Advanced Python II: decorators and context managers
- Programming project
Day 5 (Fri Sept 6) — Practical Software Development
- Programming project
- The Pelita Tournament
Every evening we will have the tutors' consultation hour : Tutors will
answer your questions and give suggestions for your own projects.
You can apply on-line at http://python.g-node.org
Applications must be submitted before 23:59 CEST, May 1, 2013.
Notifications of acceptance will be sent by June 1, 2013.
No fee is charged but participants should take care of travel,
living, and accommodation expenses. Candidates will be selected on
the basis of their profile. Places are limited: acceptance rate is
usually around 20%. Prerequisites: You are supposed to know the
basics of Python to participate in the lectures. You are encouraged
to go through the introductory material available on the website.
- Francesc Alted, Continuum Analytics Inc., USA
- Pietro Berkes, Enthought Inc., UK
- Valentin Haenel, freelance developer and consultant, Berlin, Germany
- Zbigniew Jędrzejewski-Szmek, Krasnow Institute,
George Mason University, USA
- Eilif Muller, Blue Brain Project, École Polytechnique Fédérale de
- Emanuele Olivetti, NeuroInformatics Laboratory, Fondazione Bruno
Kessler and University of Trento, Italy
- Rike-Benjamin Schuppner, Technologit GbR, Germany
- Bartosz Teleńczuk, Unité de Neurosciences Information et Complexité,
- Stéfan van der Walt, Applied Mathematics, Stellenbosch University,
- Bastian Venthur, Berlin Institute of Technology and Bernstein Focus
- Niko Wilbert, TNG Technology Consulting GmbH, Germany
- Tiziano Zito, Institute for Theoretical Biology, Humboldt-Universität
zu Berlin, Germany
Organized by Nicola Chiapolini and colleagues of the Physik-Institut,
University of Zurich, and by Zbigniew Jędrzejewski-Szmek and Tiziano Zito for
the German Neuroinformatics Node of the INCF.